Author : Björn Friedrich, Enno-Edzard Steen, Sebastian Fudickar and Andreas Hein
Affiliation : Carl von Ossietzky University
Country : Germany
Category : Computer Science & Information Technology
Volume, Issue, Month, Year : 12, 1/2, April, 2021
A continuous monitoring of the physical strength and mobility of elderly people is important for maintaining their health and treating diseases at an early stage. However, frequent screenings by physicians are exceeding the logistic capacities. An alternate approach is the automatic and unobtrusive collection of functional measures by ambient sensors. In the current publication, we show the correlation among data of ambient motion sensors and the well-established mobility assessments Short-PhysicalPerformance-Battery, Tinetti and Timed Up & Go. We use the average number of motion sensor events as activity measure for correlation with the assessment scores. The evaluation on a real-world dataset shows a moderate to strong correlation with the scores of standardised geriatrics physical assessments.