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Angelini Leonardo

Professeur HES assistant

Compétences principales

Professeur HES assistant

Bureau: HEG 411

Haute école de gestion de Fribourg
Chemin du Musée 4, 1700 Fribourg, CH

Collaborateur scientifique HES

Téléphone: +41 26 429 67 45

Bureau: HEIA_D30.05

Haute école d'ingénierie et d'architecture de Fribourg
Boulevard de Pérolles 80, 1700 Fribourg, CH

Institut
HumanTech - Technology for Human Wellbeing Institute

BSc HES-SO en Informatique - Haute école d'ingénierie et d'architecture de Fribourg

Systèmes d'information
interaction homme machine
machine learning
technologies web

En cours

Silver & Home

Rôle: Requérant(e) principal(e)

Financement: HES-SO, SwissUniversities, Loterie Romande, Canton de Fribourg, Associations et Institutions Fribourgeoises

Description du projet :

Le projet Silver & Home du Gérontopôle Fribourg/Freiburg recherche une meilleure adéquation entre les produits et les services développés par les entreprises et les besoins des seniors cherchant une meilleure qualité de vie à la maison, dans les appartements adaptés ou en EMS.

Silver&Home collabore avec des entreprises qui offrent des gérontechnologies dans leur catalogue de produits ou services, des prestataires dans le domaine du vieillissement, enfin et surtout, des seniors, utilisateurs finaux de ces produits et services. Silver & Home s’intéresse à différents types de gérontechnologies qui peuvent être regroupées autour de 4 catégories principales: la sécurité, les liens sociaux, la prise en soins et la mobilité.

Equipe de recherche au sein de la HES-SO: Angelini Leonardo , Mugellini Elena , Houmard Laurent

Partenaires professionnels: Emmanuel Michielan, Gérontopôle Fribourg / AFIPA; Thierry Müller, Associations Fribourgeoise Aide Soins à domicile; Jean Marc Groppo, Pro Senectute Fribourg

Durée du projet: 01.11.2018 - 31.07.2020

Montant global du projet: 200'000 CHF

Archivage des données: https://www.silverhome.ch/

Statut: En cours

NESTORE COACH (SC1-PM-15-2017 H2020)

Rôle: Co-requérant(s)

Requérant(e)s: Giuseppe Andreoni, Politecnico di Milano

Financement: EU SC1-PM-15-2017 H2020

Description du projet :

NESTORE (Novel Empowering Solutions and Technologies for Older people to Retain Everyday life activities) is a H2020 EU project funded under the SC1-PM15-2017 programme aimed at developing virtual coaches for older adults.

Equipe de recherche au sein de la HES-SO: Angelini Leonardo , Mugellini Elena , Abou Khaled Omar , El Kamali Mira , Crausaz Didier , Carrino Francesco , Caon Maurizio

Partenaires académiques: Giuseppe Andreoni, Politecnico di Milano

Durée du projet: 01.09.2017 - 01.01.2021

Archivage des données: https://nestore-coach.eu/

Publications liées:

Statut: En cours

Terminés

Living in smart environments: Natural and economic gesture-based HCI. A joint PhD research initiative

AGP

Rôle: Collaborateur/trice

Requérant(e)s: FR - EIA - Institut HumanTech, Mugellini Elena, FR - EIA - Institut HumanTech

Financement: FR - Ecole d'ingénieurs de Fribourg; Hasler; SPO

Description du projet : Novel interaction paradigms for home and work environment are still an open-issue. Since its invention in the 60's, the most popular mode of interaction remains the mouse- keyboard artifact, principally because of its accuracy, ergonomic and effortless usage. The aim of this project is to set up a joint PhD research initiative, between University of Applied Sciences of Western Switzerland-Fribourg and University of Fribourg, to develop a novel natural and economic gesture-based HCI for everyday use. This document presents our vision, our motivation and finally outlines the major research issues that will be handled during the project.

Equipe de recherche au sein de la HES-SO: Angelini Leonardo , Tscherrig Julien , Riedo Olivier , Chassot Laurent , Capallera Marine , Mugellini Elena , Ruffieux Simon

Partenaires académiques: FR - EIA - Institut HumanTech; Mugellini Elena, FR - EIA - Institut HumanTech

Durée du projet: 01.09.2010 - 31.12.2020

Montant global du projet: 614'092 CHF

Statut: Terminé

2024

Classification of driver fatigue in conditionally automated driving using physiological signals and machine learning

Article scientifique ArODES

Quentin Meteier, Renée Favre, Sofia Viola, Marine Capallera, Leonardo Angelini, Elena Mugellini, Andreas Sonderegger

Transportation Research Interdisciplinary Perspectives, 26, 101148

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Résumé:

Conditionally automated vehicles (Level 3 SAE) are emerging on the roads, but long periods without engaging in a non-driving-related task can reduce drivers’ vigilance. This study aims to determine whether driver fatigue can be accurately predicted using physiological signals and machine learning (ML) techniques in such a context. 63 young drivers completed two separate conditional automated drives of 30 min each, in either a rural or a urban area. Half of them had been mildly sleep-deprived the previous night (slept less than six hours). Electrocardiogram (ECG), electrodermal activity (EDA), and respiration were collected, along with subjective measures of sleepiness and affective state. Using ML, sleep deprivation, driving environment, and sleepiness could be predicted from physiological features with an accuracy of 99%, 85%, and 73% respectively. Signal segmentation increased model accuracy, and EDA features were the most predictive. The differences between the results obtained from statistical analyses of sleepiness measures and the accuracy achieved by ML models are discussed. The results of this empirical study indicate that even mild sleep deprivation affects the physiological state of drivers, which can have serious consequences when combined with long periods of inactivity. Car manufacturers and researchers should take this into account when designing intelligent systems capable of providing drivers with appropriate warnings before a critical situation arises.

