Members: O. Grynszpan, L. Abbih, Y. Bellik, D. BérouleF. BimbardM. Gouiffès, Y. Guedira, 

Due to aging population and medical progress allowing higher survival rates of people with motor, sensory or cognitive conditions, issues related to handicaps and disabilities have become a major concern for our health system. National and international policies in the last decade have stressed the need for digital technologies to support people with disabilities. Yet, industry still struggles to deliver adequate technology. Using digital technology to support people with disabilities raises new challenges. Rigorous evidence-based methodologies are required to evaluate technological supports, while taking in account their immense potential to individualize interventions. Computational models are also increasingly used to investigate and analyze various disorders.

Building Evidence for Technology and Autism (beta-project.org)


There has been an exponential proliferation of digital technologies supporting the autism community, with no specific mechanism by which autistic people or their caregivers can easily identify and use evidence to gauge whether such technologies are beneficial, or to assess possible harm. The current situation can be characterised as one in which commercially available digital technologies for autism rarely have evidence for effectiveness, whilst such technologies with evidence of effectiveness are rarely commercially available. In this project, we sought to co-develop with the autism community a framework to assess evidence supporting technology-based interventions. This project was funded by the FIRAH (International Foundation of Applied Disability Research), Orange Foundation, the UEFA Foundation for children. It is coordinated with the Centre for Applied Autism Research (CAAR) in the University of Bath (UK). Other partners included the Institute of Robotics and Information and Communication Technologies (IRTIC) in the University of Valencia (Spain), the Patrick Wild Centre of the University of Edinburgh (UK) and Bouvé College of Health Sciences & College of Computer and Information Science in Northeastern University (USA).
We developed a novel scale, called the User-Centered Design for Support (UCDS) scale, to assess research reports on digital technology based supports for autism. We also conducted a Delphi study, which is an online consensus-building technique, to extract recommendations from a panel of experts on digital technology supports for autism. Autistic adults, family members, practitioners/clinicians and researchers were consulted iteratively until a consensual list of guidelines was obtained. The framework we developed can help members of the autism community determine the evidence base before adopting technology-based interventions.

Gaze-contingent interfaces for autism


Gaze plays a major role in the development of social skills in humans and its dysfunctions are an early sign of autism. In a social context, the gaze contributes to communication as an action: It allows individuals to direct the attention of others on elements of the environment, thus yielding a situation of joint attention. Our previous studies in collaboration with the CPU team highlight difficulties faced by people with ASD to adapt their gaze to social situations, especially when they have to guide the gaze of others. To address these questions, we are designing eye-tracking technologies to induce interactions between participants and social virtual humans.

Multimodal and augmented electric wheelchair

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This project in collaboration with the Aimé Cotton Laboratory (LAC) aims to design, implement and evaluate an augmented electric wheelchair for multi-disabled people with motor disabilities
possibly associated to cognitive and/or visual disabilities. It aims at increasing the chair with active optical imaging to make people's movements safer and to provide a multimodal interface adaptable to the sensory-motor and cognitive capacities of the polyhandicapped person. A combination of triangulation laser rangefinders and time-of-flight cameras will make it possible to detect narrow passages (corridors, door thresholds, etc.) and dangerous trajectories (stairs, pavement descents, obstacles, etc.). A multimodal interface offering various modalities input/output interaction (joystick, touchpad, contactors,
occipital control, vibrators, speech recognition and synthesis, ...) will offer a wide range of interaction possibilities in order to facilitate control of the chair, to alert and prevent situations and to adapt in the best possible way to the interaction abilities of the person with multiple disabilities. In particular, a touch interface on a smartphone to control the wheelchair has been developed. Collaborations with Fondation Poidatz, the AFM-Telethon as well as the functional re-education center "Le Brasset" have been put in place for evaluation purposes with the target users.

More details can be found on the FREMA page project.

Spatialized multimodal access to information for blind people

matriceThis project aims to explore a new method for access to documents by the blind that preserve the spatial structure of the information. This method is based on the definition of three levels of access to information: 1- the spatial level that allows the user to perceive the global spatial structure of the information without being hindered by details; 2- the typological level which allows to have access to the type of information explored by the finger (image, table, menu, ...); 3- the substantial level which allows to obtain the detailed content of the item being explored. Different modalities (dynamic tactile graphic display, Braille, speech synthesis, ... ) and devices (tactile matrix, Braille mouse, Braille terminal, ...) allowing access to these three levels will be explored and compared. An initial study to determine the rendering of geometric shapes to be used in the spatial level was carried out with 40 users (who were blindfolded) and has shown that the use of empty rectangles to highlight the different key areas of a document was the best solution.

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Scientific report

LIMSI in numbers

8 Research Teams
100 Researchers
40 Technicians and Engineers
60 Doctoral Students
70 Trainees


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