Designing a Gait Recognition Algorithm for Older Adults Using Mobility Aids: Prospective Cohort Study

This study successfully recognized the walking patterns of older adults with or without mobility aids. The performance metrics show that this algorithm has promise for being used to monitor physical activity. This approach is computationally lightweight and explainable. Our calibration approach can be adopted to tune to new populations and has a low barrier to entry for adopting a new technology due to the sole reliance on accelerometer data which is a standard sensor in wearable devices. The most noteworthy parameter adjustment is the ratio for superharmonics. Low values for the subharmonic and superharmonic ratios cause the algorithm not to detect walking in our older adult data. We validated the algorithm on ten mobility aid users. A larger study with more participants using mobility aids is necessary to conduct a deeper analysis on what parameters work best for this population. Future work includes validating the algorithm's ability to estimate step counts and measure physical activity in real-world settings.