Modality-independent effect of gravity in shaping the internal representation of 3D space for visual and haptic object perception

Article scientifique ArODES

Michele Tagliabue, Theo Morfoisse, Gabriela Herrera Altamira, Leonardo Angelini, Gilles Clément, Mathieu Beraneck, Joseph McIntyre

The Journal of Neuroscience, 44, 13, e2457202023

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Résumé:

Visual and haptic perceptions of 3D shape are plagued by distortions, which are influenced by non-visual factors, such as gravitational vestibular signals. Whether gravity acts directly on the visual or haptic systems or at a higher, modality-independent level of information processing remains unknown. To test these hypotheses, we examined visual and haptic 3D shape perception by asking male and female human subjects to perform a “squaring” task in upright and supine postures and in microgravity. Subjects adjusted one edge of a 3D object to match the length of another in each of the 3 canonical reference planes and we recorded the matching errors to obtain a characterization of the perceived 3D shape. The results show opposing, body-centered patterns of errors for visual and haptic modalities, whose amplitudes are negatively correlated, suggesting that they arise in distinct modality-specific representations that are nevertheless linked at some level. On the other hand, weightlessness significantly modulated both visual and haptic perceptual distortions in the same way, indicating a common, modality-independent origin for gravity's effects. Overall, our findings show a link between modality-specific visual and haptic perceptual distortions and demonstrate a role of gravity-related signals on a modality-independent internal representation of the body and peripersonal 3D space used to interpret incoming sensory inputs. Significance Statement Both visual and haptic 3D-object perception are plagued by anisotropic patterns of errors, as shown in a task of “squaring” the faces of an adjustable cube. We report opposing and negatively correlated perceptive errors for the visual and haptic perceptions, suggesting a strong interaction between the two sensory modalities, even when the task was fundamentally unimodal. In addition, the similar effect of microgravity observed on both visual and haptic perception indicates that gravity acts on a modality-independent representation of 3D space used to process these sensory inputs. These findings foster awareness that even simple, unimodal, egocentric tasks are likely to involve complex, cross-modal signal processing.

2023

Older adults' perspectives on multimodal interaction with a conversational virtual coach

Article scientifique ArODES

Mira El Kamali, Denis Lalanne, Omar Abou Khaled, Elena Mugellini, Leonardo Angelini

Frontiers in Computer Science, 5, 112895

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Résumé:

The use of multiple interfaces may improve the perception of a stronger relationship between a conversational virtual coach and older adults. The purpose of this paper is to show the effect of output combinations [single-interface (chatbot, tangible coach), multi-interface (assignment, redundant-complementary)] of two distinct conversational agent interfaces (chatbot and tangible coach) on the eCoach-user relationship (closeness, commitment, complementarity) and the older adults' feeling of social presence of the eCoach. Our study was conducted with two different study settings: an online web survey and a face to face experiment. Our online study with 59 seniors shows that the output modes in multi-interface redundant-complementary manner significantly improves the eCoach-user relationship and social presence of the eCoach compared to only using single-interfaces outputs. Whereas in our face to face experiment with 15 seniors, significant results were found only in terms of higher social presence of multi-interface redundant complementary manner compared to chatbot only. We also investigated the effect of each study design on our results, using both quantitative and qualitative methods.

A recommender system for increasing energy efficiency of solar-powered smart homes

Article scientifique ArODES

Quentin Meteier, Mira El Kamali, Leonardo Angelini, Omar Abou Khaled

Sensors, 23, 18, 7974

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Résumé:

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.

A dataset on the physiological state and behavior of drivers in conditionally automated driving

Article scientifique ArODES

Quentin Meteier, Marine Capallera, Emmanuel de Salis, Leonardo Angelini, Stefano Carrino, Marino Widmer, Omar Abou Khaled, Elena Mugellini, Andreas Sonderegger

Data in Brief, 2023, 47, 109027

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Résumé:

