Validation of an ambient measurement system (AMS) for walking speed

Jonathan S Varsanik, Zebadiah M Kimmel, Carl de Moor, Wendy Gabel, Glenn A Phillips
Journal of Medical Engineering & Technology 2017, 41 (5): 362-374
Walking speed is an important indicator of worsening in a variety of neurological and neuromuscular diseases, yet typically is measured only infrequently and in a clinical setting. Passive measurement of walking speed at home could provide valuable information to track the progression of many neuromuscular conditions. The purpose of this study was to validate the measurement of walking speed by a shelf-top ambient measurement system (AMS) that can be placed in a patient's home. Twenty-eight healthy adults (16 male, 12 female) were asked to walk three pre-defined routes two times each (total of 168 traversals). For each traversal, walking speed was measured simultaneously by five sources: two independent AMSs and three human timers with stopwatches. Measurements across the five sources were compared by generalised estimating equations (GEE). Correlation coefficients compared pairwise for walking speeds across the two AMSs, three human timers, and three routes all exceeded 0.86 (p < .0001), and for AMS-to-AMS exceeded 0.92 (p < .0001). Aggregated across all routes, there was no significant difference in measured walking speeds between the two AMSs (p = .596). There was a statistically significant difference between the AMSs and human timers of 8.5 cm/s (p < .0001), which is comparable to differences reported for other non-worn sensors. The tested AMS demonstrated the ability to automatically measure walking speeds comparable to manual observation and recording, which is the current standard for assessing walking speed in a clinical setting. The AMS may be used to detect changes in walking speed in community settings.

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