Phone: +41 26 429 65 89
Role: Main Applicant
Description du projet :
All research projects are in the following fields:
Financing resources :
Research team within HES-SO:
Abou Khaled Omar
Durée du projet:
16.07.2013 - 16.06.2030
Url of the project site:
Quentin Meteier, Mira El Kamali, Leonardo Angelini, Omar Abou Khaled
23, 18, 7974
Link to the publication
Photovoltaic installations can be environmentally beneficial to a greater or lesser extent, depending on the conditions. If the energy produced is not used, it is redirected to the grid, otherwise a battery with a high ecological footprint is needed to store it. To alleviate this problem, an innovative recommender system is proposed for residents of smart homes equipped with battery-free solar panels to optimise the energy produced. Using artificial intelligence, the system is designed to predict the energy produced and consumed for the day ahead using three data sources: sensor logs from the home automation solution, data collected by the solar inverter, and weather data. Based on these predictions, recommendations are then generated and ranked by relevance. Data collected over 76 days were used to train two variants of the system, considering or without considering energy consumption. Recommendations selected by the system over 14 days were randomly picked to be evaluated for relevance, ranking, and diversity by 11 people. The results show that it is difficult to predict residents’ consumption based solely on sensor logs. On average, respondents reported that 74% of the recommendations were relevant, while the values contained in them (i.e., accuracy of times of day and kW energy) were accurate in 66% (variant 1) and 77% of cases (variant 2). Also, the ranking of the recommendations was considered logical in 91% and 88% of cases. Overall, residents of such solar-powered smart homes might be willing to use such a system to optimise the energy produced. However, further research should be conducted to improve the accuracy of the values contained in the recommendations.
Marine Capallera, Quentin Meteier, Marino Widmer, Leonardo Angelini, Stefano Carrino, Andreas Sonderegger, Omar Abou Khaled, Elena Mugellini
2023, vol. 11, pp. 5746-5771
Advanced driver assistances are becoming increasingly common in commercial cars, not only to assist but also to free drivers from manual driving whenever possible. Soon, drivers should be allowed to engage in non-driving-related tasks. The fact that responsibility for driving is shifting from humans to machines must be considered in the development of these assistances in order to guarantee safety and trust. In this article, we introduce AdVitam (for Advanced Driver-Vehicle Interaction to Make future driving safer), an autonomous system aiming at maintaining driver’s situation awareness and optimizing takeover quality during conditionally automated driving. The information conveyed to drivers is dynamically adapted to achieve these goals, depending on the driving environment and the driver’s physiological state. This system consists of three connected modules. The first module (Driver State) predicts the driver’s state with machine learning and physiological signals as inputs. The second module (Supervision) uses different interfaces (a haptic seat, a personal device, and ambient lights) to maintain the drivers’ situation awareness during the autonomous driving phases. The third module (Intervention) is a machine learning model that chooses the most appropriate combination among haptic, auditory, and visual modalities to request the driver to take over control and thus optimize takeover quality. To evaluate the system and each module independently, a preliminary user study with 35 drivers was conducted in a fixed-base driving simulator. All participants drove in two different environments (rural and urban). In addition, the activation of the Supervision and Intervention modules were manipulated as two between-subject factors. Results show that conveying information on the driving environment status through multimodal interfaces increases drivers’ situation awareness (i.e., better identification of potential problems in the environment) and trust in the automated vehicle. However, the system does not show positive outcomes on takeover quality. Besides, the Driver State module provided consistent predictions with the experimental manipulation. The system proposed in this paper could lead to better acceptance and safety when conditionally automated vehicles will be released by increasing drivers’ trust during phases of automated driving.
Marine Capallera, Leonardo Angelini, Quentin Meteier, Omar Abou Khaled, Elena Mugellini
IEEE Transactions on Intelligent Vehicles,
2023, Vol. 8, n° 3, pp. 2551 - 2567
Autonomous driving will change the role of the driver. From being the main actor in driving, the driver will now have a supervisory role during the autonomous driving phases. However, if the driver has to take over control of the vehicle, he must be aware of the situation around him. This is why it is important to develop interfaces to keep him in the loop. This article proposes a systematic review of Human Vehicle Interaction (HVI) providing situation awareness in the context of autonomous driving. 37 articles presenting such interactions are analyzed in terms of design of the interaction (modalities, location, conveyed information) but also in term of evaluation and experimental conditions. We present an overview of previous studies in order to highlight the work already done or in progress. Current studies present mainly monomodal interfaces although the evaluation of multimodal interactions present promising results in this field.
Leonardo Angelini, Mira El Kamali, Elena Mugellini, Omar Abou Khaled, Christina Röcke, Simone Porcelli, Alfonso Mastropietro, Giovanni Rizzo, Noemi Boqué, Josep Maria Del Bas, Filippo Palumbo, Michele Girolami, Antonino Crivello, Canan Ziylan, Paula Subías-Beltrán, Silvia Orte, Carlo Emilio Standoli, Laura Fernandez Maldonado, Maurizio Caon, Martin Sykora, Suzanne Elayan, Sabrina Guye, Giuseppe Andreoni
2022, vol. 10, no 2, pp. 50-77
This article describes the coaching strategies of the NESTORE e-coach, a virtual coach for promoting healthier lifestyles in older age. The novelty of the NESTORE project is the definition of a multi-domain personalized pathway where the e-coach accompanies the user throughout different structured and non-structured coaching activities and recommendations. The article also presents the design process of the coaching strategies, carried out including older adults from four European countries and experts from the different health domains, and the results of the tests carried out with 60 older adults in Italy, Spain and The Netherlands.
Christina Röcke, Leonardo Angelini, Sabrina Guye, Mira El Kamali, Maurizio Caon, Omar Abou Khaled, Elena Mugellini
Dans Andreoni, Giuseppe, Mambretti, Cinzia, Digital health technology for better aging: a multidisciplinary approach
(Pp. 161-177). 2021,
Cham : Springer
Link to the publication
This chapter discusses the theoretical behaviour change framework and its integration and implementation of behaviour change techniques that form the conceptual psychological basis for innovative but efficient coaching approach. We review the current state of e-coaching solutions for older adults that can be found in the literature and identify gaps. Finally, we review and discuss the technological implementation of behaviour change techniques applied in NESTORE to support healthy older adults to adopt a healthy lifestyle in all NESTORE well-being domains as reference case study.
Filippo Palumbo, Antonino Crivello, Francesco Furfari, Michele Girolami, Alfonso Mastropietro, Giorgio Manfredelli, Christina Röcke, Sabrina Guye, Antoni Salvá Casanovas, Maurizio Caon, Francesco Carrino, Omar Abou Khaled, Elena Mugellini, Enrico Denna, Marco Mauri, David Ward, Paula Subías-Beltrán, Silvia Orte, Ciprian Candea, Gabriele Candea, Giovanna Rizzo
Frontiers in Digital Health,
2020, vol. 2, article 545949, pp. 1-17
In the context of the fourth revolution in healthcare technologies, leveraging monitoring and personalization across different domains becomes a key factor for providing useful services to maintain and promote well-being. This is even more crucial for older people, with aging being a complex multi-dimensional and multi-factorial process which can lead to frailty. The NESTORE project was recently funded by the EU Commission with the aim of supporting healthy older people to sustain their well-being and capacity to live independently. It is based on a multi-dimensional model of the healthy aging process that covers physical activity, nutrition, cognition, and social activity. NESTORE is based on the paradigm of the human-in-the-loop cyber-physical system that, exploiting the availability of Internet of Things technologies combined with analytics in the cloud, provides a virtual coaching system to support healthy aging. This work describes the design of the NESTORE methodology and its IoT architecture. We first model the end-user under several domains, then we present the NESTORE system that, analyzing relevant key-markers, provides coaching activities and personalized feedback to the user. Finally, we describe the validation strategy to assess the effectiveness of NESTORE as a coaching platform for healthy aging.
Quentin Meteier, Marine Capallera, Andreas Sonderegger, Leonardo Angelini, Stefano Carrino, Elena Mugellini, Omar Abou Khaled
Proceedings of AutomotiveUI '20: 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 21-22 September 2020, Online Conference,
In conditionally automated driving, drivers do not have to constantly monitor their vehicle but they must be able to take over control when necessary. In this paper, we assess the impact of instructions about limitations of automation and the presentation of context-related information through a mobile application on the situation awareness and takeover performance of drivers. We conducted an experiment with 80 participants in a fixed-base driving simulator. Participants drove for an hour in conditional automation while performing secondary tasks on a tablet. Besides, they had to react to five different takeover requests. In addition to the assessment of behavioral data (e.g. quality of takeover), participants rated their situation awareness after each takeover situation. Instructions and context-related information on limitations combined showed encouraging results to raise awareness and improve takeover performance.
Maurizio Caon, Rico Süsse, Benoit Grelier, Omar Abou Khaled, Elena Mugellini
2020, vol. 66, pp. 933-944
Connected bike computers can support professional cyclists in achieving better performances but interacting with them requires taking their hands off the handlebar compromising focus and safety.
This research aims at exploring the design of an ergonomic interface based on micro-gestures that can allow cyclists to interact with a device while holding the handlebar.
Three different studies were conducted with seven professional cyclists adopting the gesture-elicitation technique. One study aimed at eliciting free micro-gestures; a second to evaluate gestures recognizable with a smart glove; the last focused on the gestures recognized through an interactive armband.
The analysis of the micro-gestures elicited during these studies allowed producing a first set of guidelines to design gestural interfaces for drop-bars (a specific type of handlebar for road bikes). These guidelines suggest which fingers to use and how to design their movement in order to provide an ergonomic interface. It also introduces the principle of symmetry for the attribution of symbols to symmetric referents. Finally, it provides suggestions on the design of the interactive drop-bar.
The guidelines provided in this paper can support the design of gestural interfaces for professional cyclists that can enhance performance and increase safety.
