The goal of the current project is to examine whether and how atypical schedules of work have short-term and long-term effects on cognitive functioning and whether they moderate cognitive trajectories associated with aging, in the direction of an accelerated cognitive aging in people with atypical work schedules. A cohort of 4000 adults covering a wide age range, representative of the French population, will be followed up on 10 years, with three measurement occasions (Wave 1 data collection starts in 2018: Wave 2 data collection starts in 2023; Wave 3 data collection starts in 2028). Data will be obtained using clinical medication examinations, and self-reported data on a website created for the study. At each measurement occasion, participants will complete questionnaires regarding current and past working conditions, personal life (social life, activities), personality and coping, health and neuropsychological tests. A comprehensive assessment of neurocognitive functioning will include several measures of episodic memory, fluid abilities, flexibility, speed of processing and crystallized abilities. A measurement-burst-design will allow to overcome main shortcomings of previous studies, and to dissociate short-term fluctuations, test-retest effects, long-term changes, and measurement errors in neurocognitive measures. The longitudinal design of the study will make it possible to investigate (1) whether atypical work schedules have short-term and long-term negative effects on neurocognition and on neurocognitive aging; (2) whether troubles associated with atypical work schedules on neurocognition and neurocognitive aging are reversible or not, by following up people who left this type of work organization; (3) possible mechanisms involved in the atypical schedules-neurocognition relations, such as quality of sleep, engagement with life, or mood (e.g., depressive symptoms, anxiety); and (4) possible moderators of atypical schedules effects on neurocognitive trends. Both individual characteristics such as personality traits and coping strategies, and contextual factors such as task parameters will be explored as possible moderators of atypical schedules effects on neurocognition. Our main hypotheses are that working in atypical schedules - which challenge natural biological rhythms – may have deleterious effects on neurocognitive functioning, in particular on process-related cognitive abilities such as memory or flexibility, and that these aversive effects may be stronger at older ages than at younger ages. That is, because older brains have reduced cognitive reserve and lower capacities to resist to adversity, they are expected to be more vulnerable than younger ones. We therefore assume that neurocognitive decline over 10 years will be more pronounced for people who work in atypical schedules than others. Sophisticated analyses will help us determine how these atypical schedules may influence neurocognitive functioning. We suppose that reduced quality of sleep, but also smaller engagement with life (social life, activities), may explain why this work organization may influence both the level of cognitive abilities, and how they change over time.

Wearable Biometric Monitoring Devices (WBMDs) represent a recent alterative for the collection of health-related data from people. WBMDs allow for continuous and real time data collection in natural settings. However, these devices face two key challenges: 1) WBMDs require seamless interfaces that are not traumatic to patients; 2) WDBMs continuous flow of data comes at the price of having an enormous amount of information that cannot be analyzed manually. While artificial intelligence (AI) systems emerge as a natural solution to deal with complex data, these require large sets of accurately annotated data, which are cannot be guaranteed. We will build new WBMDs in the form of skin-compliant electrodes, capable of recording electrophysiological signals while guaranteeing patients’ acceptance. Then, a novel AI system will be developed for improved neurodevelopmental stress assessment that exploits weakly annotated data from WBMDs jointly with traditional measures.

In this project, we seek to early diagnose Autistic Spectrum Disorders (ASD), through automated video analysis. In this domain, few reliable solutions exist except off-line human expert analysis. For this purpose, we propose to develop a video interpretation platform allowing both the detection, by non-invasive solutions, of the position of the gaze and the extraction of the movements of a person moving in the scene, and therefore in a natural situation. It would also allow the recognition and the semantic interpretation of certain behaviors predefined by our partner experts, or even of emerging behaviors. This represents an innovation and a major technological breakthrough because it would make it possible to detect the behavioral characteristics of children with autism, to quantify their evolution over time and thus to facilitate the adjustment of the interventions practiced by professionals.