This dataset contains data of 346 drivers collected during six experiments conducted in a fixed-base driving simulator. Five studies simulated conditionally automated driving (L3-SAE), and the other one simulated manual driving (L0-SAE). The dataset includes physiological data (electrocardiogram (ECG), electrodermal activity (EDA), and respiration (RESP)), driving and behavioral data (reaction time, steering wheel angle, …), performance data of non-driving-related tasks, and questionnaire responses. Among them, measures from standardized questionnaires were collected, either to control the experimental manipulation of the driver's state, or to measure constructs related to human factors and driving safety (drowsiness, mental workload, affective state, situation awareness, situational trust, user experience). In the provided dataset, some raw data have been processed, notably physiological data from which physiological indicators (or features) have been calculated. The latter can be used as input for machine learning models to predict various states (sleep deprivation, high mental workload, ...) that may be critical for driver safety. Subjective self-reported measures can also be used as ground truth to apply regression techniques. Besides that, statistical analyses can be performed using the dataset, in particular to analyze the situational awareness or the takeover quality of drivers, in different states and different driving scenarios. Overall, this dataset contributes to better understanding and consideration of the driver's state and behavior in conditionally automated driving. In addition, this dataset stimulates and inspires research in the fields of physiological/affective computing and human factors in transportation, and allows companies from the automotive industry to better design adapted human-vehicle interfaces for safe use of automated vehicles on the roads.

Fully immersive virtual reality using 360° videos to manage well-being in older adults :

Article scientifique ArODES

a scoping review

Julie Restout, Iouri Bernache-Assollant, Charles Morizio, Arnaud Boujut, Leonardo Angelini, Achille Tchalla, Anaick Perrochon

Journal of the American Medical Directors Association, 24, 4, 564-572

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Résumé:

Objective: The development of negative behavioral and psychosocial factors (depression, anxiety, apathy, etc) is associated with poor well-being, which can contribute to health issues in ageing, especially in the context of COVID-19. Despite its relative novelty, fully immersive virtual reality (VR) interventions through 360 immersive videos are becoming more accessible and flexible and constitute an emerging method to potentially enhance well-being. The aim of this scoping review is to assess the effectiveness of 360 interventions on well-being in older adults with or without cognitive impairment, as well as cybersickness and attitudes toward this technology. Design: Scoping review. Setting and Participants: Older adults with or without cognitive impairment. Methods: The PRISMA-SR guideline was followed. Four databases were used, and we selected articles published until April 2022. We have analyzed the effect of 360° videos on the well-being of older adults with respect to the study design, the population, the contents, the duration of intervention, and the outcomes. Results: A total of 2262 articles were screened, of which 10 articles were finally included in this review. Most of them are pilot studies and used mixed methods including scales and interviews. The material and content of VR are diversified. Many behavioral and psychological outcomes were assessed, including anxiety, apathy, loneliness, depression, social engagement, quality of life, and emotions. The results were positive or mixed, according to the outcomes. We recorded few adverse events, and the interviews show contrasting results concerning the participants’ feelings (ie, degree of immersion, familiarity with technology, and VR content). Conclusions and Implications: The use of VR 360° videos seems feasible in community-dwelling older adults or residential aged care facilities, as they are safe and provide enjoyment. It constitutes an emerging and promising therapeutic tool to manage psychosocial disorders. This review provides key considerations for the design and implementation of interventions using VR 360° video in clinical practice.

Co-designing an embodied e-coach with older adults :

Article scientifique ArODES

the tangible coach journey

Mira El Kamali, Leonardo Angelini, Maurizio Caon, Nick Dulake, Paul Chamberlain, Claire Craig, Carlo Emilio Standoli, Giuseppe Andreoni, Omar Abou Khaled, Elena Mugellini

International Journal of Human–Computer Interaction, 40, 10, 2736-2759

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Résumé:

This article describes a tangible interface for an e-coach, co-designed in four countries to meet older adults’ needs and expectations. The aim of this device is to coach the user by giving recommendations, personalized tasks and to build empathy through vocal, visual, and physical interaction. Through our co-design process, we collected insights that helped identifying requirements for the physical design, the interaction design and the privacy and data control. In the first phase, we collected users’ needs and expectations through several workshops. Requirements were then trans- formed into three design concepts that were rated and commented by our target users. The final design was implemented and tested in three countries. We discussed the results and the open challenges for the design of physical e-coaches for older adults. To encourage further developments in this field, we released the research outputs of this design process in an open-source repository.

A contextual multimodal system for increasing situation awareness and takeover quality in conditionally automated driving

Article scientifique ArODES

Marine Capallera, Quentin Meteier, Marino Widmer, Leonardo Angelini, Stefano Carrino, Andreas Sonderegger, Omar Abou Khaled, Elena Mugellini

IEEE Access, 2023, vol. 11, pp. 5746-5771

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Résumé:

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.

2022

Human-Vehicle Interaction to Support Driver's Situation Awareness in Automated Vehicles: A Systematic Review

Article scientifique ArODES

Marine Capallera, Leonardo Angelini, Quentin Meteier, Omar Abou Khaled, Elena Mugellini

IEEE Transactions on Intelligent Vehicles, 2023, Vol. 8, n° 3, pp. 2551 - 2567

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Résumé:

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.

