bsafe UI

Check out the video here: https://vimeo.com/355562822

The increasing prevalence of falls in the aging population, is a serious threat to life expectancy, wellbeing/quality of life and healthcare costs. Strategies to prevent fall incidents exist and rely on timely detection of aberrant movement patterns. Unfortunately, not many vulnerable patients present themselves to a doctor for fall prevention and not many clinicians are able to detect fall risk “by eye.

We propose to fill this gap by developing a proof of concept (POC) of a smartphone app (bsafe) that can record a short video of the walking pattern and automatically analyse it to conclude whether the person has an elevated chance to fall.

The algorithms that will be developed within bsafe use supervised machine learning, driven by the expert opinion of a health care professional. The intended users of bsafe may be healthcare professionals or close relatives of elderly persons who may be worried about the walking stability of their loved ones.

After a successful POC, bsafe should be extended towards database interaction (eventually integration into Electronic Health Records), and contact information of local balance trainings programs for elderly, extended trainings sets and clinical validation studies of bsafe.