All over the world the increasing prevalence of chronic disorders and its impact on functional decline is challenging the sustainability of health care systems. Older individuals also frequently experience the reversible “frailty syndrome”, which overlaps with chronic diseases, increasing incidence of disability. In the field of Alzheimer’s disease (AD) and related disorders, Information and Communication technologies (ICT) already shown to be useful to improve the clinical assessment. For instance in a previous ANR project (SWEET HOME) Taiwan and French groups have already demonstrated that it is possible to set up in a classical consultation setting a specific room equipped with audio and video sensors in order to assess motor functions and activities of daily living. At the same time in therapeutic clinicians are now able to propose interventions to delay functional decline and sometimes to decrease the burden of the most disturbing behavioral symptoms. Building a global system aiming to take in charge all causes leading to loss of autonomy is a rather complicated task involving numerous ICT solutions which are not always easy to use in everyday life. This is most particularly true for elderly subjects who frequently have the psychological feeling to have no expertise mastery or control on ICT devices use. The SafEE (Safe Easy Environment) project aim is to improve the safety, autonomy and quality of life of older people at risk or suffering from AD and related disorders. More specifically the SafEE project: - focuses on specific clinical targets in three domains: behavior, motricity and cognition - merges assessment and non pharmacological help/interventions - proposes easy ICT device solutions for the end users To reach this goal, the SafEE project will develop: 1/ an ICT-based behavior analysis platform able to detect, recognize and assess daytime (such as agitation) and nighttime (such as sleep disturbances) behavioral patterns (BEHAVIOR), walking/balancing capabilities (MOTRICITY), orientation and procedural memory (COGNITION) 2/ Tailored non pharmacological therapeutic responses: -for sleep and related behavioral disturbances using stimulation aromatherapy automatic fragrance release system tailored to the clinical patterns detected within the assessment phase -for orientation, procedural memory and feeling of control for ICT devices using a training interface based on Kinect sensor and tactile tablet/Smartphone 3/ pilot studies in order to validate the acceptability, sensitivity and efficacy of the systems French partners of the projects include clinicians (CHU, CoBTeK), basic research engineers (INRIA) and industrials (Aromatherapeutics, SolarGames). Taiwan partners also include clinicians (TVGH, NCKUH) and basic research engineers (SMILE NCKU). The innovation of the project lies in a new methodological approach to deal with care of elderly people, through an innovative use of ICT based on (a) the association of assessment and help/intervention method for specific cognitive, behavioral and motor patterns, (b) addressing user needs by associating ICT researchers, clinicians and users from the beginning of the project, (c) proposing the most easy ICT solution for the end users and in the same time (d) providing to the clinician understandable important objective data for the patients’ follow-up.

The COVID-19 pandemic, caused by SARS-CoV2, has spread quickly around the world and has had unprecedented effects on societies, including disease management and health care systems. COVID-19 was described initially as a respiratory disease, however, it is increasingly recognized as a neurological disease. The neurological manifestations of COVID-19, if they are lasting, potentially modify the accuracy and ability of Memory Clinics to conduct appropriate Alzheimer’s care. Both clinical and research programs on Alzheimer's Disease have been disturbed by the COVID-19 pandemic. Preventive measures like social distancing and the use of telehealth have changed practices and brought forth new challenges from the perspective of people with dementia and their caregivers. For example, social distancing measures break down social networks and have led to the discontinuation of many programs designed to provide cognitive stimulation or social interaction. This has contributed to an increase in both social isolation and in the behavioral symptoms in people living with Alzheimer's Disease. While Information and Communication Technologies (ICTs) have led to the development of new remote applications and platforms for telehealth, these applications and platforms must conform to specific clinical conditions, such as ensuring privacy and security. They must also ensure a patient and their caregivers’ ongoing engagement and involvement with the clinician, using these platforms. This working group brings together an international clinical and research team with complementary expertise, to work on Alzheimer’s care and research. Our objectives are: - To identify the biomarkers that are still relevant among the commonly-used and new digital biomarkers for the early onset of Alzheimer’s Disease in individuals who have or have not been infected by SARS-CoV2. - To establish recommendations for the implementation of selected biomarkers in the process of early diagnosis using telehealth. - To conduct a scoping review on the changes and associated challenges related to the acceleration of the use of telehealth for people living with Alzheimer’s Disease induced by COVID-19. - To establish recommendations for better telehealth appropriation by patients with Alzheimer's Disease and their caregivers, in light of current digital means and knowledge, in order to empower patients and to maintain social interactions. - To establish recommendations on the implementation of new models of care for Alzheimer’s Disease based on telehealth and empowerment of patients and caregivers. - To determine a methodological framework to ensure the sustainability of the working group at the end of the funding and that provides best practices for working interdisciplinary on Alzheimer’s Disease care and research.