Carrying a passenger and relaxation before driving :

Article scientifique ArODES

classification of young drivers’ physiological activation

Quentin Meteier, Marine Capallera, Emmanuel de Salis, Marino Widmer, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini, Andreas Sonderegger

Physiological Reports, 2022, vol. 10, article no. e15229

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Résumé:

Drivers are often held responsible for road crashes. Previous research has shown that stressors such as carrying passengers in the vehicle can be a source of accidents for young drivers. To mitigate this problem, this study investigated whether the presence of a passenger behind the wheel can be predicted using machine learning, based on physiological signals. It also addresses the question whether relaxation before driving can positively influence the driver's state and help controlling the potential negative consequences of stressors. Sixty young participants completed a 10-min driving simulator session, either alone or with a passenger. Before their driving session, participants spent 10 min relaxing or listening to an audiobook. Physiological signals were recorded throughout the experiment. Results show that drivers experience a higher increase in skin conductance when driving with a passenger, which can be predicted with 90%-accuracy by a k-nearest neighbors classifier. This might be a possible explanation for increased risk taking in this age group. Besides, the practice of relaxation can be predicted with 80% accuracy using a neural network. According to the statistical analysis, the potential beneficial effect of relaxation did not carry out on the driver's physiological state while driving, although machine learning techniques revealed that participants who exercised relaxation before driving could be recognized with 70% accuracy. Analysis of physiological characteristics after classification revealed several relevant physiological indicators associated with the presence of a passenger and relaxation.

The NESTORE e-Coach : designing a multi-domain pathway to well-being in older age

Article scientifique ArODES

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

Technologies, 2022, vol. 10, no 2, pp. 50-77

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Résumé:

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.

PEGASO e-Diary: :

Article scientifique ArODES

user engagement and dietary behavior change of a mobile food record for adolescents

Maurizio Caon, Federica Prinelli, Leonardo Angelini, Stefano Carrino, Elena Mugellini, Silvia Orte, José C. E. Serrano, Sarah Atkinson, Anne Martin, Fulvio Adorni

Frontiers in Nutrition, 2022, vol. 9, article 727480

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Résumé:

Background: Obesity amongst children and adolescents is becoming a major health problem globally and mobile food records can play a crucial role in promoting healthy dietary habits. Objective: To describe the methodology for the implementation of the e-Diary mobile food record, to assess its capability in promoting healthy eating habits, to evaluate the factors associated with its usage and engagement. Methods: This is a descriptive study that compared the characteristics of participants engaged in the e-Diary, which was part of the PEGASO project in which an app to provide proactive health promotion was given to 365 students at 4 European sites enrolled during October to December 2016: England (UK), Scotland (UK), Lombardy (Italy), and Catalonia (Spain). The e-Diary tracked the users' dietary habits in terms of food groups, dietary indexes, and 6 dietary target behaviors relating to consumption of: fruit; vegetable; breakfast; sugar-sweetened beverages; fast-food; and snacks. The e-Diary provided also personalized suggestions for the next meal and gamification. Results: The e-Diary was used for 6 months by 357 adolescents (53.8% females). The study showed that females used the e-Diary much more than males (aOR 3.8, 95% CI 1.6–8.8). Participants aged 14 years were more engaged in the e-Diary than older age groups (aOR 5.1, 95% CI 1.4–18.8) as were those with a very good/excellent self-perceived health status compared to their peers with fair/poor health perception (aOR 4.2, 95% CI 1.3–13.3). Compared to the intervention sites, those living in Catalonia (aOR 13.2 95% CI 2.5–68.8) were more engaged. In terms of behavior change, a significant positive correlation between fruit (p < 0.0001) and vegetables (p = 0.0087) intake was observed in association with increased engagement in the e-Diary. Similarly, adolescents who used the app for more than 2 weeks had significantly higher odds of not skipping breakfast over the study period (aOR 2.5, 95% CI 1.0–6.3). Conclusions: The users highly engaged with the e-Diary were associated with improved dietary behaviors: increased consumption of fruit and vegetables and reduced skipping of breakfast. Although the overall usage of the e-Diary was high during the first weeks, it declined thereafter. Future applications should foster user engagement, particularly targeting adolescents at high risk.

Non-intrusive contact respiratory sensor for vehicles

Article scientifique ArODES

Quentin Meteier, Michiel Kindt, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini

Sensors, 2022, vol. 22, no. 3, article no. 880

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Résumé:

In this work, we propose a low-cost solution capable of collecting the driver’s respiratory signal in a robust and non-intrusive way by contact with the chest and abdomen. It consists of a microcontroller and two piezoelectric sensors with their respective 3D printed plastic housings attached to the seat belt. An iterative process was conducted to find the optimal shape of the sensor housing. The location of the sensors can be easily adapted by sliding them along the seat belt. A few participants took part in three test sessions in a driving simulator. They had to perform various activities: resting, deep breathing, manual driving, and a non-driving-related task during automated driving. The subjects’ breathing rates were calculated from raw data collected with a reference chest belt, each sensor alone, and the fusion of the two. Results indicate that respiratory rate could be assessed from a single sensor located on the chest with an average absolute error of 0.92 min−1 across all periods, dropping to 0.13 min−1 during deep breathing. Sensor fusion did not improve system performance. A 4-pole filter with a cutoff frequency of 1 Hz emerged as the best option to minimize the error during the different periods. The results suggest that such a system could be used to assess the driver’s breathing rate while performing various activities in a vehicle.