Mira El Kamali, Leonardo Angelini, Maurizio Caon, Francesco Carrino, Christina Röcke, Sabrina Guye, Giovanna Rizzo, Alfonso Mastropietro, Martin Sykora, Suzanne Elayan, Isabelle Kniestedt, Canan Ziylan, Emanuele Lettieri, Omar Abou Khaled, Elena Mugellini
2020, vol. 8, pp. 101884-101902
Virtual Coaches, also known as e-coaches, are a disruptive technology in healthcare. Indeed, among other usages, they might provide cost-effective solutions for increasing human wellbeing in different domains, such as physical, nutritional, cognitive, social, and emotional. This paper presents a systematic review of virtual coaches specifically aimed at improving or maintaining older adults' health in the aforementioned domains. Such digital systems assume various forms, from classic apps, to more advanced conversational agents or robots. Fifty-six articles describing a virtual coach for older adults and aimed at improving their wellbeing were identified and further analyzed. In particular, we presented how previous studies defined their virtual coaches, which behavioral change models and techniques they adopted and the overall system architecture, in terms of monitoring solutions, processing methods and modalities for intervention delivery. Our results show that few thorough evaluations of e-coaching systems have been conducted, especially regarding multi-domain coaching approaches. Through our analysis, we identified the wellbeing domains that should be addressed in future studies as well as the most promising behavior change models and techniques and coaching interfaces. Previous work illustrates that older adults often appreciate conversational agents and robots. However, the lack of a multidomain intervention approach in the current literature motivates us to seek to define future solutions.
Carrino Francesco, Moullet Valentin, Abou Khaled Omar, Mugellini Elena, Maggiori Christian
Dans T. Ahram, R. Taiar, V. Gremeaux-Bader & K. Aminian,
Human Interaction, Emerging Technologies and Future Applications II. 2020,
Cham, Switzerland : Advances in Intelligent Systems and Computing
Cherix Robin, Piérart Geneviève, Abou Khaled Omar, Mugellini Elena,
HCI International 2020 - Late Breaking Papers., 2020
Martina Caramenti, Claudio L. Lafortuna, Elena Mugellini, Omar Abou Khaled, Jean-Pierre Bresciani, Amandine Dubois
2019, vol. 9, no. 21
We investigated how the presentation and the manipulation of an optical flow while running on a treadmill affect perceived locomotor speed (Experiment 1) and gait parameters (Experiment 2). In Experiment 1, 12 healthy participants were instructed to run at an imposed speed and to focus on their sensorimotor sensations to be able to reproduce this running speed later. After a pause, they had to retrieve the reference locomotor speed by manipulating the treadmill speed while being presented with different optical flow conditions, namely no optical flow or a matching/slower/faster optical flow. In Experiment 2, 20 healthy participants ran at a previously self-selected constant speed while being presented with different optical flow conditions (see Experiment 1). The results did not show any effect of the presence and manipulation of the optical flow either on perceived locomotor speed or on the biomechanics of treadmill running. Specifically, the ability to retrieve the reference locomotor speed was similar for all optical flow conditions. Manipulating the speed of the optical flow did not affect the spatiotemporal gait parameters and also failed to affect the treadmill running accommodation process. Nevertheless, the virtual reality conditions affected the heart rate of the participants but without affecting perceived effort.
In virtual reality, visual speed is usually underestimated relative to locomotor speed. Here we investigated how physical activity and fitness affect perceived visual speed when running in a treadmill-mediated virtual environment. Thirty healthy participants (ten sedentary individuals, ten team sport players and ten expert runners) ran on a treadmill at two different speeds (8, 12km/h) in front of a moving virtual scene. Participants were asked to match the speed of the visual scene to their running speed (i.e. treadmill speed), indicating for each trial whether the scene was moving slower or faster than the treadmill. The speed of the visual scene was adjusted according to the participant’s response using a staircase until visual and running speeds were perceived as equivalent. More sedentary participants underestimated visual speed relative to their actual running speed. Specifically, visual speed had to exceed running speed to be perceived as equivalent. The underestimation of visual speed was speed-dependent, and it was significantly larger for sedentary participants than for team sports players and expert runners. The volume of physical activity per week was found to be the best predictor of visual speed perception for both running speeds, while the perceived effort constituted a good predictor only at 8km/h. Physical fitness, on the other hand turned out to be a poor predictor of visual speed perception. Therefore, in order to enhance users’ engagement and their adherence to physical activity programs, the development of “personalized” treadmill-mediated virtual environments should take into account users’ personal characteristics to provide the most natural and engaging feedback possible.
Leonardo Angelini, Elena Mugellini, Omar Abou Khaled, Christina Röcke, Sabrina Guye, Simone Porcelli, Alfonso Mastropietro, Giovanna Rizzo, Noemi Boqué, Paula Subias, Silvia Orte, Giuseppe Andreoni
ICPS Proceedings, PETRA'19 : Proceedings of the 12th ACM International Conference on Pervasive Technologies Related to Assistive Environments, 5-7 June 2019, Rhodes, Greece,
This paper describes the NESTORE e-coaching strategy and system architecture and its unique approach to support older adults to achieve a healthier lifestyle. The novelty of the NESTORE project is the definition of a multi-domain personalized pathway where the e-coach accompany the user throughout different structured and non-structured coaching activities and recommendations. The NESTORE e-Coach is the result of a highly multidisciplinary EU project, granted under the call SC1-PM-15-2017.
Capallera Marine, Meteier Quentin, De Salis Emmanuel, Carrino Stefano, Angelini Leonardo, Abou Khaled Omar, Mugellini Elena
AutomotiveUI '19: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 2019
In the context of highly automated driving, the driver has to be aware of driving risks and to take over control of the car in hazardous situations. The goal of this paper is to categorize and analyze the factors that lead to such critical scenarios. To this purpose, we analyzed limitations of Advanced Driver-Assistance Systems (ADAS) extracted from owner manuals of 12 partially automated cars available on the market. A taxonomy with 6 macro-categories and 26 micro-categories is proposed to classify and better understand the limitations of these vehicles. We also investigated if these limitations are conveyed to the driver through Human-Machine Interaction (HMI) in the car. Some suggestions are made to better communicate these limitations to the driver in order to raise his/her situation awareness.
Meteier Quentin, Capallera Marine, Angelini Leonardo, Mugellini Elena, Abou Khaled Omar, Carrino Stefano, De Salis Emmanuel, Stéphane Galland, Susanne Boll
AutomotiveUI '19: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings, 2019
With the increasing use of automation, users tend to delegate more tasks to the machines. Such complex systems are usually developed with "black box" Artificial Intelligence (AI), which makes these systems difficult to understand for the user. This assumption is particularly true in the field of automated driving since the level of automation is constantly increasing via the use of state-of-the-art AI solutions. We believe it is important to investigate the field of Explainable AI (XAI) in the context of automated driving since interpretability and transparency are key factors for increasing trust and security. In this workshop, we aim at gathering researchers and industry practitioners from different fields to brainstorm about XAI with a special focus on human-vehicle interaction. Questions like "what kind of explanation do we need", "which is the best trade-off between performance and explainability" and "how granular should the explanations be" will be addressed in this workshop.
Maurizio Caon, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini
Rivista italiana di ergonomia,
2018, no. 16, pp. 9-23
Maurizio Caon, Leonardo Angelini, Katharina Ledermann, Chantal Martin-Sölch, Omar Abou Khaled, Elena Mugellini
Dans Bagnara, Sebastiano, Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) : volume VII: ergonomics in design, design for all, activity theories for work analysis and design, affective design
(Pp. 1372-1381). 2018,
Cham : Springer
Pain assessment is an essential first step in planning for and providing pain management. Access to effective pain management programs is often limited, due to scarcity of services. Other barriers to treatment include physical symptoms that limit mobility, distance from a clinic, transportation requirements and cost constraints. In response to these barriers to service delivery, the demand for online health resources is growing. However, current solutions present a number of shortcomings, in particular when referring to usability and accessibility. This paper presents the vision of the My Pain Coach system and the first prototype generated as the result of the first iteration of the development process. This prototype is based on a smartphone app and presents two different interfaces: a force-sensitive touchscreen, and a tangible interface based on a textile mat. A preliminary usability evaluation has been conducted and the results show that these interfaces are perceived as excellent from a usability point of view. Nevertheless, further development and testing are still required for the tangible interface.
Dans Bagnara, Sebastiano, Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) : volume VII: ergonomics in design, design for all, activity theories for work analysis and design, affective design
(Pp. 429-439). 2018,
Cham : Springer
There are growing numbers of apps and smartphone-mounts for professional cyclists, since they are crucial to track performances during training. However, these solutions require the athlete to take her hand off the handlebar to interact with it. This represents a major safety issue for the cyclists since it requires leaving the brake control, shifting the attention and, possibly, compromising posture. This paper reports the findings of a user elicitation study conducted with seven professional and semi-professional cyclists in order to design gestures that can be performed while maintaining the hands in the correct position on the handlebar. Results report the frequency of fingers used for these gestures, with the index being the favorite. Furthermore, it provides a classification of gestures in three categories: press, extension and swipe. The most convenient gestures were the thumb and index press, followed by the extension of different combinations of fingers.
Alessandra Rinaldi, Maurizio Caon, Omar Abou Khaled, Elena Mugellini
Dans Bagnara, Sebastiano, Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) : volume VII: ergonomics in design, design for all, activity theories for work analysis and design, affective design
(Pp. 461-470). 2018,
Cham : Springer
European cities are changing due the immigration of people from different cultures. There are many issues related to the integration and dialogue between cultures. Urban design plays a key role in how migrants participate in their host community and it is an important driver for the inclusion process. Facilitating the participation of residents in designing public spaces and their use helps to create a better sense of belonging. Promoting in public spaces the interaction of different cultures becomes a crucial element to facilitate social cohesion and living together. The research project explores an innovative approach in the use of public spaces, through the design of smart urban furniture. Based on a survey of the user’s needs, and on co-design activities, the project investigates innovative solutions for facilitating migrants’ integration and the dialogue between different cultures, through the design of innovative urban furniture, with smart technologies embodied inside. The project, based on the co-design approach of rapid prototyping, creates different kinds of new interaction among urban space and people, and between users of different social or cultural background. The results presented in this paper, were conducted by the research unit of the University of Florence, in cooperation with the Human Tech Institute and the School of Management of the University of Applied Sciences and Arts Western Switzerland.
