In-home, non-contact sensors that can identify changes in movement and behaviors may allow age-related diseases, including Parkinson’s, to be detected early, a study reports.
By using machine learning tools, the study shows how outcomes such as fall risk, frailty, and cognitive abilities may be assessed in a home setting. Such data may help scientists to discover new digital biomarkers to monitor disease activity.
“We were able to show that such a systems approach — in contrast to the common use of a few health metrics — [helps] to detect age-relevant health problems such as cognitive impairment, fall risk or frailty surprisingly well,” Tobias Nef, PhD, co-study lead, from the University of Bern, in Switzerland, said in a press release.
Read more at: https://parkinsonsnewstoday.com/news/digital-home-sensors-may-help-early-detection-parkinsons/