Relevant physiological indicators for assessing workload in conditionally automated driving, through three-class classification and regression

Article scientifique ArODES

Quentin Meteier, Emmanuel de Salis, Marine Capallera, Marino Widmer, Leonardo Angelini, Omar Abou Khaled, Andreas Sonderegger, Elena Mugellini

Frontiers in Computer Science, 2022, vol. 3, article no. 775282

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Résumé:

In future conditionally automated driving, drivers may be asked to take over control of the car while it is driving autonomously. Performing a non-driving-related task could degrade their takeover performance, which could be detected by continuous assessment of drivers' mental load. In this regard, three physiological signals from 80 subjects were collected during 1 h of conditionally automated driving in a simulator. Participants were asked to perform a non-driving cognitive task (N-back) for 90 s, 15 times during driving. The modality and difficulty of the task were experimentally manipulated. The experiment yielded a dataset of drivers' physiological indicators during the task sequences, which was used to predict drivers' workload. This was done by classifying task difficulty (three classes) and regressing participants' reported level of subjective workload after each task (on a 0–20 scale). Classification of task modality was also studied. For each task, the effect of sensor fusion and task performance were studied. The implemented pipeline consisted of a repeated cross validation approach with grid search applied to three machine learning algorithms. The results showed that three different levels of mental load could be classified with a f1-score of 0.713 using the skin conductance and respiration signals as inputs of a random forest classifier. The best regression model predicted the subjective level of workload with a mean absolute error of 3.195 using the three signals. The accuracy of the model increased with participants' task performance. However, classification of task modality (visual or auditory) was not successful. Some physiological indicators such as estimates of respiratory sinus arrhythmia, respiratory amplitude, and temporal indices of heart rate variability were found to be relevant measures of mental workload. Their use should be preferred for ongoing assessment of driver workload in automated driving.

2021

Conversational agents for health and well-being across the life course :

Article scientifique ArODES

protocol for an evidence map

Mara Pereira Guerreiro, Leonardo Angelini, Helga Rafael Henriques, Mira El Kamali, Cristina Baixinho, João Balsa, Isa Félix Brito, Omar Abou Khaled, Maria Beatriz Carmo, Ana Paula Claudio, Maurizio Caon, Karl Daher, Bruno Alexandre, Mafalda Padinha, Elena Mugellini

JMIR Research Protocols, 2021, vol. 10, no. 9, article no. e26680

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Résumé:

Background: Conversational agents, which we defined as computer programs that are designed to simulate two-way human conversation by using language and are potentially supplemented with nonlanguage modalities, offer promising avenues for health interventions for different populations across the life course. There is a lack of open-access and user-friendly resources for identifying research trends and gaps and pinpointing expertise across international centers. Objective: Our aim is to provide an overview of all relevant evidence on conversational agents for health and well-being across the life course. Specifically, our objectives are to identify, categorize, and synthesize—through visual formats and a searchable database—primary studies and reviews in this research field. Methods: An evidence map was selected as the type of literature review to be conducted, as it optimally corresponded to our aim. We systematically searched 8 databases (MEDLINE; CINAHL; Web of Science; Scopus; the Cochrane, ACM, IEEE, and Joanna Briggs Institute databases; and Google Scholar). We will perform backward citation searching on all included studies. The first stage of a double-stage screening procedure, which was based on abstracts and titles only, was conducted by using predetermined eligibility criteria for primary studies and reviews. An operational screening procedure was developed for streamlined and consistent screening across the team. Double data extraction will be performed with previously piloted data collection forms. We will appraise systematic reviews by using A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2. Primary studies and reviews will be assessed separately in the analysis. Data will be synthesized through descriptive statistics, bivariate statistics, and subgroup analysis (if appropriate) and through high-level maps such as scatter and bubble charts. The development of the searchable database will be informed by the research questions and data extraction forms. Results: As of April 2021, the literature search in the eight databases was concluded, yielding a total of 16,351 records. The first stage of screening, which was based on abstracts and titles only, resulted in the selection of 1282 records of primary studies and 151 records of reviews. These will be subjected to second-stage screening. A glossary with operational definitions for supporting the study selection and data extraction stages was drafted. The anticipated completion date is October 2021. Conclusions: Our wider definition of a conversational agent and the broad scope of our evidence map will explicate trends and gaps in this field of research. Additionally, our evidence map and searchable database of studies will help researchers to avoid fragmented research efforts and wasteful redundancies. Finally, as part of the Harnessing the Power of Conversational e-Coaches for Health and Well-being Through Swiss-Portuguese Collaboration project, our work will also inform the development of an international taxonomy on conversational agents for health and well-being, thereby contributing to terminology standardization and categorization.

Coaching older adults towards a healthier lifestyle: psychological and technological methods

Chapitre de livre ArODES

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

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Résumé:

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.