João Ventura, Sandy Ingram, Maurizio Caon, Maya Zumstein-Shaha, Omar Abou Khaled, Elena Mugellini
Dans Kurosu, Masaaki, Human-computer interaction : interaction in context : 20th International Conference, HCI International 2018, Las Vegas, NV, USA, July 15–20, 2018, Proceedings, Part II
(Pp. 206-218). 2018,
Cham : Springer
This paper presents a mobile gamified application encouraging positive coping strategies for patients of serious and possibly fatal illnesses. The application concept is based on the analogy between one’s lifetime memories and future bucket lists and a journey in the sea of remembrance, traveling back and forth between past and present positive moments and future wish-lists, whilst being aware that life as water, goes on. This concept was co-designed by a team of UX researchers, engineers, and domain experts applying the principles of Eudaimonic design. The iterative development process brought to the final prototype: a multimedia diary with a gameful interface, which is thoroughly described, along with the relative heuristic and empirical evaluations, in this paper.
Hussein Hazimeh, Elena Mugellini, Omar Abou Khaled, Philippe Cudré-Mauroux
International Journal of Social Network Mining,
2018, vol. 2, no. 4, pp. 333-361
The existence of user profiles belonging to a single user across different social networking sites poses several challenges to the research community. The main technical issue in that context is to detect the same user profiles across several different social networks by leveraging a set of mechanisms that identify the similarity among the user profiles. This problem is commonly referred to as entity matching or identity linkage on social networks. In this review, we describe and compare the 27 most important (to the best of our knowledge) research papers in this area. The main contributions of this article are to provide a systematic and integrated review of papers in this area, to provide comparative points that simplify the understanding of such systems, and finally to discuss future research avenues.
Sajida Chamass, Hussein Hazimeh, Jawad Makki, Elena Mugellini, Omar Abou Khaled
International Journal of Services and Standards,
2018, vol. 12, no. 2, pp. 126-139
Social media platforms (SMP) are new resource for data analytics. Multiple aspects can be studied by using its variety of features. Sentiment analysis (SA) is a rising research topic in SMPs. SA approaches on studying and analysing events are still missing several shortcomings. In this paper, we address the problem of ranking event entities and propose a novel approach for this goal. An entity is a person who presents some task in such event, for e.g., a researcher in a conference. To achieve our target, we employ the lexical approach, in addition to associating features from both Facebook and Twitter platforms. We used Facebook reactions also, that not been used in the state-of-the-art approaches. Our results have shown that by associating both features from Facebook and Twitter and by using reactions, we can successfully rank entities participating in a specific event having high precision.
Julien Esseiva, Maurizio Caon, Elena Mugellini, Omar Abou Khaled, Kamiar Aminian
Dans Ortuño, Francesco, Rojas, Ignacio, Bioinformatics and Biomedical Engineering : 6th International Work-Conference, IWBBIO 2018, Granada, Spain, April 25–27, 2018, Proceedings, Part I
(Pp. 75-84). 2018,
Cham : Springer
Detection of fidgeting activities is a field which has not been much explored as of now. Studies have shown that fidgeting has a beneficial impact on people's healthiness as it burns a significant amount of energy. Being able to detect when someone is fidgeting would allow to study more closely the health impact of fidgeting. The purpose of this work is to propose an algorithm being able to detect feet fidgeting period of subjects while sitting using 3D accelerometers on both shoes. Initial results on data from 5 subjects collected during this work shows an accuracy of 95% for a classification between sitting with fidgeting and sitting without fidgeting.
We investigated how visual and kinaesthetic/efferent information is integrated for speed perception in running. Twelve moderately trained to trained subjects ran on a treadmill at three different speeds (8, 10, 12 km/h) in front of a moving virtual scene. They were asked to match the visual speed of the scene to their running speed–i.e., treadmill’s speed. For each trial, participants indicated whether the scene was moving slower or faster than they were running. Visual speed was adjusted according to their response using a staircase until the Point of Subjective Equality (PSE) was reached, i.e., until visual and running speed were perceived as equivalent. For all three running speeds, participants systematically underestimated the visual speed relative to their actual running speed. Indeed, the speed of the visual scene had to exceed the actual running speed in order to be perceived as equivalent to the treadmill speed. The underestimation of visual speed was speed-dependent, and percentage of underestimation relative to running speed ranged from 15% at 8km/h to 31% at 12km/h. We suggest that this fact should be taken into consideration to improve the design of attractive treadmill-mediated virtual environments enhancing engagement into physical activity for healthier lifestyles and disease prevention and care.
El Kamali Mira, Angelini Leonardo, Caon Maurizio, Giuseppe Andreoni, Abou Khaled Omar, Mugellini Elena
Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, 2018
The ability to engage the user in a conversation and the credibility of the system are two fundamental characteristics of virtual coaches. In this paper, we present the architecture of a conversational e-coach for promoting healthy lifestyles in older age, developed in the context of the NESTORE H2020 EU project. The proposed system allows multiple access points to a conversational agent via different interaction modalities: a tangible companion that embodies the virtual coach will leverage voice and other non-verbal cues in the domestic environment, while a mobile app will integrate a text-based chat for a ubiquitous intervention. In both cases, the conversational agent will deliver personalized interventions based on behavior change models and will promote trust by means of emotionally rich conversations.
Leonardo Angelini, Elena Mugellini, Omar Abou Khaled, Nadine Couture
2018, vol. 5(1), no. 7
In the Internet of Things era, an increasing number of everyday objects are able to offer innovative services to the user. However, most of these devices provide only smartphone or web user interfaces. As a result, the interaction is disconnected from the physical world, decreasing the user experience and increasing the risk of user alienation from the physical world. We argue that tangible interaction can counteract this trend and this article discusses the potential benefits and the still open challenges of tangible interaction applied to the Internet of Things. After an analysis of open challenges for Human-Computer Interaction in IoT, we summarize current trends in tangible interaction and extrapolate eight tangible interaction properties that could be exploited for designing novel interactions with IoT objects. Through a systematic review of tangible interaction applied to IoT, we show what has been already explored in the systems that pioneered the field and the future explorations that still have to be conducted. In order to guide future work in this field, we propose a design card set for supporting the generation of tangible interfaces for IoT objects. The card set has been evaluated during a workshop with 21 people and the results are discussed.
Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini
World Academy of Science, Engineering and Technology ; International Journal of Computer and Information Engineering,
2017, vol. 11, no. 9, pp. 996-1001
In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.
Ouerhani Nabil, Carrino Francesco, Abou Khaled Omar, Mugellini Elena, Ehrensberger Jürgen
Future Internet Journal, 2016
Henning Müller, Sandrine Ding, Bruno Alves, David Godel, Omar Abou Khaled, Francois Mooser, Michael Schumacher
ASTRM actuel (Association Suisse es techniciens en radiologie médicales) - SVMTRA aktuell (Schweizerische Vereinigung der Fachleute für medizinisch technische Radiologie) - ASTRM attualità (Associazione Svizzera dei Tecnici di Radiologia Medica),
Octobre 2014, pp. 18-23
Le projet MediCoordination a permis de contribuer à la stratégie e-Health. L’e-Health est en plein essor en Suisse même si un gros effort devra encore être fourni en termes d’interopérabilité et de standardisation dans la mesure où le dossier patient informatisé est alimenté par des informations provenant d’un nombre considérable de services différents avec des standards tout aussi divers.
Damien Zufferey, Gisler Christophe, Abou Khaled Omar, Hennebert Jean
The 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2012), 2012 , pp.
Damien Perritaz, Christophe Salzmann, Denis Gillet, Olivier Naef, Jacques Bapst, Frédéric Barras, Elena Mugellini, Omar Abou Khaled
Lecture Notes in Computer Science,
2009, vol. 5440, pp. 280-310
Augmented Reality enhances user perception by overlaying real world information with virtual computer-generated information. The aims of the 6th Sense project are to improve real-time interaction between the real environment and the virtual world and to maximize the user experience in mobile Augmented Reality. To achieve these objectives a generic framework constituted of two main layers is proposed. The End-to-End Adaptation Layer adapts in real-time the parameters of the Augmented Reality system to provide the user with the best possible experience despite the varying operating conditions such as the transmission link and user head motion. The Generic Augmented Reality Layer encompasses solutions to the problem of overlaying adequate information in the real scene and manages multimodal interaction with the virtual environment.
Aleksandar Boder, Elena Mugellini, Denis Lalanne, Bruno Dumas, Florian Evequoz, Sandro Gerardi, Anne Le Calve, Rolf Ingold, Omar Abou Khaled
In : LALANNE, Denis, KOHLAS, Jürg (eds). Human machine interaction : research results of the MMI program. Berlin : Springer, 2009. P. 103-132. (Lecture notes in computer science ; 5440). 2009
Marine Capallera, Leonardo Angelini, Alexandre Favre, François Magnin, Omar Abou Khaled, Elena Mugellini
Proceeding sof the 34th international francophone conference on human-computer interaction
Link to the conference
Virtual Reality can provide an immersive training environment in nursing education, in particular to experience situations that cannot be perceived in the reality. Through a user-centered design process with educators and students from a nursing school, we developed a VR application for asepsis training in a blood sampling scenario. The simulation allows to visualize the contamination risks during the procedures. We conducted three tests and continuously improved the application in order to increase the usability and the feeling of immersion. During the tests, we compared two interaction modalities, two visualizations of the hands and different degrees of immersion (teleportation, or mapping a real simulation room, with the possibility to walk and touch physical elements). These experiments allowed us to draw a conclusion on the level of immersion reached by the new virtual reality technologies and on their possible implication in the practical training of students.
