Metrics from in-home sensor data to assess the effect of clinical therapies
Published On: 09-01-2017
A set of metrics and a methodology were developed to characterize a subject’s ability to ambulate. These metrics use the movement of the subject’s centroid as detected by an inexpensive depth camera system. The centroid is chosen as it is less sensitive to cluttered environments typically found in a person’s home. Three classes of metrics focusing on three major categories of motion were developed. The first class measures fundamental characteristics of movement in three directions. The second class focuses on measuring the walk’s entropy. The third class uses periodicity in the subject’s motion to deduce temporal gait parameters including stride length. Metrics are validated and compared to existing Fall Risk Assessments (FRA’s). While results show strong correlation to many FRA’s, not every subject has the same relationships between metrics and FRA’s suggesting a unique “fingerprint” of metrics associated with a subject and/or their condition.
The methodology was tested using a group of subjects undergoing Balance Wear Therapy targeting sensory inputs to improve balance control. The ability of the metrics to detect changes in the subject’s ambulation when the vest is either put on, or taken off was also explored. Results show sufficient sensitivity to detect changes when the vest is donned and doffed. Many effects are not seen immediately, but over 2–4 h following donning or doffing the vest. Results also demonstrate the ability, using the size of the analysis window, to focus on the time required for the effects of each metric to change.
Wallace, R., Abbott, C., Gibson-Horn, C., Rantz, M., & Skubic, M. (2017). Metrics from in-home sensor data to assess the effect of clinical therapies. Smart Health, 3-4, 1-19.
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