Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
Department of Rehabilitation Medicine, University of Washington, Seattle, WA 98195, USA.
Clin Biomech (Bristol). 2022 Oct;99:105741. doi: 10.1016/j.clinbiomech.2022.105741. Epub 2022 Aug 17.
Step activity monitors provide insight into the amount of physical activity prosthesis users conduct but not how they use their prosthesis. The purpose of this research was to help fill this void by developing and testing a technology to monitor bodily position and type of activity.
Thin inductive distance sensors were adhered to the insides of sockets of a small group of transtibial prosthesis users, two at proximal locations and two at distal locations. An in-lab structured protocol and a semi-structured out-of-lab protocol were video recorded, and then participants wore the sensing system for up to 7 days. A data processing algorithm was developed to identify sit, seated shift, stand, standing weight-shift, walk, partial doff, and non-use. Sensed distance data from the structured and semi-structured protocols were compared against the video data to characterize accuracy. Bodily positions and activities during take-home testing were tabulated to characterize participants' use of the prosthesis.
Sit and walk detection accuracies were above 95% for all four participants tested. Stand detection accuracy was above 90% for three participants and 62.5% for one participant. The reduced accuracy may have been due to limited stand data from that participant. Step count was not proportional to active use time (sum of stand, walk, and standing weight-shift times).
Step count may provide an incomplete picture of prosthesis use. Larger studies should be pursued to investigate how bodily position and type of activity may facilitate clinical decision-making and improve the lives of people with lower limb amputation.
步活动监测器可深入了解假肢使用者进行的身体活动量,但无法了解他们如何使用假肢。本研究的目的是通过开发和测试一种监测身体位置和活动类型的技术来填补这一空白。
将薄的感应距离传感器粘贴到一小群小腿假肢使用者的接受腔内,两个位于近端位置,两个位于远端位置。进行了实验室内结构化协议和实验室外半结构化协议的视频记录,然后参与者佩戴传感系统长达 7 天。开发了一种数据处理算法来识别坐、坐姿转移、站、站立体重转移、行走、部分脱卸和不使用。将结构化和半结构化协议中的感应距离数据与视频数据进行比较,以确定准确性。记录居家测试期间的身体位置和活动情况,以描述参与者对假肢的使用情况。
所有 4 名测试参与者的坐和走检测准确率均高于 95%。3 名参与者的站检测准确率高于 90%,1 名参与者的准确率为 62.5%。准确率降低可能是由于该参与者的站立数据有限。步数与活动时间(站立、行走和站立体重转移时间之和)不成比例。
步数可能无法全面反映假肢的使用情况。应开展更大规模的研究,以调查身体位置和活动类型如何促进临床决策并改善下肢截肢者的生活。