Metrics from in-home sensor data to assess gait change due to weighted vest therapy
Smart Health(2017)
摘要
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.
更多查看译文
关键词
gait change,vest therapy,in-home
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络