Farah ABDEL KHALEK

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Topic: Connected, intelligent housing to help people stay at home: a contribution to characterizing the state of frailty of an elderly person.

Summary: By 2050, France will have almost 4 million people aged over 60 suffering from loss of autonomy, an increase of over 60% compared to the last census in 2015. These few figures give an idea of the stakes involved in the medical-social sector, and of the challenge that the ageing population represents for our society in various respects. In an attempt to respond to the desire of the French to be able to remain at home, expressed via the Grand Age concertation in 2019, the aim of the thesis is to make a contribution to helping elderly people remain at home.

The research approach consists first and foremost in identifying the main causes of departure from the home to independent living facilities, so as to focus on the very first causes representing the majority of cases of departure from the home. The project's ambition is to be able to detect the first warning signs of loss of autonomy in the elderly: the physical and functional variables linked to their increasing frailty, notably governing balance, are certainly preponderant factors. However, frailty is a complex, multifactorial phenomenon that is difficult to quantify. Healthcare practitioners are able to assess the evolution of frailty through clinical observation of people, using questionnaires, but the parameters observed are not objectified in the day-to-day clinical approach, and the frequency of observations, which is difficult to implement, is not individualized and does not allow for appropriate follow-up.

We will therefore seek to link the relevant parameters used by professionals to detect changes in the state of frailty with the main causes of people leaving home. The aim of the study is to equip the home, and not the person, with devices to carry out continuous measurements in the home - a natural, non-stigmatizing and a priori non-intrusive environment - in order to obtain relevant, objective information about the person's behavior. This approach will be validated by the definition of a kit of connected objects associated with intelligent data processing.

The work is therefore organized into 4 phases: (1) determine the main causes of home departure; (2) analyze the professional practices used by practitioners to characterize the state of frailty of an elderly subject, and identify the relevant objectifiable parameters; (3) validate these diagnostically relevant parameters through preliminary measurements carried out in close collaboration with practitioners, and identify which measurements are feasible in the home; (4) implement a proof-of-concept in the form of an experimental demonstrator based on connected objects to be placed in the home measuring balance and other parameters determined during the previous stages.

Tags: Elderly, IoT, Machine learning, Data fusion

Supervisor: Christine Barthod

Co-supervisors: Stéphane Perrin, Eric Bénoit, Luc Marechal, Benoit Godiard

Start of thesis: November 2020

Doctoral school: SISEO "Sciences et Ingénierie des Systèmes, de l'Environnement et des Organisations" (Science and Engineering of Systems, the Environment and Organizations)