State of the Field of Waist-Mounted Sensor Algorithm for Gait Events Detection: A Scoping Review
State of the Field of Waist-Mounted Sensor Algorithm for Gait Events Detection: A Scoping Review
复制标题
用于步态事件检测的腰部安装传感器算法领域的现状：范围界定审查
DOI：
10.1016/j.gaitpost.2020.03.021
复制
发表时间：
2020
期刊：
影响因子：
2.4
通讯作者：
Takahashi M
中科院分区：
文献类型：
--
作者：
Iijima H;Takahashi M
背景腰部安装传感器是一种有吸引力的选择，可在临床环境中检测步态期间足部接触的初始和结束，而不干扰受试者的自然步态。研究问题旨在检查用于成人运动期间步态事件检测的腰部安装传感器算法领域的现状。方法范围界定审查设计用于搜索截至 2018 年 10 月发布的同行评审文献或会议记录，以查找步态事件检测算法。我们以描述性方式分析了研究数据。结果总共选择了 588 篇潜在相关文章，其中 14 篇（171 名参与者，平均年龄：44.0 岁）符合纳入标准。我们确定了 15 种使用生物力学理论开发的算法，包括代表水平行走步态的倒立摆模型。大多数算法使用三轴加速度数据来估计健康成年人的步态事件，绝对误差约为 50-100 毫秒。然而，试验间存在大量异质性，并且只有少数算法在神经系统疾病患者中得到验证。较低的步态速度降低了步态事件估计的准确性。意义没有算法在使用腰部安装的传感器水平行走期间的步态事件估计中表现出出色的性能。需要对所有可用算法与一个数据集的既定参考标准进行更多比较，以确定最佳算法。由于患有病理状况的患者表现出躯干加速度改变和步态速度变慢，因此在推荐特定算法作为临床实践的有效策略之前，需要开发一种不依赖于特定信号特征且对各种步态速度具有鲁棒性的算法。
BackgroundA waist-mounted sensor is an attractive option for detecting initial and end of foot contacts during gait in a clinical setting without disturbing the subject’s natural gait.Research questionTo examine the current state of the field regarding waist-mounted sensor algorithms for gait event detection during locomotion in adults.MethodsA scoping review design was used to search peer-reviewed literature or conference proceedings published through October 2018 for algorithms for gait event detection. We analyzed data from the studies in a descriptive manner.ResultsIn total, 588 potentially relevant articles were selected, of which 14 (171 participants, mean age: 44.0 years) met the inclusion criteria. We identified 15 algorithms developed using biomechanical theories including the inverted pendulum model that represents gait during level walking. Most algorithms estimated gait events using triaxial acceleration data with an absolute error of approximately 50–100 ms in healthy adults. However, there was a large amount of inter-trial heterogeneity, and only a few algorithms were validated in patients with neurological diseases. Lower gait speed reduced the accuracy of gait event estimation.SignificanceThere was no algorithm that showed outstanding performance in the estimation of gait events during level walking using the waist-mounted sensor. More comparisons of all available algorithms with an established reference standard for one data-set are needed to identify the best algorithms. As patients with pathological conditions display altered trunk acceleration and slower gait speeds, the development of an algorithm that does not rely on particular signal characteristics and is robust for a wide range of gait speeds is needed before a specific algorithm can be recommended as a valid strategy for clinical practice.