Quentin Meteier, Marine Capallera, Emmanuel de Salis, Leonardo Angelini, Stefano Carrino, Omar Abou Khaled, Elena Mugellini, Andreas Sonderegger
In conditionally automated driving, several factors can affect the driver’s situation awareness and ability to take over control. To better understand the influence of some of these factors, 88 participants spent 20 minutes in a conditionally automated driving simulator. They had to react to four obstacles that varied in danger and movement. Half of the participants were required to engage in a verbal cognitive non-driving-related task. Situation awareness, takeover performance and physiological responses were measured for each situation. The results suggest that obstacle movement influences obstacle danger perception, situation awareness, and response time, while the latter is also influenced by obstacle danger. The cognitive verbal task also had an effect on the takeover response time. These results imply that the driver’s cognitive state and the driving situation (e.g. the movement/danger of entities present around the vehicle) must be considered when conveying information to drivers through in-vehicle interfaces.
Piérart Geneviève, Capallera Marine, Cherix Robin, Carrino Francesco, Rossier Amélie, Abou Khaled Omar
Gamification and Serious Games 2022 (GSGS'22), 29.06.2022 - 01.07.2022, Sion
Leonardo Angellini, Massimo Mecella, Hai-Ning Liang, Danilo Bernardini, Omar Abou Khaled, Elena Mugellini, Maurizio Caon
Proceedings of the 13th Augmented Human International Conference
Several big tech companies are currently eager of building the metaverse, mainly through virtual reality experiences. Albeit immersive, in shared virtual environments it might be difficult to have emotionally rich interactions. Indeed, current available headsets and VR applications have limited possibilities for tracking and sharing emotions. We believe that physiological signal technology could enhance future metaverse applications. In this context, this paper presents a framework for visualizing, recording and synchronizing experiences in VR with human body signals. In order to prove the effectiveness of the system, we illustrate a use case and the development of a proof-of-concept scenario. Finally, we present the results of the tests conducted on this proof-of-concept that demonstrate the validity of the proposed system. Such framework could be used to design new emotionally augmented experiences in VR.
Emmanuel de Salis, Quentin Meteier, Colin Pelletier, Marine Capallera, Leonardo Angelini, Andreas Sonderegger, Omar Abou Khaled, Elena Mugellini, Marino Widmer, Stefano Carrino
International Conference on Human Interaction and Emerging Technologies ; Proceedings of IHIET 2021: Human Interaction, Emerging Technologies and Future Systems V, 28-30 October 2021, Reims, France
Conditionally automated cars share the driving task with the driver. When the control switches from one to another, accidents can occur, especially when the car emits a takeover request (TOR) to warn the driver that they must take the control back immediately. The driver’s physiological state prior to the TOR may impact takeover performance and as such was extensively studied experimentally. However, little was done about using Machine Learning (ML) to cluster natural states of the driver. In this study, four unsupervised ML algorithms were trained and optimized using a dataset collected in a driving simulator. Their performances for generating clusters of physiological states prior to takeover were compared. Some algorithms provide interesting insights regarding the number of clusters, but most of the results were not statistically significant. As such, we advise researchers to focus on supervised ML using ground truth labels after experimental manipulation of drivers’ states.
Leonardo Angelini, Maurizio Caon, Emmanuel Michielan, Omar Abou Khaled, Elena Mugellini
Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021)
As the European population is getting older, there is an increasing need in maintaining older adults living independently at home. Vocal assistants may offer various services that can be beneficial for senior citizens. In the context of the Silver&Home living lab, we tested the Google Home Smart speaker connected to smart lighting installation with 7 people to understand the strengths, weaknesses and possible usage for improving the quality of life of older adults. The test and the questions asked to participants were framed according to the Unified Theory on Acceptance and Use of Technology (UTAUT2). Participants generally appreciated the interaction with the smart speaker, although they also identified some barriers, such as the “OK Google” wakeword or the assistant speaking too fast for some answers. Finally, they considered it particularly adapted to people living alone.
Mira El Kamali, Leonardo Angelini, Maurizio Caon, Francesco Carrino, Carlo Emilio Standoli, Paolo Perego, Giuseppe Andreoni, Filippo Palumbo, Alfonso Mastropietro, Omar Abou Khaled, Elena Mugellini
The current research proposes a technological system "NESTORE" designed for and with older adults in four different countries in order to improve and sustain their wellbeing. The system personalized activities and architecture, co-designed interfaces, and its multilingual aspect aim to establish an ‘inclusion’ criterion based on the user’s sociocultural profile and health condition.
Francesco Carrino, Omar Abou Khaled, Elena Mugellini, Maurizio Caon
The blockchain technology offers reliability, decentralization, security and credibility. Blockchain solutions can be based on smart contracts and on the use of utility tokens which may represent a utility of a company like limited fashion items, cars, car parts or even human biological samples stored in biobanks. However, decentralization comes with responsibilities: people must take care of storing those tokens in a safe place (commonly denominated as “wallets”) knowing that losing a wallet or wallet key means losing the owned tokens. This concept is still new to people and might sound scary. The success of such services relies on the extent of customers intending to adopt them and very few studies target this intention.
The current research proposes a model combining of the unified theory of acceptance and usage of technology (UTAUT2) with the initial trust model (ITM) and the perceived risk construct in order to evaluate the factors affecting the behaviour and use intention of people towards a blockchain technology that enables access to biobank services. An online questionnaire was built and sent to swiss university students. The 72 results showed that simplifying the access to blockchain-based technologies will facilitate inclusion, enabling people with lower digital literacy to access these technologies.
Chiara Lucifora, Leonardo Angelini, Quentin Meteier, Carmelo M. Vicario, Omar Abou Khaled, Elena Mugellini, Giorgio M. Grasso
Advances in Intelligent Systems and Computing ; Proceedings of International Conference on Intelligent Human Systems Integration IHSI 2021: Intelligent Human Systems Integration 2021, 22-24 February 2021, Palermo, Italy
Cyber Therapy is a research project based on the relationship between Computer Science and Psychology. We are working on post-traumatic stress disorder (PTSD) due to severe traffic accidents using a virtual reality driving simulator and ECG, EDA and breathing sensors. With the help of virtual reality (VR) our goal is to build one software that can process the user’s biofeedback signals - heart rate, body temperature, state of tension, etc. - in real time, to make the phobic stimulus autonomous. To this purpose, we developed a platform capable of adapting the phobic stimulus based on the user’s biofeedback signals. We believe that this human-computer integrated system could be useful to patients as it would allow them to face fear autonomously, and to the psychotherapist, as it would allow a real time - physiologically based - knowledge of fear symptoms severity able to promote a timely and more appropriate program of intervention.
Axel Collet, Valérie Duay, Stéphane Bourquin, Stéphane Gobron, Omar Abou Khaled
Proceedings of GSGS'20 : 5th Gamification & Serious Game Symposium, September-November 2020, Switzerland
A traditional paper guide for industrial maintenance tasks has been transformed into a digital one composed of three augmented reality supports: augmented reality glasses, spatial projection, and video stream superimposition. For the last two, the recording is done by a 6 degree of freedom (trasnlation and rotations) tracking algorithms by deep learning on synthetically generated data. Tests in an industrial environment showed very good results and also that each support has its own advantages depending on the to-do task.
Quentin Meteier, Marine Capallera, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini, Jean-Pierre Bresciani, Andreas Sonderegger, Stefano Carrino
Simulations play a crucial role to investigate hazardous situations that are impossible to test in real-life conditions without endangering the user’s safety. This paper presents a simulator of conditionally automated cars aiming at enhancing the driver safety and driving comfort. In addition, thanks to the simulator’s highly repeatability, integrated sensors and controlled conditions we collected valuable scientific data, which is otherwise very difficult to gather.
Marine Capallera, Omar Abou Khaled, Leonardo Angelini, Elena Mugellini
Proceedings of ETIS 2020 : the Fourth European Tangible Interaction Studio, 16-20 November 2020, Siena, Italy
Developments in the field of semi-autonomous driving will increasingly free the driver from the main driving task. Conditional autonomous driving allows the driver not to constantly monitor her/his environment, but s/he must still be able to regain control of the vehicle at any time if the situation requires it. That’s why it is important to maintain driver’s Situation Awareness while is performing a secondary task. This paper presents a model of an adaptive, full-body and multimodal Human Vehicle Interaction (HVI) for supervision.
Mira El Kamali, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini
Proceedings of ETIS 2020 : Fourth European Tangible Interaction Studio 2020, 16-20 November 2020, Siena, Italy
Older adults are increasing in Europe . Technology may play a role in older adults' health. Giving technology the ability to be physically manipulated can result in creating trust . According to Spreicer , co-designing tangible user interface with elderly people can increase the chance of technology acceptance. NESTORE  is a virtual coach that comes in different forms of modalities/interfaces: a chatbot, a mobile application and a tangible coach. This article focuses on presenting one of the interfaces of NESTORE: the “tangible coach”. The tangible coach is an embodied conversational agent that seeks to empower older adults in becoming the co-producers of their wellbeing lifestyle through its tangible and its vocal interaction.
Francesco Carrino, Quentin Vaucher, Richard Pasquier, Vincent Bourquin, Omar Abou Khaled, Elena Mugellini, Stéphane Gobron
The environmental and societal cost of traditional logistics, based on the "Hub and spoke" model, is increasingly unfavorable. Digitization allows new approaches that have proved effective in people transportation (e.g., Uber, BlaBlaCar). This project proposes the creation of a smart distribution network for the goods transport by exploiting existing transport capabilities. We present the gamification design of the user interface (UI) to foster users’ motivation and trust to the platform.
