Detecting differences in limb load asymmetry during walking between older adult fallers and non-fallers using in-shoe sensors

Background: Previous studies have reported that clinical walk tests could not detect differences between fallers and non-fallers in older adults. With advancements in wearable technology, it may be possible to assess differences in loading parameters in clinical settings using portable data collection methods. Research question: The purpose of this study was to determine if wearable sensors (loadsol (R)) are reliable for assessing asymmetry of contact time, peak force, loading rate (LR), and impulse in older adults and determine if the insole can detect differences in these parameters between fallers and non-fallers during walking. Methods: Fifty-five older adults (74.1 +/- 6.1 years) walked at their maximum speed on a flat floor. Force data were collected from insoles (100 Hz) during a 10-m walk test. To assess reliability, an intraclass correlation coefficient [ICC(2,k)] was generated for each asymmetry variable. To determine differences between fallers and non-fallers, analysis of covariance (ANCOVA; covariate: body mass index) was completed for each variable. Results: The ICC of peak force asymmetry (PFA) was 0.942, but other ICCs were less than 0.75. The ANCOVA results indicate that the loadsol (R) can detect differences in PFA between fallers and non-fallers. The PFA was significantly greater in fallers than in non-fallers. Significance: The ability to collect force data while walking using loadsol (R) has the potential to broaden the research questions investigated, explore clinical applications, and increase generalizability.