Étude et conception d'un système de personnalisation et d'aide fonctionnelle multi-agents permettant d'assister simultanément de manière transparente les activités de vie quotidienne de multiples personnes dans un Habitat Intelligent pour la Santé

The application domains of this thesis are Health Smart Homes, and the research is more precisely centered on the improvement of daily-living for cognitively impaired persons and theirs caregivers.The proposed system can observe the context of each person, personalize the environment and assist the tasks detected if they need to be. Every action of the system is as unobtrusive as possible and takes into consideration the presence of more than one person. To personalize and assist the daily-living activities of a lone person, we need to know his personal context. This context is the conjunction of the preferences and habits, the illness or impairment, the movements in the smart home and the state of the various sensor and electrical devices, and the current activities that are detected for one person. To be able to assist many persons simultaneously, we need to compute the overall conjunction of each and every person's context since every presence can influence the global context and every personal one. This complexity brings a lot of problems like the multiple person localization and identification, or the personalization and assistance of multiple persons in the same space with various activities. Those problems are even more interesting since, following an ethical choice to ensure inhabitant's privacy, this project avoid the use of some intrusive technologies

Participative Urban Health and Healthy Aging in the Age of AI

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2022, held in Paris, France, in June 2022. The 15 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 33 submissions. They cover topics such as design, development, deployment, and evaluation of AI for health, smart urban environments, assistive technologies, chronic disease management, and coaching and health telematics systems

Pervasive informatics and persistent actimetric information in health smart homes

International audienceThis paper discuss the ability to obtain a reliable pervasive information at home from a network of localizing sensors allowing to follow the different locations at which a dependent (elderly or handicapped) person can be detected. The data recorded can be treated as the sequence of color coding numbers of balls (symbolizing activity-stations) taken in a Polya's urn, in which the persistence of the presence in an activity-station is taken into account by adding a number of balls of the same color as the ball just drawn. We discuss the pertinency of such a procedure to early detect sudden or chronic changes in the parameters values of the random process made of the succession of ball numbers and we use it to trigger alarms

Détection de la présence humaine et évaluation de la qualité du sommeil en établissement d’hébergement pour personnes âgées dépendantes (EHPAD)

In France, in Europe and worldwide, the aging population is a reality. Some of these elderly people lose their autonomy as they are no longer able to manage alone the tasks of daily life. The societal issue is therefore to ensure a level of well-being and safety of these persons, consistent with changes in living standards, customs and modern habits. The research areas related to the problems of elderly people at home are showing great dynamism, while the nursing home, which remains the solution for cases of high dependence, is somewhat neglected. Nevertheless, staff shortages combined with rising costs and residents’ demands offer an opportunity for innovative ICT-based solutions. The work presented here was performed, in the context of a CIFRE doctoral thesis, within the Legrand research team and at the physics and electronics department of Mines-Telecom SudParis at Evry. The subject and project aim was twofold: firstly, designing a new sensor which will be incorporated in the electrical installation of the patient’s living space, and secondly, a multi-sensor merger to monitor the activity of the resident in order to enable real-time reporting of situations requiring the caregiver’s intervention or to detect slow drifts whose interpretation will be the responsibility of the medical staff. The work carried out for the purpose of this thesis has been included partially in the FUI 14 project whose propose is precisely the “supervision of residents in the nursing home”. The present paper is structured in such a way as to introduce the background of the work and the approach taken to perform it. The context and needs identified for monitoring of nursing home residents are also introduced. We begin by describing existing monitoring systems and the technical methods used to detect emergency situations. We end the first part (chapter 1) of this paper by specifying the major problem encountered when testing existing monitoring systems based on ambient sensors: namely how to detect the presence of an immobile and silent person in the room. Using an existing pyro-electric infrared sensors network installation in a nursing home, the next section proposes an original solution for detecting human presence in a room and also for differentiating between the presence of one and the presence of more than one person (chapter 2). Chapter 3 presents a new sensor integrated into the electrical installation of the patient’s living space. Here, we introduce a thermopile based thermal sensor in order to detect the presence of a person in his/her living space. In this work we restrict the use of this sensor to detecting the presence of the person in bed (chapter 4). The estimation of sleep quality which represents the original dimension of our work is presented in chapter 5. Differentiation between different phases of sleep is based on unsupervised classification approaches. Our project opens up encouraging prospects for the use of this type of sensor for relatively fine characterization of different kinds of sleepEn France, en Europe et dans le monde entier, le vieillissement de la population est une réalité. Une partie de cette population âgée est dite dépendante car elle n’est plus en mesure d’assumer seule les tâches de la vie quotidienne. L’enjeu sociétal est alors de garantir un niveau de bien-être et de sécurité à ces personnes, compatible avec l’évolution du niveau de vie et des usages et habitudes ‘modernes’. Très logiquement, les domaines de recherche liés à la problématique des personnes âgées à domicile font preuve d’un grand dynamisme, alors que la maison de retraite, qui reste la solution pour la grande dépendance, a été un peu délaissée. Néanmoins, la pénurie de personnel conjuguée à l’augmentation des coûts et des exigences des résidents offre une opportunité à des solutions innovantes basées sur les TIC. Les travaux de cette thèse de doctorat sous convention CIFRE se sont déroulés dans ce contexte au sein de l’équipe de recherche de Legrand et du département d’Electronique et Physique de Télécom SudParis à Evry. Le sujet concerne la conception d’un nouveau capteur (non-porté) intégrant l’installation électrique du lieu de vie du patient ainsi que la fusion avec d’autres capteurs de l’infrastructure afin de suivre l’activité du résident et, le cas échéant, soit signaler en temps réel des situations nécessitant le recours d’un aidant, soit identifier des dérives lentes dont l’interprétation sera du ressort du personnel médical. Les travaux de la thèse ont été en partie intégrés au projet FUI14 « E-monitor’âge » dont l’objectif est précisément la « supervision » des résidents. Ce mémoire est structuré de manière à présenter l’historique de ces travaux et la démarche opérée pour leur réalisation. Nous introduisons le contexte et les besoins identifiés pour le suivi des personnes âgées dans les maisons de retraites. Nous faisons un point sur les systèmes de supervision/monitoring existants et nous présentons les méthodes et les techniques de détection de situations d’urgence. Nous terminons cette partie du mémoire (chapitre 1) par la spécification du problème majeur rencontré par ces systèmes de supervision qui est celui de la détection de présence d’une personne. En s’appuyant sur la technologie des capteurs pyro-électriques, la partie suivante propose une solution originale de traitement de signal pour la détection d’une présence humaine dans une chambre voire la détection de présence de plusieurs personnes à la fois (chapitre 2). Le chapitre 3 introduit ensuite un capteur thermique à base de thermopiles afin de détecter la présence d’une personne dans son lit, ce que ne permet pas la technologie pyro-électrique qui ne détecte pas un corps chaud immobile. Dans cette partie nous limitons l’utilisation de ce capteur à la détection de la présence de la personne dans son lit (chapitre 4) voire à l’estimation de la qualité de son sommeil qui constitue d’une part l’originalité de nos travaux s’appuyant sur des approches de classification non-supervisée, et qui ouvre des perspectives encourageantes quant à l’utilisation de ce capteur pour caractériser relativement finement le type de sommeil d’autre part (chapitre 5