Mira El Kamali, Leonardo Angelini, Denis Lalanne, Omar Abou Khaled, Elena Mugellini
Proceedings of ICMI '20 Companion : International Conference on Multimodal Interaction, 25-29 October 2020, Virtual event, Netherlands
Anthony Gillioz, Jacky Casas, Elena Mugellini, Omar Abou Khaled
Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, 6-9 September 2020, Sofia, Bulgaria ; Annals of Computer Sciences and Information Sciences
In 2017, Vaswani et al. proposed a new neural network architecture named Transformer. That modern architecture quickly revolutionized the natural language processing world. Models like GPT and BERT relying on this Transformer architecture have fully outperformed the previous state-of-the-art networks. It surpassed the earlier approaches by such a wide margin that all the recent cutting edge models seem to rely on these Transformer-based architectures. In this paper, we provide an overview and explanations of the latest models. We cover the auto-regressive models such as GPT, GPT-2 and XLNET, as well as the auto-encoder architecture such as BERT and a lot of post-BERT models like RoBERTa, ALBERT, ERNIE 1.0/2.0.
Publié dans les actes de la conférence WACAI 2020, Workshop sur les affects, compagnons artificiels et interactions, 2-4 juin 2021, Île d'Oléron
Dans le cadre du projet Européen NESTORE, nous envisageons de créer un coach virtuel pour le bien-être des seniors. Ce dernier est un agent conversationnel qui peut avoir une conversation utilisant le langage naturel avec l'utilisateur afin de coacher, de se lier d'amitié et d'accompagner les seniors tout au long de leur parcours. Cet agent conversationnel se décline sous différentes formes d'interfaces telles qu’une application de messagerie textuelle ou un assistant vocal intégré. Cet agent conversationnel multimodal cherche à construire une relation empathique avec les utilisateurs basée sur son omniprésence, son attitude de coaching, sa fidélité et enfin sa capacité de comprendre l'émotion de l'utilisateur. Dans cet article, nous présentons la conception de ce coach virtuel, son but, ses rôles, l’architecture du système, ses capacités et ses multiinterfaces.
Karl Daher, Mathias Fuchs, Elena Mugellini, Denis Lalanne, Omar Abou Khaled
Advances in Intelligent Systems and Computing ; Proceedings of Human Interaction, Emerging Technologies and Future Applications II (IHIET 2020), 23-25 April, Lausanne, Switzerland
Daily life problems, can lead to distress, which has a harmful effect on health. Individuals are using machines for longer period. Machines should now have the ability to understand and show empathy which relies on trying to help the other through their emotional situation. In this study, showing empathy is done by reducing the effect of negative stress by using blue light. In the experiment, 17 participants executed a computer-mediated stress-generating test while using an Empatica E4 to extract physiological signals. The test is done without and with additional blue-colored light. The results show that a simple addition of blue colored light has the tendency to reduce mental stress. That can be interpreted as, compared to the normal state, the experiment with no light-induced more stress than the experiment with the blue light in the humans. Which imply that the blue light helped in maintaining a lower level of stress.
Marine Capallera, Quentin Meteier, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini, Marino Widmer, Stefano Carrino
Proceedings of HCII 2020 : 22nd International Conference on Human-Computer Interaction, 19-24 July 2020, Copenhagen, Denmark ; Lecture Notes in Computer Science
In this paper, we propose a model for an AI-Companion for conditionally automated cars, able to maintain awareness of the driver regarding the environment but also to able design take-over requests (TOR) on the fly, with the goal of better support the driver in case of a disengagement.
Our AI-Companion would interact with the driver in two ways: first, it could provide feedback to the driver in order to raise the driver Situation Awareness (SA), prevent them to get out of the supervision loop and so, improve takeover during critical situations by decreasing their cognitive workload. Second, in the case of TOR with a smart choice of modalities for convey the request to the driver. In particular, the AI-Companion can interact with the driver using many modalities, such as visual messages (warning lights, images, text, etc.), auditory signals (sound, speech, etc.) and haptic technologies (vibrations in different parts of the seat: back, headrest, etc.).
The ultimate goal of the proposed approach is to design smart HMIs in semi-autonomous vehicles that are able to understand 1) the user state and fitness to drive, 2) the current external situation (vehicle status and behavior) in order to minimize the automation surprise and maximizing safety and trust, and 3) leverage AI to provide adaptive TOR and useful feedback to the driver.
Mira El Kamali, Leonardo Angelini, Maurizio Caon, Denis Lalanne, Omar Abou Khaled, Elena Mugellini
Human-computer Interaction : human values and quality of life : thematic area, HCI 2020, held as part of the 22nd International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, proceedings, part III
The population of people age 65 or over is increasing especially inEurope . Granting to this target population a longer and healthier life isparamount for the European Community. In the context of the H2020 EUfunded project“NESTORE”, an embodied and ubiquitous e-coach is beingdeveloped seeking to change the lifestyle of seniors in different domains ofwellbeing. NESTORE e-coach is known as a personalized embodied andubiquitous e-coach that plays three essential roles in elderly’s wellbeing: acoach, a friend and a companion. As a coach, NESTORE will give trainings andadvice following a wellbeing path that is proposed by experts in wellbeing. As afriend, this e-coach knows and understands the user. As a companion, this e-coach has the ability to detect the user’s emotion and aims at building empathywith the user based by providing support throughout their daily training.The NESTORE e-coach is based on three different intervention medium: amobile application, a chatbot and an embodied vocal assistant. These interfaceshave different forms, different capabilities and different visions. Users cancommunicate with the NESTORE e-coach through different interfaces exclu-sively, sequentially, concurrently and synergistically. The interaction can beinitiated from the user side to different interfaces and/or from the e-coach side.In this paper, we present the NESTORE’s full vision for building the threeessential roles of this e-coach which are: a coach, a companion and a friend forseniors. Furthermore, we explain the NESTORE system design, architecture,capabilities and how the different interfaces of this E-coach contribute to make amulti-modal system. Finally, we conclude our work with the state of this H2020project.
Matthieu Vallat, Alessandro Silacci, Omar Abou Khaled, Elena Mugellini, Giuseppe Fedele, Maurizio Caon
Advances in physical, social & occupational ergonomics : Proceedings of the AHFE 2020 Virtual Conferences on Physical Ergonomics and Human Factors, Social & Occupational Ergonomics and Cross-Cultural Decision Making, July 16–20, 2020, USA
Interactions with treadmills are based on pressing buttons or through a touchscreen. However, these interactions require the user to touch the frontal dashboard of the treadmill while running. Indeed, for each interaction that the runner does, the user needs to break her/his running form to reach the interface.
Those actions cost also some additional energy to the runner with a possible impact on performance. Current technologies allow finding a better solution for the runner like gesture-based interaction. This paper presents a comparison of different interaction modalities, including gestures, on a treadmill. The goal of this study is to analyze the ergonomics of gestural interfaces while running on a treadmill. In fact, specific tailored gestures are perceived as more natural and easier to perform while doing an activity and can improve significantly the user experience.
Robin Cherix, Francesco Carrino, Geneviève Piérart, Omar Abou Khaled, Elena Mugellini, Dominique Wunderle
Lecture Notes in Computer Science ; Proceedings of HCII 2020, HCI in Mobility, Transport, and Automotive Systems. Driving Behavior, Urban and Smart Mobility, Second International Conference, Held as Part of the 22nd HCI International Conference, 19-24 July 2020, Copenhagen, Denmark
The possibility to move independently outdoor has a huge impact on the quality of life. However, it requires complex skills, difficult to acquire for youth with intellectual disabilities (ID). They need an engaging and varied environment in which they can safely train these skills for all the time they may need. We present an exploratory study that aims to evaluate the usability of virtual reality (immersive headset) as learning tool for youth with ID. We developed a simulator of a pedestrian crossing able to reproduce different environmental conditions (i.e., weather, day-time/night-time, and drivers’ kindness). We tested our simulator with 15 people (9–18 years old) with ID. The tests showed good acceptability and a learning effect was visible after only four consecutive sessions, for a total of sixteen simulated crossings. However, additional studies are required (i) to assess in which measure this effect is imputable to actually learned crossing road skills or to a better control over the tool, (ii) to measure the transfer of the learning from virtual reality to real word conditions.
Karl Daher, Zeno Bardelli, Matteo Badaracco, Elena Mugellini, Denis Lalanne, Omar Abou Khaled
Proceedings of the CODIT 2020 : 7th International Conference on control, decision and information technologies, 29 June - 2 July, 2020, Prague, Czech republic
Humans nowadays are tending to spend too much time in front of their screens. Direct interaction between humans is falling in numbers and people are losing their empathic behaviour. By integrating empathy and emotions in everyday objects researchers can address this problem. In addition we can have a positive effect on our lives, from physical and mental health through tackling many issues, like productivity, time wasting, stress and other problems. In this article, we tackle the productivity problem by presenting the Empathic Flower Companion (EFC) that will be using the expression of emotions to help the human through their working day. It will be monitoring their time and at the same time analysing the websites they will be surfing. The concept proposed will reduce the time wasted on unproductive websites. The results show an increase of 15% in the productivity of the testers, which shows that EFC was effective in reducing the amount of time wasted.
Maurizio Caon, Omar Abou Khaled, Paul Vaucher, Dany Mezher, George Mc Guire
Proceedings of the 2nd International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2020)
The digitalization of humanitarian supply chains allows overcoming one of the greatest difficulties faced by NGOs and governments in managing health equipment in crisis situations: the visibility of stocks and consumption at the end of the chain. This paper presents the design process of the health equipment inventory management system developed to support the humanitarian crisis related to the Syrian refugees in Lebanon. The prototype was tested at the pharmacy of the ICRC Weapon-wounded Trauma and Training Centre in Tripoli, Lebanon, where it was demonstrated to be easy to use and able to facilitate the work related to the management of medicament stocks and orders.
