The aim of our study was to conduct an ad hoc data collection in healthy adults with the intention of extracting individual profiles to study the ability to effectively monitor one's health by extracting relevant indicators. As “each patient is a unique case”, AMISIA (Defi CNRS AUTON project) proposes an integrated approach, combining medical health devices, information technology, and human factors to provide patients, health care actors and family caregivers with both the best incentives and a high degree of monitoring.

We conducted a data collection experiment in Limoges with 61 participants at the Limoges University. Data were biographic elements, socio-economic profiles, cognitive performance (Corsi test results), a psychological battery (anxiety, fatigue, sleep), posture and gait measurement with 4 Imus and a Wii-balance board, and finally physical activity during a week at home (Armband sensors).

For the Corsi virtual walking test, the median memory span for Group A was significantly less (p<0.001) than for Group B. Step count and active energy expenditure were significantly higher in Group B (p<0.05). A multiple regression analysis showed that gender, active energy expenditure, fatigue and tendency to play video games account for 41% of the memory span variance.

We have shown that encouraging physical activity can be based on the knowledge of many parameters, such as weight, age, gender and other bio-psycho-social parameters that must also be included in the model.