Technologies to Prevent Falls and Their Consequences

Abstract

Thousands of Apps offer guidance on exercise, and consumer electronics such as wristbands or smartphones increasingly offer tools to measure physical activity and mobility. The promised analysis goes far beyond step counting. In sharp contrast, the evidence of mobile gait analysis based on these mass products is rare at best. Seemingly trivial technologies such as automated personal response systems to detect falls are often dysfunctional from a consumer safety perspective. The willingness to use real-world monitoring to personalize training and dynamically give useful feedback is high but the data supporting this are still in an early phase. One reason for this is the lack of patient-centred co-design. Another reason is the notorious attempt to use young volunteers simulating falls to study the phenomenon of falls mostly affecting older persons. Much slower than expected there is the development of attractive gamified training interventions. Gradually, the analysis of real-world mobility data including real-world falls allows the tuning of risk factor analysis and personalization of fall prevention efforts. Last but not least, embedded sensors and other approaches are getting closer to the market to properly assess unrecovered falls and alarm informal or formal helpers to assist fallen persons. The chapter starts with an overview of up-to-date knowledge on falls and then gives a comprehensive overview over the technological areas most likely to help older persons and patients with chronic diseases to cope with their risk of falling,