Jacky Casas, Elena Mugellini, Omar Abou Khaled
Proceedings of the 2nd International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2020), 23-25 April 2020, Lausanne, Switzerland ; Advances in Intelligent Systems and Computing
Alert Center is a platform aiming at detecting outbreaks caused by food toxin infections and food intoxications in Switzerland. It does this by analyzing tweets and sending alerts to the Federal Food Safety and Veterinary Office (FSVO) when a risk is detected. The platform is composed of four main parts: a real-time extractor that targets tweets based on a list of curated keywords, three classifiers (one for each main spoken language) that isolate tweets related to food toxin, a system that locates tweets on the Swiss territory and a web-based dashboard to visualize the results. Combining localization algorithms of tweets and users allows the system to locate 75.09% of the tweets, 2.31% of which were located in Switerzland. In addition, a list of Swiss Twitter accounts corresponding to 15% of the total estimated number of Swiss accounts has been created.
Francesco Carrino, Valentin Moullet, Omar Abou Khaled, Elena Mugellini, Christian Maggiori
Advances in Intelligent Systems and Computing ; Proceedings of IHIET 2020 : 2nd International Conference on Human Interaction Emerging Technologies: Future Applications, 23-25 April 2020, Lausanne, Switzerland
The PersonAge VR project has the two-folded goal of using Virtual Reality (VR) and interactive storytelling to divulge the research and knowledge in the field of ageism and, in the process, to raise awareness about ageism in the population. The system we conceived and developed allows experiencing ageism under three different points of view: the victim, the perpetrator, and the witness. We performed preliminary usability tests (formative usability) with 8 participants from the point of view of the victim. The system was found to be easy to use and the participants provided feedback about the emotions felt when playing the role of an elderly person. The participants felt strong anger and surprise. These feelings could be associated with a situation of discrimination.
Maurizio Caon, Marc Demierre, Omar Abou Khaled, Elena Mugellini, Pierre Delaigue
Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020)
This paper presents the R’SENS project, the design for a system leveraging the Internet of Things to connect the dots between the user, her car and her environment through the integration of tools belonging to different domains, such as the connected car, the quantified self and web services. The aim of this study is to test a concept through a prototype to explore the possibility of enhancing the user experience of a connected car through the opportune and ubiquitous display of relevant information not only about the car status and the environment, but also the physical status of the driver. The integration of three different user interfaces (i.e., wearable, smartphone and infotainment system) to be used in different moments played a crucial role in the preliminary evaluation of the perceived usefulness and usability of this proof-of-concept.
Marine Capallera, Leonardo Angelini, Quentin Meteier, Stefano Carrino, Emmanuel de Salis, Omar Abou Khaled, Elena Mugellini
Actes de la 31e conférence francophone sur l'interaction homme-machine (IHM 2019), 10-13 décembre 2019, Grenoble, France
Autonomous vehicles are developing rapidly and will lead to a significant change in the driver’s role: he/she will have to move from the role of actor to the role of supervisor. Indeed, the driver will soon be able to perform a secondary task but he/she must be able to take over control in the event of a critical situation that is not managed by the autonomous system. This implies that the role of new interfaces and interactions within the vehicle is important to take into account. This article describes the design of an application that provides the driver with information about the environment perceived by his/her vehicle in the form of modules. This application is displayed as split screen on a tablet by which a secondary task can be performed. Initial tests were carried out with this application in a driving simulator. They made it possible to test the acceptance of the application and the clarity of the information transmitted. The results generally showed that the participants correctly identified some of the factors limiting the proper functioning of the autonomous pilot while performing a secondary task on a tablet.
Virtual Reality (VR) has three main advantages: allowing safe simulations, experimenting different conditions for the same scenario, and providing the perfect replicability of the scenarios. We present a feasibility study on the use of VR and VR immersive headsets to assist young adults (10-18) with intellectual disabilities in learning new skills. We focused on the scenario of a pedestrian crossing without traffic lights, and we considered several environmental conditions (day/night, weather, kindness of drivers, etc.). Our study is not limited to young people with autism spectrum disorder but takes into account young adults with intellectual disability with an associated disorder. 15 young people participated in the study showing a very good acceptability of immersive headsets and a noticeable learning effect already afer a short training session. However, a longer and more extensive study is needed to evaluate the transfer of learning to reality.
Marine Capallera, Peïo Barbé-Labarthe, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini
Semi-autonomous driving is rapidly evolving and one of its major issues is the reduction of the driver’s
attention to his/her environment. After a brief study of current interactions increasing this situational
awareness, and more particularly haptic interactions, this article proposes the use of vibrations in the seat.
Vibrations, due to their location and variations in frequency and amplitude, make it possible to convey
different information to the driver such as the position of obstacles around his/her vehicle as well as the
state of deterioration of the road markings. The results of initial exploratory tests are promising on the use
of haptic interactions. They make it possible to set up the design and procedure for future experiments.
Filippo Palumbo, Paolo Baronti, Antonino Crivello, Francesco Furfari, Michele Girolami, Fabio Mavilia, Marta Civiello, Enrico Denna, Leonardo Angelini, Mira El Kamali, Omar Abou Khaled, Elena Mugellini, Giancarlo Pace
Proceedings of the 5th Italian Workshop on Artificial Intelligence for Ambient Assisted Living 2019, co-located with 18th International Conference of the Italian Association for Artificial Intelligence, AI*AAL@AI*IA 2019, 22 November 2019, Rende, Italy
Monitoring physiological and behavioural data related to the five domains of well-being (i.e., physical, mental, cognitive, social, and nutritional) is relevant for assessing the profile of people using assistive technologies, in order to provide early detection and adaptive support to his changing individual needs related to ageing. In this paper, we present a system called NESTORE that aims at addressing such a challenge. In particular, we focus on the enabling technology that composes the core set of devices of the so-called environmental monitoring system, namely the NESTORE Bluetooth Low Energy beacons. The presented system performs a range of services including data collection and analysis of short- and long-term trends in social and behavioural parameters. Furthermore, using the same set of devices the system provides insights on the status of the user’s vital space in terms of thermal comfort. We provide an overview of the NESTORE environmental monitoring system and details and evaluation of the software modules built upont the chosen technology: social interaction detection, indoor behavioural index inference, and indoor thermal comfort detection.
Quentin Meteier, Marine Capallera, Leonardo Angelini, Elena Mugellini, Omar Abou Khaled, Stefano Carrino, Emmanuel de Salis, Stéphane Galland, Susanne Boll
Proceedings of the 11th International Conferecne on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI'19, 22-25 September 2019, Utrecht, Netherlands
With the increasing use of automation, users tend to delegate more tasks to the machines. Such complex systems are usually developed with “black box” Artificial Intelligence (AI), which makes these systems difficult to understand for the user. This assumption is particularly true in the field of automated driving since the level of automation is constantly increasing via the use of state-of-the-art AI solutions. We believe it is important to investigate the field of Explainable AI (XAI) in the context of automated driving since interpretability and transparency are key factors for increasing trust and security. In this workshop, we aim at gathering researchers and industry practitioners from different fields to brainstorm about XAI with a special focus on human-vehicle interaction. Questions like “what kind of explanation do we need”, “which is the best trade-off between performance and explainability” and “how granular should the explanations be” will be addressed in this workshop.
Marine Capallera, Emmanuel de Salis, Quentin Meteier, Leonardo Angelini, Stefano Carrino, Omar Abou Khaled, Elena Mugellini
Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI'19, 22-25 September 2019, Utrecht, Netherlands
Autonomous vehicles are developing rapidly and will lead to a significant change in the driver’s role: s/he will have to move from the role of actor to the role of supervisor. Indeed, s/he will soon be able to perform a secondary task but s/he must be able to take over control when a critical situation is not managed by the driving system. The role of new interfaces and interactions within the vehicle is important to take into account. This article describes the design of an application that provides the driver with information about the environment perceived by the vehicle. This application is displayed as split screen on a tablet by which a secondary task can be performed. The results of initial experiment showed that the participants correctly identified all the factors limiting the proper functioning of the driving system while performing a secondary task on the tablet.
Marine Capallera, Quentin Meteier, Emmanuel de Salis, Leonardo Angelini, Stefano Carrino, Omar Abou Khaled, Elena Mugellini
In the context of highly automated driving, the driver has to be aware of driving risks and to take over control of the car in hazardous situations. The goal of this paper is to categorize and analyze the factors that lead to such critical scenarios. To this purpose, we analyzed limitations of Advanced DriverAssistance Systems (ADAS) extracted from owner manuals of 12 partially automated cars available on the market. A taxonomy with 6 macro-categories and 26 micro-categories is proposed to classify and better understand the limitations of these vehicles. We also investigated if these limitations are conveyed to the driver through Human-Machine Interaction (HMI) in the car. Some suggestions are made to better communicate these limitations to the driver in order to raise his/her situation awareness.
Conditionally automated driving is rapidly evolving and one of its major issues is the reduction of the driver’s attention to her/his environment. After a brief study of interactions increasing situation awareness, and more specifically haptic interactions, this paper proposes the use of vibrations in the seat. Vibrations, with the variation of their location, frequency and amplitude, allow to transmit to the driver various information such as the position of obstacles around her/his vehicle and the state of deterioration of track markings. The results of a first exploratory test are promising on the use of haptic interactions and they pave the way for future experiments.
Alessandro Silacci, Omar Abou Khaled, Elena Mugellini, Maurizio Caon
Proceedings of 3rd International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2019), 16-18 September 2019, Munich, Germany
Athletes seek to constantly improve their performances pushing their limits and overwork is often the direct consequence of this behavior. This is not a common problem for professionals, who usually are followed by a coach, but it is a growing phenomenon in amateur sports, which drives people to get injured because of overtraining or incorrect movements. Meantime, advances in artificial intelligence enabled the creation of new tools increasingly capable of understanding the complexity of our world. We therefore propose a novel e-coaching system for road cycling athletes, able to automatically follow and tailor their training plans. This paper describes the design of the machine learning algorithm, its model based on reinforcement learning and the metrics that were adopted for the scoring system. Finally, we report our tests, which show that the virtual coach already can compete with human experts in making a proper personalized training plan.
