Institute of Sports Science, Leibniz University Hannover, 30167 Hannover, Germany.
Sensors (Basel). 2021 Oct 5;21(19):6621. doi: 10.3390/s21196621.
Gait symmetry analysis plays an important role in the diagnosis and rehabilitation of pathological gait. Recently, wearable devices have also been developed for simple gait analysis solutions. However, measurement in clinical settings can differ from gait in daily life, and simple wearable devices are restricted to a few parameters, providing one-sided trajectories of one arm or leg. Therefore, head-worn devices with sensors (e.g., earbuds) should be considered to analyze gait symmetry because the head sways towards the left and right side depending on steps. This paper proposed new visualization methods using head-worn sensors, able to facilitate gait symmetry analysis outside as well as inside. Data were collected with an inertial measurement unit (IMU) based motion capture system when twelve participants walked on the 400-m running track. From head trajectories on the transverse and frontal plane, three types of diagrams were displayed, and five concepts of parameters were measured for gait symmetry analysis. The mean absolute percentage error (MAPE) of step counting was lower than 0.65%, representing the reliability of measured parameters. The methods enable also left-right step recognition (MAPE ≤ 2.13%). This study can support maintenance and relearning of a balanced healthy gait in various areas with simple and easy-to-use devices.
步态对称性分析在病理性步态的诊断和康复中起着重要作用。最近,也开发出了可穿戴设备来实现简单的步态分析解决方案。然而,临床环境中的测量结果可能与日常生活中的步态不同,而且简单的可穿戴设备只能限制在几个参数上,只能提供一条手臂或腿的片面轨迹。因此,应该考虑使用带有传感器的头戴式设备(例如耳塞)来分析步态对称性,因为头部会根据步伐向左右两侧摆动。本文提出了使用头戴式传感器的新可视化方法,这些方法能够方便地在室内和室外进行步态对称性分析。使用基于惯性测量单元(IMU)的运动捕捉系统收集了 12 名参与者在 400 米跑道上行走的数据。从横向和额状面的头部轨迹中,显示了三种类型的图表,并测量了五个参数概念来进行步态对称性分析。计步的平均绝对百分比误差(MAPE)低于 0.65%,表示测量参数的可靠性。这些方法还可以实现左右步的识别(MAPE ≤ 2.13%)。本研究可以使用简单易用的设备在各个领域支持维持和重新学习平衡健康的步态。