Pervasive informatics and persistent actimetric information in health smart homes : different approaches

International audienceINTRODUCTION: This paper discuss the ability to obtain a reliable pervasive information at home from a network of localizing sensors allowing to follow the different activity-station at which a dependent (elderly or handicapped) person can be detected. Since 12 years ([1-3]), many experiments have been achieved for watching dependent people at home, in particular elderly and handicapped persons. For acquiring data necessary to permit the alarms triggering, numerous sensors have been invented, in particular for localizing the person at home or in the surroundings. These localizers are on the body (GPS, accelerometers,...), in the flat rooms (on the walls: infrared or radar detectors; on the ground, the bed or the chairs: pressure sensors), on the doors (magnetic switches) or in gardens and streets (video-cameras). METHODS: The data recorded can be treated as time series as the sequence of color coding numbers of balls (symbolizing activity-stations) taken in a Polya's urn, in which the persistence of the presence in an activity-station is represented by adding a number of balls of the same color as the ball just drawn ([5]). The sequence could also represent historical data from a model, deriving from language models and markovian processes existing in speech recognition research, where the persistence is the probability to stay at the same activity-station ([6]). Other models can also be used as well as the mean time passed or the remaining time in the activity-station. Theses models are compared in order to use the most representative one. RESULTS: Using statistics, the best model offers up to 98.03% of good prediction location, considering only the last second of location but distinguishing days of week. Other models need to be improved. We discuss the pertinence of such procedures to early detect sudden or chronic changes in the parameters values of the random process made of the succession of ball numbers. We will use the best procedure to trigger alarms, which will occur when an incorrect prediction is made, or when the person persists at the same station more than the mean time passed in this station, or when the remaining time is passed. CONCLUSIONS: The sensors network is very important to follow up the dependent people during their walk trajectories inside home or outside. If the space/time data are acquired on healthy elderly people or on patients which suffer from neuro-degenerative diseases, the sensors recording must be very well calibrated, to give birth to specific profiles concerning the time series which correspond to the successive locations of the dependent person in rooms inside the flat or in specific places inside a room ([4]). Simpler than Polya's urns derived approach, the Markovian approach seems to be a good way of location modeling. Other models need to be improved in order to concurrence it. A big hope comes from the ambient information techniques to be able to detect a sudden fall on the ground or a progressive stereotyped behavior (for the early diagnosis of chronic neuro-degenerative diseases like the Alzheimer or Parkinson ones). ACKNOWLEDGEMENTS: AFIRM Team from TIMC-IMAG Laboratory for HIS data records. REFERENCES 1. Couturier et al., Rev. Gériatrie 21:23-31, 1996. 2. Demongeot et al., Comptes Rendus Biologies 325:673-682, 2002. 3. Das et al., Pervasive and Mobile Computing 2:372-404, 2006. 4. Le Bellego et al., IEEE Transactions ITB 10:92-99, 2006. 5. Demongeot et al., IEEE CISIS & APPLIMS, 589-594, 2008. 6. Fouquet et al., IEEE CISIS, 2009

Pervasive informatics and persistent actimetric information in health smart homes : From Language Model to Location Model

International audienceThis paper presents an approach of location model deriving from language models existing in speech recognition research. The purpose is to applicate existing model in speech recognition to predict location of an elderly person. Using statistics, the model offers up to 98.03% of good prediction location, considering only the last second of location but distinguishing days of week. Simpler than Polya's urns derived approach, this approach seems to be a good way of location modelling