Simon Ruffieux, Elena Mugellini, Omar Abou Khaled
Proceedings of 6th Swiss Conference on Data Science – SDS|2019, 14 June 2019, Bern, Switzerland
This article presents a framework to facilitate and optimize the management of field operations for bike-sharing companies. The study focuses on two modules based on artificial intelligence: the prediction module forecasts bikes availability at station-level using machine-learning and the rebalancing module provides optimal rebalancing operations and routes using constraint programming. The evaluation on 9 months of data collected from a real bike-sharing network notably highlighted the superior forecasting accuracy of the Multilayer Perceptron algorithm.
Francesco Carrino, Ales Janka, Omar Abou Khaled, Elena Mugellini
LoRa technology allows long-range transmissions with low power consumption and it can also be used indoor. For these reasons, the introduction of a precise timestamping of LoRa frames provides the possibility to use this technology for accurate localization in many scenarios. However, this is still very challenging to achieve in non-line-of-sight environments such as urban landscapes. In this paper, we present a “fingerprinting” method to perform outdoor geolocation based on machine learning (Random Forest and Neural Networks) applied to a reference map. The map combines Time Difference Of Arrival (TDOA) measurements generated by a LoRa network and GPS location as ground truth. We tested our approach on simulated data achieving promising results with a Root Mean Squared Error below 9 meters by using a Long Short-Term Memory (LSTM) network.
Timo Spring, Jacky Casas, Karl Daher, Elena Mugellini, Omar Abou Khaled
Proceedings of 4th Swiss Text Analytics Conference (SwissText 2019), 18-19 June 2019, Wintherthur, Switzerland
Recent years show an increasing popularity of chatbots, with latest efforts aiming to make them more empathic and humanlike, finding application for example in customer service or in treating mental illnesses. Thereby, emphatic chatbots can understand the user’s emotional state and respond to it on an appropriate emotional level. This survey provides an overview of existing approaches used for emotion detection and empathic response generation. These approaches raise at least one of the following profound challenges: the lack of quality training data, balancing emotion and content level information, considering the full end-to-end experience and modelling emotions throughout conversations. Furthermore, only few approaches actually cover response generation. We state that these approaches are not yet empathic in that they either mirror the user’s emotional state or leave it up to the user to decide the emotion category of the response. Empathic response generation should select appropriate emotional responses more dynamically and express them accordingly, for example using emojis.
Lucien Aymon, Jean Decaix, Francesco Carrino, Pierre-André Mudry, Elena Mugellini, Omar Abou Khaled, Richard Baltensperger
Proceedings of 2019 6th Swiss Conference on Data Science (SDS), 14 June 2019, Bern, Switzerland
Water is a scarce resource which is becoming increasingly inaccessible. It is therefore necessary, in most parts of the world, to capture, transport and allocate it efficiently and thoughtfully. The implementation of monitored water distribution networks is often expensive. The purpose of this project is therefore to monitor leakage and consumption in a non-pressurized agricultural irrigation system using only inexpensive and easily installed pressure sensors. We modeled the water network to automatically simulate a leak randomly through the network. These simulated pressures serve as a dataset to train, test and validate a Random Forest algorithm that detects the leaks. Through pressure measures, the model can locate the junction closest to the leak with an accuracy of 96.24%. This approach therefore allows leaks detection in a water distribution system without the use of expensive flow sensors.
Paula Subias-Beltran, Silvia Orte, Eloisa Vargiu, Filippo Palumbo, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini, Maurizio Caon
Proceedings of the 32nd IEEE CBMS International Symposium on Computer-Based Medical Systems
This paper presents the decision support system that has been defined and developed under the umbrella of the NESTORE project. The main goal of the proposed system is to help users in selecting coaching plans by proposing personalised recommendations based on their behaviours and preferences. Recognising such behaviours and their evolution over time is therefore a crucial element for tailoring the interaction of the system with the user. A three-layer system composed of pathways, coaching activity plans, and coaching events, constitutes the so-called coaching timeline on which the analysis is grounded. Various techniques are used to model and personalise the recommendations and feedback. Firstly, the indicators are extracted from disparate data sources, then these are modelled through a profiling system and, finally, recommendations on the pathways and coaching plans are performed through a scoring and a tagging system.
Alessandro Silacci, Julien Tscherrig, Elena Mugellini, Omar Abou Khaled
Proceedings of the 13th International Conference on Digital Society and eGovernments ICDS 2019, 24-28 February 2019, Athens, Greece
This study presents a solution to enhance the cities’ traffic control by classifying particular vehicles’ behaviors. A Support Vector Machine (SVM) approach is presented, enabling the system to classify cars that are looking to park and those that are simply transiting through a city. Through this paper, we also propose a new way of managing the high density of traffic data using a grid. The results show that the system is able to distinguish the two different behaviors with an accuracy averaging 80%.
Hussein Hazimeh, Mohammad Harissa, Elena Mugellini, Omar Abou Khaled
Proceedings of ACM 8th International Conference on Software and Computer Applications (ICSCA 2019), 19-21 February 2019, Penang, Malaysia
Online Social Networks (OSNs) are emergent resources for largescale multi-purpose data analytics. Sentiment analysis (SA) is a trending research area on OSNs. SA approaches for studying and analyzing events are still missing several shortcomings. Unlike other approaches that analyzed micro-scaled events such as "marriage", "graduation", we analyzed the sentiment of large-scale social events such as "festivals". In this paper, we address the problem of finding the sentiment of large-scale social events and introduce a novel method for this goal. To address this problem, we utilize a lexical approach. The features used in our method are universal and composed of auxiliary and essential features from OSNs. Auxiliary features are non-textual features used to emphasize the sentiment polarity. Moreover, we track the temporal interchanges of audience sentiment on OSNs.We finally empirically validate that our method can outperform with high precision and recall values.
Hussein Hazimeh, Elena Mugellini, Omar Abou Khaled
In this paper, we introduce heterogeneous methods to analyze and discover user profiles on Online Social Networks (OSNs).We are the first to investigate such methods to profile users on multiple OSNs (Facebook, Twitter, Google+, etc.). In addition, we perform reliable analytics, i.e., users in the datasets are identical. Deeply speaking, if we have a dataset of n number of user profiles on Facebook, we do not analyze n different profiles on corresponding OSN. However, we first perform a user Profile Matching (PM) task from a seed dataset (Facebook for instance) and then match these profiles inside this dataset to their corresponding profiles on other OSNs, then we start our User Profile Analysis and Discovery task (UPAD). We show that our UPAD methods uncover very interesting facts about OSN users.
Hussein Hazimeh, Elena Mugellini, Simon Ruffieux, Omar Abou Khaled, Philippe Cudré-Mauroux
Proceedings of the 9th International Symposium on Information and Communication Technology (SoICT 2018), 6-7 December 2018, Da Nang City, Viet Nam
Recent Knowledge Graphs (KGs) like Wikidata and YAGO are often constructed by incorporating knowledge from semi-structured heterogeneous data resources such as Wikipedia. However, despite their large amount of knowledge, these graphs are still incomplete. In this paper, we posit that Online Social Networks (OSNs) can become prominent data resources comprising abundant knowledge about real-world entities. An entity on an OSN is represented by a profile; the link to this profile is called a social link. In this paper, we propose a KG refinement method for adding missing knowledge to a KG, i.e., social links. We target specific entity types, in the scientific community, such as researchers. Our approach uses both scholarly data resources and existing KG for building knowledge bases. Then, it matches this knowledge with OSNs to detect the corresponding social link(s) for a specific entity. It uses a novel matching algorithm, in combination with supervised and unsupervised learning methods. We empirically validate that our system is able to detect a large number of social links with high confidence.
Proceedings of 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI), 5-7 November 2018, Volos, Greece
This article presents the first step of a project focusing on enhancing the management of bike-sharing systems. The objective of the project is to optimize the daily rebalancing operations that need to be performed by operators of bike-sharing systems using machine-learning algorithms and constraint programming. This study presents an evaluation of machine learning algorithms developed for forecasting the availability of bikes on three Swiss bike-sharing networks. The results demonstrate the superiority of the Multi-Layer Perceptron algorithm for forecasting available bikes at station-level for different prediction horizons and its applicability for real-time prediction generation.
Joël Dumoulin, Olivier Canévet, Michael Villamizar, Hugo Nunes, Omar Abou Khaled, Elena Mugellini, Jean-Marc Odobez, Fabrice Moscheni
Proceedings of the 15th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS 2018), 27-30 November 2018, Auckland, New Zealand
We introduce a new dataset, dubbed UNICITY , for the task of detecting people in security airlocks in top view depth images. If security companies have been relying on computer systems and algorithms for a long time, very few are trusting artificial intelligence and more specifically machine learning approaches in production environments. We are confident that the recent advances in these domains, especially with the democratization of deep learning, will open new horizons for security systems. We release this dataset to encourage the development of such approaches in the scientific community. UNICITY consists of 58k images collected from 65 recorded sequences with one or two people performing different behaviors including attacks and trickeries (e.g. tailgating). It also provides full annotation of people such as the location of head and shoulders. As as result, UNICITY is perfectly suited for training and adapting machine learning algorithms for video surveillance applications. This paper presents the data collection, an evaluation protocol, as well as two baseline methods for attack detection.
Leonardo Angelini, Maurizio Caon, Jacky Casas, Frederica Cena, Amon Rapp, Omar Abou Khaled, Elena Mugellini
Proceedings of ACM International Symposium on Wearble Computers (ISWC'18), Ubicomp 2018, 8-12 October 2018, Singapore
Human-computer interaction is progressively shifting towards natural language communication, determining the rise of conversational agents. In the context of ubiquitous computing, the opportunities for interacting with new services and systems in a conversational manner are increasing and, nowadays, it is common to talk to home assistants to interact with a smart environment or to write to chatbots to access an online service. This workshop aims at bringing together researchers from academia and industry in order to establish a multidisciplinary community interested in discovering and exploring the challenges and opportunities coming from the ubiquity of conversational agents.