Building trust and companionship in e-coaching through embodiment

Chapitre de livre ArODES

Mira El Kamali, Leonardo Angelini, Maurizio Caon, Guiseppe Andreoni, Nick Dulake, Paul Chamberlain, Omar Abou Khlaed, Elena Mugellini

Dans Andreoni, Giuseppe, Mambretti, Cinzia, Digital health technology for better aging: a multidisciplinary approach (Pp. 195-204). 2021, Cham : Springer

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Résumé:

E-coaches are promising tools for health interventions, being scalable and relatively low costs compared to human coaches. Nevertheless, they cannot compare to humans when it comes to trust and social companionship. Hence, many researches were held around the importance of tangible user interfaces in building trust and companionship during human-machine interaction. Co-design, in particular, is the act of creating with stakeholders within the design development process to ensure the results meet their needs and are usable. This chapter describes a design process method and the rationale for building an embodiment for a companion and a trustable e-coach. We also shed lights on the co-design process held in the NESTORE project, which was specifically conducted with older adults to build a vocal assistant that supports user’s behavioral change, as well as to increase the social bonding with the NESTORE e-coach.

Nutritional monitoring in older people prevention services

Chapitre de livre ArODES

Bhalaji Nagarajan, Rupali Khatun, Marc Bolaños, Eduardo Aguilar, Leonardo Angelini, Mira El Kamali, Elena Mugellini, Omar Abou Khaled, Noemi Boqué, Lucia Taro, Petia Radeva

Dans Andreoni, Giuseppe, Mambretti, Cinzia, Digital Health Technology for Better Aging : a multidisciplinary approach (pp. 77-102). 2021, Cham : Springer

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Résumé:

Nutritional monitoring is an important aspect of providing a healthy lifestyle and smarter food consumption. Food recognition is a key task in nutrition monitoring applications especially of interest for older people suffering from malnutrition and unhealthy eating. In order to ease the problem of food intake monitoring, recent health apps involve Artificial Intelligence algorithms for food image analysis. Food recognition is a highly challenging task as the dishes could be composed of mixed types, it could have a lower inter-class variance and also the number of dishes to be recognized is quite higher. In this chapter, we present an in-depth analysis and insights into the development of a nutritional monitoring system that would act as a Key Performance Indicator for the older people food intake monitoring. This system is aimed at providing a convenient food logging environment that would assist older people and their relatives as well as geriatrists in monitoring and maintaining the healthy daily dietary nutritional needs.

Understanding older adults’ affect states in daily life for promoting self-reflection about mental wellbeing

Chapitre de livre ArODES

Martin Sykora, Suzanne Elayan, Leonardo Angelini, Christina Röcke, Mira El Kamali, Elena Mugellini, Sabrina Guye

Dans Andreoni, Giuseppe, Mambretti, Cinzia, Digital Health Technology for Better Aging : a multidisciplinary approach (pp. 179-193). 2021, Cham : Springer

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Résumé:

In recent years, due to the rise in availability of unstructured big data and technological affordances, there has been a proverbial “explosion” of research within the field of sentiment analysis and affective computing, facilitating the study of in-situ communicated emotion and its accurate detection at an unprecedented scale. Increasingly the emotional dimension and its key important role is being recognized in e-coaching, with attempts at its integration within such systems. This chapter reviews the predominant extant models for representing affect, as well as emotion related states relevant to older persons’ experiences, including the state-of-art for their automated detection and integration within e-coaching systems. Given the approaches available, we describe how the NESTORE system addresses emotion recognition, self-tracking and subsequent feedback intended to help older adults make sense of their affective experiences across their daily life, as well as the role it can play in holistic e-coaching systems. Finally, from the NESTORE experience, we draw recommendations about how future e-coaching system could be implemented in the future to include the emotional dimension.

Locomotor illusions are generated by perceptual body-environment organization

Article scientifique ArODES

Martin Dobricki, David Weibel, Leonardo Angelini, Elena Mugellini, Fred W. Mast

PLOS ONE, 2021, vol. 16, no. 5, article no. e0251562

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While one is walking, the stimulation by one’s body forms a structure with the stimulation by the environment. This locomotor array of stimulation corresponds to the human-environment relation that one’s body forms with the environment it is moving through. Thus, the perceptual experience of walking may arise from such a locomotor array of stimulation. Humans can also experience walking while they are sitting. In this case, there is no stimulation by one’s walking body. Hence, one can experience walking although a basic component of a locomotor array of stimulation is missing. This may be facilitated by perception organizing the sensory input about one’s body and environment into a perceptual structure that corresponds to a locomotor array of stimulation. We examined whether locomotor illusions are generated by this perceptual formation of a locomotor structure. We exposed sixteen seated individuals to environmental stimuli that elicited either the perceptual formation of a locomotor structure or that of a control structure. The study participants experienced distinct locomotor illusions when they were presented with environmental stimuli that elicited the perceptual formation of a locomotor structure. They did not experience distinct locomotor illusions when the stimuli instead elicited the perceptual formation of the control structure. These findings suggest that locomotor illusions are generated by the perceptual organization of sensory input about one’s body and environment into a locomotor structure. This perceptual body-environment organization elucidates why seated human individuals experience the sensation of walking without any proprioceptive or kinaesthetic stimulation.

