Biomedical Engineering, School of Biological Sciences, University of Reading, Reading RG6 6DH, UK.
Information Systems Engineering, University of Colombo School of Computing, Colombo 00700, Sri Lanka.
Sensors (Basel). 2022 Sep 1;22(17):6605. doi: 10.3390/s22176605.
A person's walking pattern can reveal important information about their health. Mounting multiple sensors onto loose clothing potentially offers a comfortable way of collecting data about walking and other human movement. This research investigates how well the data from three sensors mounted on the lateral side of clothing (on a pair of trousers near the waist, upper thigh and lower shank) correlate with the data from sensors mounted on the frontal side of the body. Data collected from three participants (two male, one female) for two days were analysed. Gait cycles were extracted based on features in the lower-shank accelerometry and analysed in terms of sensor-to-vertical angles (SVA). The correlations in SVA between the clothing- and body-mounted sensor pairs were analysed. Correlation coefficients above 0.76 were found for the waist sensor pairs, while the thigh and lower-shank sensor pairs had correlations above 0.90. The cyclical nature of gait cycles was evident in the clothing data, and it was possible to distinguish the stance and swing phases of walking based on features in the clothing data. Furthermore, simultaneously recording data from the waist, thigh, and shank was helpful in capturing the movement of the whole leg.
一个人的行走模式可以揭示其健康的重要信息。将多个传感器安装在宽松的衣物上，可能提供了一种舒适的方式来收集关于行走和其他人体运动的数据。本研究调查了安装在衣物侧面（腰部附近的裤子、大腿上部和小腿下部）的三个传感器的数据与安装在身体正面的传感器的数据的相关性。对三名参与者（两名男性，一名女性）两天的数据进行了分析。根据小腿加速度计中的特征提取步态周期，并根据传感器到垂直角度（SVA）进行分析。分析了衣物和身体安装的传感器对之间的 SVA 相关性。腰部传感器对的相关系数高于 0.76，而大腿和小腿下部传感器对的相关系数高于 0.90。在衣物数据中可以明显看出步态周期的周期性，并且可以根据衣物数据中的特征区分行走的站立和摆动阶段。此外，同时记录腰部、大腿和小腿的数据有助于捕捉整个腿部的运动。
