Yamamoto Akio, Nakamoto Hiroyuki, Yamaji Tokiya, Ootaka Hideo, Bessho Yusuke, Nakamura Ryo, Ono Rei
Department of Community Health Science, Graduate School of Health Science, Kobe University, Kobe, Hyogo, Japan.
Department of System Science, Graduate School of System Informatics, Kobe University, Kobe, Hyogo, Japan.
PLoS One. 2017 Oct 11;12(10):e0183651. doi: 10.1371/journal.pone.0183651. eCollection 2017.
Body movements, such as trunk flexion and rotation, are risk factors for low back pain in occupational settings, especially in healthcare workers. Wearable motion capture systems are potentially useful to monitor lower back movement in healthcare workers to help avoid the risk factors. In this study, we propose a novel system using sheet stretch sensors and investigate the system validity for estimating lower back movement.
Six volunteers (female:male = 1:1, mean age: 24.8 ± 4.0 years, height 166.7 ± 5.6 cm, weight 56.3 ± 7.6 kg) participated in test protocols that involved executing seven types of movements. The movements were three uniaxial trunk movements (i.e., trunk flexion-extension, trunk side-bending, and trunk rotation) and four multiaxial trunk movements (i.e., flexion + rotation, flexion + side-bending, side-bending + rotation, and moving around the cranial-caudal axis). Each trial lasted for approximately 30 s. Four stretch sensors were attached to each participant's lower back. The lumbar motion angles were estimated using simple linear regression analysis based on the stretch sensor outputs and compared with those obtained by the optical motion capture system.
The estimated lumbar motion angles showed a good correlation with the actual angles, with correlation values of r = 0.68 (SD = 0.35), r = 0.60 (SD = 0.19), and r = 0.72 (SD = 0.18) for the flexion-extension, side bending, and rotation movements, respectively (all P < 0.05). The estimation errors in all three directions were less than 3°.
The stretch sensors mounted on the back provided reasonable estimates of the lumbar motion angles. The novel motion capture system provided three directional angles without capture space limits. The wearable system possessed great potential to monitor the lower back movement in healthcare workers and helping prevent low back pain.
身体动作,如躯干屈曲和旋转,是职业环境中腰痛的危险因素,尤其是在医护人员中。可穿戴运动捕捉系统可能有助于监测医护人员的下背部运动,以帮助避免这些危险因素。在本研究中,我们提出了一种使用片状拉伸传感器的新型系统,并研究该系统在估计下背部运动方面的有效性。
六名志愿者(女性:男性 = 1:1,平均年龄:24.8 ± 4.0岁,身高166.7 ± 5.6厘米,体重56.3 ± 7.6千克)参与了涉及执行七种类型动作的测试方案。这些动作包括三种单轴躯干动作(即躯干屈伸、躯干侧屈和躯干旋转)和四种多轴躯干动作(即屈曲 + 旋转、屈曲 + 侧屈、侧屈 + 旋转以及绕头尾轴移动)。每个试验持续约30秒。在每个参与者的下背部附着四个拉伸传感器。基于拉伸传感器的输出,使用简单线性回归分析估计腰椎运动角度,并与通过光学运动捕捉系统获得的角度进行比较。
估计的腰椎运动角度与实际角度显示出良好的相关性,屈伸、侧屈和旋转动作的相关值分别为r = 0.68(标准差 = 0.35)、r = 0.60(标准差 = 0.19)和r = 0.72(标准差 = 0.18)(所有P < 0.05)。所有三个方向的估计误差均小于3°。
安装在背部的拉伸传感器对腰椎运动角度提供了合理的估计。这种新型运动捕捉系统提供了三个方向角度且没有捕捉空间限制。该可穿戴系统在监测医护人员下背部运动及预防腰痛方面具有巨大潜力。