Classification of drivers' workload using physiological signals in conditional automation

Article scientifique ArODES

Quentin Meteier, Marine Capallera, Simon Ruffieux, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini, Marino Widmer, Andreas Sonderegger

Frontiers in Psychology, 2021, vol. 12, article no. 596038

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Résumé:

The use of automation in cars is increasing. In future vehicles, drivers will no longer be in charge of the main driving task and may be allowed to perform a secondary task. However, they might be requested to regain control of the car if a hazardous situation occurs (i.e., conditionally automated driving). Performing a secondary task might increase drivers' mental workload and consequently decrease the takeover performance if the workload level exceeds a certain threshold. Knowledge about the driver's mental state might hence be useful for increasing safety in conditionally automated vehicles. Measuring drivers' workload continuously is essential to support the driver and hence limit the number of accidents in takeover situations. This goal can be achieved using machine learning techniques to evaluate and classify the drivers' workload in real-time. To evaluate the usefulness of physiological data as an indicator for workload in conditionally automated driving, three physiological signals from 90 subjects were collected during 25 min of automated driving in a fixed-base simulator. Half of the participants performed a verbal cognitive task to induce mental workload while the other half only had to monitor the environment of the car. Three classifiers, sensor fusion and levels of data segmentation were compared. Results show that the best model was able to successfully classify the condition of the driver with an accuracy of 95%. In some cases, the model benefited from sensors' fusion. Increasing the segmentation level (e.g., size of the time window to compute physiological indicators) increased the performance of the model for windows smaller than 4 min, but decreased for windows larger than 4 min. In conclusion, the study showed that a high level of drivers' mental workload can be accurately detected while driving in conditional automation based on 4-min recordings of respiration and skin conductance.

2020

The effect of instructions and context-related information about limitations of conditionally automated vehicles on situation awareness

Article scientifique ArODES

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, pp. 241-251

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Résumé:

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.

Virtual coaches for older adults’ wellbeing :

Article scientifique ArODES

a systematic review

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

IEEE Access, 2020, vol. 8, pp. 101884-101902

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Résumé:

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.

2019

Codesign of public spaces for intercultural communication, diversity and inclusion

Chapitre de livre ArODES

Alessandra Rinaldi, Leonardo Angelini, Abou Khaled, Elena Mugellini, Maurizio Caon

Dans Di Bucchianico, Giuseppe, Advances in design for inclusion : proceedings of the AHFE 2019 International Conference on design for inclusion and the AHFE 2019 International Conference on human factors for apparel and textile engineering, July 24-28, 2019, Washington D.C., USA (Pp. 186-195). 2019, Cham, Switzerland : Springer

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Résumé:

The consistent phenomenon of immigration from countries with different cultures, that characterized the last decade, has changed the use of public spaces in European cities. The need to develop innovative solutions aimed at improving intercultural inclusion and mutual understanding of all citizens emerges, so that urban spaces become inclusive, safe and sustainable. This research project is focused on two main questions: (1) can design and technology enable the creation of a different way of living the public space to catalyze interpersonal interaction and to promote a shared sense of citizenship? (2) is it possible to support intercultural communication and to facilitate social inclusion through the design of innovative and interactive public spaces equipped with smart urban furniture? This paper presents three Design Orienting Scenarios as results of the research conducted by several experts, professionals and people with different cultural backgrounds during a focus groups and two different workshops where they made converge competences from design, business, engineering and social sciences to find innovative solutions for the social inclusion of migrants in urban areas.

Owner Manuals Review and Taxonomy of ADAS Limitations in Partially Automated Vehicles

Article scientifique

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

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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.

Workshop on explainable AI in automated driving: a user-centered interaction approach

Article scientifique

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

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Résumé:

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.

2018

Utilizzare il design partecipativo per l'innovazione sostenibile

Article scientifique ArODES

Maurizio Caon, Leonardo Angelini, Omar Abou Khaled, Elena Mugellini

Rivista italiana di ergonomia, 2018, no. 16, pp. 9-23

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My pain coach :

Chapitre de livre ArODES

a mobile system with tangible interface for pain assessment

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

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Résumé:

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.

Internet of tangible things (IoTT) :

Article scientifique ArODES

challenges and opportunities for tangible interaction with IoT

Leonardo Angelini, Elena Mugellini, Omar Abou Khaled, Nadine Couture

Informatics, 2018, vol. 5(1), no. 7

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Résumé:

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.

Towards the nestore e-coach: a tangible and embodied conversational agent for older adults

Article scientifique

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

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Résumé:

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.

2017

Bien-être psychologique avec l'âge

Article professionnel ArODES

Leonardo Angelini, Francesco Carrino, Maurizio Caon, Elena Mugellini, Omar Abou Khaled, Nadine Couture

Angewandte GERONTOLOGIE Appliquée, 2017, vol. 2

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Résumé:

La perte progressive de mobilité chez les seniors peut avoir de lourdes conséquences, pas seulement physiques, mais aussi psychiques et cognitives due à un isolement social croissant. La fenêtre interactive est un outil permettant la communication à distance. Elle est issue d’un projet de recherche qui vise à réduire l’isolement social des seniors en utilisant de nouvelles technologies de manière innovante.

