Specific changes in our movement patterns can be indicators of several health problems: For instance, decrease in strength often correlates with risk of falls, mild cognitive impairment, depression, sleep problems, respiratory problems, cardiac arrhythmias and increasing myocardial weakness or worsening of a COVID-19 infection. In older individuals, systematic detection of such changes could help identify chronic diseases such as dementia, Parkinson's disease, or heart disease at an early stage. These age-related health problems are often discovered late, and their progression is usually difficult to assess objectively.
An interdisciplinary research team led by Tobias Nef of the ARTORG Center for Biomedical Engineering Research, and Professor Emeritus of Cardiology Hugo Saner of the University of Bern and Bern University Hospital, now shows how large-scale, sensor-based health monitoring could tackle these problems. The researchers combined a variety of everyday activity and behavior patterns measured by sensors in the homes of elderly study participants helping them to create a summary picture. "We used non-contact sensors at home to create an extensive collection of digital measures that capture broad parts of daily life, behavior and physiology, in order to identify health risks of older people at an early stage," explains study first author and postdoctoral researcher Dr. Narayan Schütz. This may benefit early detection as well as foster development of personalized treatments and research into new therapeutic approaches and drugs. The study was published in npj Digital Medicine.