Cognitive disabilities from Alzheimer’s disease trigger difficulties during instrumental activities of daily living (IADL) that could be detected at the very beginning of the disease. The smart home, equipped with a large set of sensors, has the potential of automatically measuring the participants’ performance in everyday life and thus detect AD early.
Experiments are carried out with participants aged 65 or older, divided in 3 groups: healthy subjects, subjects with mild cognitive impairment (MCI) and subjects with mild Alzheimer’s disease. The experimental protocol includes the completion of five IADLs by the participant (such as cleaning the bathroom or preparing lunch) under the supervision of an occupational therapist. In addition, the experiment is recorded via five cameras for further analysis.
Moreover, the interdisciplinarity between the clinical and technical teams through different research centers adds challenges for the joining of expertise and the development of collaborative tools. As a result of the experiments, two subprojects emerged: one consisting of the creation of a transdisciplinary collaboration tool and the other dedicated to the analysis of collected sensor data.
Hélène Pigot, Domus laboratory, Université de Sherbrooke
Nathalie Bier, Université de Montréal
Mathieu Gagnon, Domus laboratory, Université de Sherbrooke
Jules Randolph, Domus laboratory, Université de Sherbrooke