This article presents the design of a conversational agent whose goal is to coach people who wish to improve their food lifestyle. The data gathering method is easy and especially fast in order to simplify the life of the user. The goals are defined by the user and the follow-up is done daily. Two choices are available to the user: reduce his consumption of meat or consume more fruits and vegetables. User tests were conducted with 36 people. Only 11% of the challenges were successful, but in 65% of cases, the tester has managed to improve its consumption compared to before.
Mira El Kamali, Leonardo Angelini, Maurizio Caon, Giuseppe Andreoni, Omar Abou Khaled, Elena Mugellini
Karl Daher, Elena Mugellini, Denis Lalanne, Omar Abou Khaled
Proceedings of Fachkonferenz Technik, Architektur und Life Sciences (FTAL) 2018, 18-19 October, Lugano (TI), Switzerland
Hussein Hazimeh, Ahmad Traboulsi, Hassan Noureddine, Elena Mugellini, Omar Abou Khaled
Proceedings of the 10th International Conference on Information Management and Engineering (ICIME 2018), 22-24 September 2018, Salford, United Kingdom
A web feed is a new kind of web services that was created in the past two decades to keep remote users updated with the latest news without having to crawl individual web sites. Currently, the existing web feed services get their information from one source (the website hosting the feed) in a standardized format that is normally structured as follows: title, description, link, image and date. In this paper, we propose a new method called NERVES (social Networks sERVing wEb feedS) that connects web feeds to a Social Networking Sites (SNS), and aims at (1) keeping users aware of the wider context taking into account both the source of the feed and the SNS. (2) Our approach enriches existing feeds with extra information harvested from the social web. We validated the efficiency and accuracy of our approach on public data and report on empirical results yielding an accuracy of 94%.
Maurizio Caon, Stefano Carrion, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini, Filip Velickovski, Giuseppe Andreoni
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'18)
In contemporary society, non-communicable diseases linked to unhealthy lifestyles, such as obesity, are on the rise with a major impact on global deaths. Prevention is the new frontier, promising to increase life expectancy and quality, while reducing costs related to healthcare. The PEGASO project developed a mobile ecosystem where the digital Companion aims at empowering teenagers in the adoption of healthy lifestyles. The pilot study conducted in three European countries (Spain, UK and Italy) shows a good acceptance of the system and that teenagers are keen to use mobile technology to improve their lifestyle, although wearable devices did not engage the young users
Francesco Carrino, Omar Abou Khaled, Elena Mugellini
Lecture Notes in Computer Science, Proceedings of the International Conference on Aumented Reality, Virtual Reality and Computer Graphics (AVR 2018), 24-27 June 2018, Ottranto, Italy
We present an overview of IMPACT, a system that uses virtual and augmented reality to enhance the mirror therapy for the treatment of phantom limb pain and stroke rehabilitation. The system tracks users’ movements and the head position using a combination of depth cameras and inertial sensors. This information is then fused together in a 3D full-body human model able to adapt to the patient’s characteristics (e.g., skin color, limb size) and avoid unnatural movements due to possible bad tracking (e.g., a joint bended in an unnatural way). IMPACT includes three serious games that can be played in first-person point of view and that allow different levels of immersion according to the needs of the treatment.
Francesco Carrino, Charlotte Junod, Omar Abou Khaled, Elena Mugellini
Proceedings of GSGS'18: 3rd Gamification Serious Game Symposium, 5-6 July 2018, Neuchâtel, Switzerland
Maurizio Caon, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini, Assunta Matassa
Proceedings of Designing Interactive Systems (DIS), 9-13 June 2018, Hong Kong, China
Current digital system interfaces are mainly based on vision and hearing. HCI practitioners and researchers need to introduce unconventional senses in interaction design in order to avoid sensory deprivation in digital life and enhance information accessibility. In this paper, we present a novel technique, called Multisensory Storming, which aims at supporting the multisensory interaction design process. Multisensory Storming is a group method enabling the generation of new ideas and design proposals in physical contexts through exercises that allow exploring all the human senses.
Leonardo Angelini, Zuzanna Lechelt, Eva Hornecker, Paul Marshall, Can Liu, Margot Brereton, Alessandro Soro, Nadine Couture, Omar Abou Khaled, Elena Mugellini
Proceedings of CHI 2018, 21-26 April 2018, Montréal, Canada
The rise of the Internet of Things (IoT) brings abundant new opportunities to create more effective and pleasing tangible user interfaces that capitalize on intuitive interaction in the physical world, whilst utilizing capabilities of sensed data and Internet connectivity. However, with these new opportunities come new challenges; little is still known how to best design tangible IoT interfaces that simultaneously provide engaging user experiences and foster a sense of understanding about the often-complex functionality of IoT systems. How should we map previous taxonomies and design principles for tangible interaction into the new landscape of IoT systems? This workshop will bring together a community of researchers from the fields of IoT and tangible interaction, in order to explore and discuss how parallels between tangible interaction and the properties of IoT systems can best be capitalised on as HCI research moves increasingly toward the Internet of Tangible Things (IoTT). Through ideation and discussion, the workshop will function as a springboard for the community to begin creating new taxonomies and design considerations for the emerging IoTT
Leonardo Angelini, Elena Mugellini, Omar Abou Khaled, Nadine Couture, Elise van der Hoven, Saskia Bakker
Proceedings of 12th International Conference on Tangible, Embedded and Embodied Interactions (TEI'18), 18-21 March 2018, Stockholm, Sweden
There is an increasing interest in the HCI research community to design richer user interactions with the Internet of Things (IoT). This studio will allow exploring the design of tangible interaction with the IoT, what we call Internet of Tangibles. In particular, we aim at investigating the full interaction-attention continuum, with the purpose of designing IoT tangible interfaces that can switch between peripheral interactions that do not disrupt everyday routines, and focused interactions that support user’s reflections. This investigation will be conducted through hands-on activities where participants will prototype tangible IoT objects, starting by a paper prototyping phase, supported by design cards, and followed by an Arduino prototype phase. The purpose of the studio is also establishing a community of researchers and practitioners, from both academy and industry, interested in the field of tangible interaction with the Internet of Things.
Leonardo Angelini, Elena Mugellini, Nadine Couture, Omar Abou Khaled
Proceedings of the 12th International Conference on Tangible, Embedded, and Embodied Interaction (TEI'18), 18-21 March 2018, Stockholm, Sweden
Current interactions for the Internet of Things are often constrained behind a screen. With the Internet of Tangible Things (IoTT) we aim at promoting the design of richer interactions, embodied in physical IoT objects. To this purpose, we propose a card set for the design of tangible interaction with IoT objects, which contains 8 cards for tangible interaction properties and 8 for IoT properties, in order to explore how tangible properties can be exploited for enhancing the interaction with IoT objects. We tested the card set in a dedicated workshop, observing that participants were able to explore most of the tangible and IoT properties. To complement the IoT card set, a hardware prototyping toolkit with examples for each of the 8 tangible properties is currently under development.
Hussein Hamizeh, Elena Mugellini, Omar Abou Khaled, Philippe Cudré-Mauroux
Proceedings of the PROFILES@ISWC 2017: Sementic web conferene, 22 october 2017, Vienna, Austria
With the large number of users connected to social networks, screenname duplication is a rising problem, which leads to interference when trying to recognize users. A number of algorithms have been proposed to distinguish user profiles on one or multiple social networks. The main task in this context is to have robust features. According to the state-of-the-art approaches, features can be: content and behavioural based features, that compare content similarity between posts or behaviour similarity (timestamps between posts (behavioural), or overlapping between content (content) for example). Attribute-based features that compare profiles attributes, such as gender, age, location or image. In this paper, we tackle this problem and propose SocialMatching++ a novel approach that leverages: (1) user life events such as graduation, marriage or new job, which used to enhance the behavioural approaches (2) profile biographies, which consist in small paragraphs that users write to comprise arbitrary information about themselves. These are used to enhance the attribute approaches. To evaluate our approach, we conducted experiments on 2,263 different profiles from Facebook matched with 5,694 Twitter users, and compared them with two baseline approaches. Our results show that SocialMatching++ achieves better results compared to the baselines approaches, showing that our system successfully bridges the gap between behavioural and attribute based approaches.
Simon Ruffieux, Nicolas Spycher, Elena Mugellini, Omar Abou Khaled
Proceedings of the 2017 Intelligent Systems Conference (IntelliSys), 7-8 september 2017, London, UK
In this paper, we present a system that has been developed to facilitate the collection and use of Bike-Sharing Systems data for research, notably to develop and compare bike usage forecasting algorithms. We collected internal and external data for six different European cities and developed a system providing short and long-term predictions of bikes and slots availabilities for bike-sharing stations in real-time. In order to provide the best predictions, we developed and compared the performances of two types of algorithm; the first one is based on the state-of-the-art Random Forest algorithm and the second one is based on Convolutional Neural Networks. Our study demonstrates their applicability, showing better accuracy for short-term predictions with the Random Forest algorithm and better long-term prediction accuracy with the Convolutional Neural Networks algorithm.
Mariam Abdullah, Hassan Noureddine, Jawad Makki, Hussein Charara, Hussein Hazimeh, Omar Abou Khaled, Elena Mugellini
Proceedings of Computer Science Information Technology (CS IT), CSCP 2017, 25-26 March 2017, Geneva, Switzerland
With the enormous growth of data, retrieving information from the Web became more desirable and even more challenging because of the Big Data issues (e.g. noise, corruption, bad quality...etc.). Expert seeking, defined as returning a ranked list of expert researchers given a topic, has been a real concern in the last 15 years. This kind of task comes in handy when building scientific committees, requiring to identify the scholars’ experience to assign them the most suitable roles in addition to other factors as well. Due to the fact the Web is drowning with plenty of data, this opens up the opportunity to collect different kinds of expertise evidence. In this paper, we propose an expert seeking approach with specifying the most desirable features (i.e. criteria on which researcher’s evaluation is done) along with their estimation techniques. We utilized some machine learning techniques in our system and we aim at verifying the effectiveness of incorporating influential features that go beyond publications.