Schneider Bradley, Banerjee Tanvi, Grover Francis, Riley Michael
Department of Computer Science and Engineering, Wright State University, 303 Russ Engineering Center, Dayton, OH 45435, USA.
Department of Psychology, Center for Cognition, Action, and Perception, University of Cincinnati, Edwards Center 1, Cincinnati, OH 45221, USA.
Healthc Technol Lett. 2020 Feb 17;7(1):25-28. doi: 10.1049/htl.2019.0015. eCollection 2020 Feb.
A feasibility study was conducted to investigate the use of a wearable gait analysis system for classifying gait speed using a low-cost wearable camera in a semi-structured indoor setting. Data were collected from 19 participants who wore the system during indoor walk sequences at varying self-determined speeds (slow, medium, and fast). Gait parameters using this system were compared with parameters obtained from a vest comprising of a single triaxial accelerometer and from a marker-based optical motion-capture system. Computer-vision techniques and signal processing methods were used to generate frequency-domain gait parameters from each gait-recording device, and those parameters were analysed to determine the effectiveness of the different measurement systems in discriminating gait speed. Results indicate that the authors' low-cost, portable, vision-based system can be effectively used for in-home gait analysis.
进行了一项可行性研究，以调查在半结构化室内环境中使用低成本可穿戴摄像头的可穿戴步态分析系统对步态速度进行分类的情况。数据是从19名参与者那里收集的，他们在室内以不同的自行确定速度（慢、中、快）行走序列时佩戴该系统。将使用该系统获得的步态参数与从包含单个三轴加速度计的背心以及基于标记的光学运动捕捉系统获得的参数进行比较。使用计算机视觉技术和信号处理方法从每个步态记录设备生成频域步态参数，并对这些参数进行分析，以确定不同测量系统在区分步态速度方面的有效性。结果表明，作者的低成本、便携式、基于视觉的系统可有效地用于家庭步态分析。