2016

Testing the tangible interactive window with older adults

Article scientifique ArODES

Leonardo Angelini, Francesco Carrino, Maurizio Caon, Frédéric Lemaréchal, Nadine Couture, Omar Abou Khaled, Elena Mugellini

GeroPsych, 2016, vol. 29, no. 4, pp. 215-224

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Résumé:

Social relationships are crucial for older adults’ well-being. Past research demonstrated that video-communication technology could reduce social isolation. However, most commercial telecommunication systems have interfaces that are too complex to be operated by older adults without assistance. In this paper, we present a system that exploits the tangible affordances of a physical window to provide a natural interface for an always-on video-communication system. In addition, we present a case study focused on the system accessibility and user acceptance with 8 older adults living in a retirement home. We also describe the preliminary findings based on an observation study and on a semistructured interview. Finally, we discuss the possible improvements and impact this system might have on older adults’ life.

2015

Move, hold and touch :

Article scientifique ArODES

a framework for tangible gesture interactive systems

Leonardo Angelini, Denis Lalanne, Elise van den Hoven, Omar Abou Khaler, Elena Mugellini

Machines, 2015, vol. 3, pp. 173-207

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Résumé:

Technology is spreading in our everyday world, and digital interaction beyond the screen, with real objects, allows taking advantage of our natural manipulative and communicative skills. Tangible gesture interaction takes advantage of these skills by bridging two popular domains in Human-Computer Interaction, tangible interaction and gestural interaction. In this paper, we present the Tangible Gesture Interaction Framework (TGIF) for classifying and guiding works in this field. We propose a classification of gestures according to three relationships with objects: move, hold and touch. Following this classification, we analyzed previous work in the literature to obtain guidelines and common practices for designing and building new tangible gesture interactive systems. We describe four interactive systems as application examples of the TGIF guidelines and we discuss the descriptive, evaluative and generative power of TGIF.

2014

PEGASO :

Chapitre de livre ArODES

a personalised and motivational ICT system to empower adolescents towards healthy lifestyle

Stefano Carrino, Maurizio Caon, Leonardo Angelini, Elena Mugellini, Omar Abou Khaled, Silvia Orte, Eloisa Vargiu, Neil Coulson, José C. E. Serrano, Sarah Tabozzi, Neil Lafortuna, Giovanna Rizzo

Dans Graña, Manuel, Howlett, Robert J., Jain, Lakhmi C., Toro, Carlos, Innovation in medicine and helathcare 2014 (pp. 350-359). 2014, Amsterdam, The Netherlands : IOS Press

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Résumé:

Unhealthy alimentary behaviours and physical inactivity habits are key risk factors for major non communicable diseases. Several researches demonstrate that juvenile obesity can lead to serious medical conditions, pathologies and have important psycho-social consequences. PEGASO is a multidisciplinary project aimed at promoting healthy lifestyles among teenagers through assistive technology. The core of this project is represented by the ICT system, which allows providing tailored interventions to the users through their smartphones in order to motivate them. The novelty of this approach consists of developing a Virtual Individual Model (VIM) for user characterization, which is based on physical, functional and behavioural parameters opportunely selected by experts. These parameters are digitised and updated thanks to the user monitoring through smartphone; data mining algorithms are applied for the detection of activity and nutrition habits and this information is used to provide personalised feedback. The user interface will be developed using gamified approaches and integrating serious games to effectively promote health literacy and facilitate behaviour change.

Affective interaction in smart environments

Article scientifique ArODES

Maurizio Caon, Leonardo Angelini, Omar Abou Khaled, Denis Lalanne, Yong Yue, Elena Mugellini

Procedia Computer Science, 2014, vol. 32, pp. 1016-1021

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Résumé:

We present a concept where the smart environments of the future will be able to provide ubiquitous affective communication. All the surfaces will become interactive and the furniture will display emotions. In particular, we present a first prototype that allows people to share their emotional states in a natural way. The input will be given through facial expressions and the output will be displayed in a context-aware multimodal way. Two novel output modalities are presented: a robotic painting that applies the concept of affective communication to the informative art and an RGB lamp that represents the emotions remaining in the user's peripheral attention. An observation study has been conducted during an interactive event and we report our preliminary findings in this paper.

2023

EYE LEARN :

Conférence ArODES

innovative pedagogical process using eye tracking to enhance systematic clinical reasoning and metacognition in acute care simulation

Jean-Michel Vasse, Alain Verdon, Catherine Senn-Dubey, Leonardo Angelini, Elena Mugellini, Quentin Meteier

Resuscitation Official Journal of the European Resuscitation Council Abstracts of Resuscitation 2023, 2-4 November 2023, Barcelona, Spain

PEOPLE@HES-SO Annuaire et Répertoire des compétences

Angelini Leonardo

Professeur HES assistant

Compétences principales

Gestion de projets

Human Computer Interaction

User Experience

Professeur HES assistant

Collaborateur scientifique HES

PEOPLE@HES-SO
Annuaire et Répertoire des compétences