Faculty of Science and Technology, Bournemouth University, Fern Barrow, Poole BH12 5BB, UK.
Royal Bournemouth Hospital, UK, CoPMRE Bournemouth University, Fern Barrow, Poole BH12 5BB, UK.
Sensors (Basel). 2018 Feb 24;18(2):676. doi: 10.3390/s18020676.
This paper aims to assess the use of Inertial Measurement Unit (IMU) sensors to identify gait asymmetry by extracting automatic gait features. We design and develop an android app to collect real time synchronous IMU data from legs. The results from our method are validated using a Qualisys Motion Capture System. The data are collected from 10 young and 10 older subjects. Each performed a trial in a straight corridor comprising 15 strides of normal walking, a turn around and another 15 strides. We analyse the data for total distance, total time, total velocity, stride, step, cadence, step ratio, stance, and swing. The accuracy of detecting the stride number using the proposed method is 100% for young and 92.67% for older subjects. The accuracy of estimating travelled distance using the proposed method for young subjects is 97.73% and 98.82% for right and left legs; and for the older, is 88.71% and 89.88% for right and left legs. The average travelled distance is 37.77 (95% CI ± 3.57) meters for young subjects and is 22.50 (95% CI ± 2.34) meters for older subjects. The average travelled time for young subjects is 51.85 (95% CI ± 3.08) seconds and for older subjects is 84.02 (95% CI ± 9.98) seconds. The results show that wearable sensors can be used for identifying gait asymmetry without the requirement and expense of an elaborate laboratory setup. This can serve as a tool in diagnosing gait abnormalities in individuals and opens the possibilities for home based self-gait asymmetry assessment.
本文旨在评估使用惯性测量单元（IMU）传感器通过提取自动步态特征来识别步态不对称。我们设计并开发了一个安卓应用程序，从腿部实时同步收集 IMU 数据。我们的方法的结果使用 Qualisys 运动捕捉系统进行验证。数据来自 10 名年轻和 10 名老年受试者。每位受试者在直走廊中进行一次试验，包括 15 步正常行走、转弯和另外 15 步。我们分析了总距离、总时间、总速度、步长、步幅、步频、步幅比、站立和摆动的数据。使用所提出的方法检测步幅数的准确性对于年轻受试者为 100%，对于老年受试者为 92.67%。使用所提出的方法估计年轻受试者的行进距离的准确性为 97.73%和 98.82%，对于右和左腿；对于老年受试者，为 88.71%和 89.88%，对于右和左腿。年轻受试者的平均行进距离为 37.77 米（95%置信区间±3.57），老年受试者为 22.50 米（95%置信区间±2.34）。年轻受试者的平均行进时间为 51.85 秒（95%置信区间±3.08），老年受试者为 84.02 秒（95%置信区间±9.98）。结果表明，可穿戴传感器可用于识别步态不对称，而无需复杂的实验室设置的要求和费用。这可以作为诊断个体步态异常的工具，并为基于家庭的自我步态不对称评估开辟可能性。
