ONWARD, Building 32, Hightech Campus, 5656 AE Eindhoven, The Netherlands.
Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands.
Sensors (Basel). 2021 Apr 13;21(8):2727. doi: 10.3390/s21082727.
Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.
步态分析传统上是在实验室环境中使用昂贵的设备进行的，但是，最近，可靠、经济实惠且可穿戴的传感器已经能够集成到临床应用中，并且可以在日常生活活动中使用。实时步态分析是步态康复技术和神经假体等辅助设备发展的关键。本文对实时步态分析中使用的可穿戴传感器和技术及其在病理步态中的应用进行了系统的回顾。我们从四个主要的科学数据库中确定了 1262 篇文章，其中有 113 篇进行了全文分析。我们发现，脚跟触地和脚趾离地是最受关注的步态事件。惯性测量单元（IMU）是最广泛使用的可穿戴传感器，小腿和脚是首选的放置位置。基于 IMU 的步态检测的地面实况验证最常用的传感器是鞋垫压力传感器。基于规则的技术依赖于阈值或峰值检测，是最广泛使用的步态检测方法。评估标准的异质性使得无法对所有方法的性能进行定量比较。尽管大多数研究预测提出的方法将适用于病理步态，但只有不到三分之一的方法在这些数据上进行了验证。我们考虑了步态检测算法的临床应用，并建议将 IMU 和基于规则的方法相结合作为最佳解决方案。
