Suppr超能文献

用于评估偏瘫性中风患者在机器人辅助步态训练期间异常模式的步态分析系统:一项针对健康成年人的标准关联效度研究。

Gait analysis system for assessing abnormal patterns in individuals with hemiparetic stroke during robot-assisted gait training: a criterion-related validity study in healthy adults.

作者信息

Nakashima Issei, Imoto Daisuke, Hirano Satoshi, Konosu Hitoshi, Otaka Yohei

机构信息

Department of Rehabilitation Medicine, School of Medicine, Fujita Health University, Aichi, Japan.

Toyota Motor Corporation, Aichi, Japan.

出版信息

Front Neurorobot. 2025 May 21;19:1558009. doi: 10.3389/fnbot.2025.1558009. eCollection 2025.

Abstract

INTRODUCTION

Gait robots have the potential to analyze gait characteristics during gait training using mounted sensors in addition to robotic assistance of the individual's movements. However, no systems have been proposed to analyze gait performance during robot-assisted gait training. Our newly developed gait robot," Welwalk WW-2000 (WW-2000)" is equipped with a gait analysis system to analyze abnormal gait patterns during robot-assisted gait training. We previously investigated the validity of the index values for the nine abnormal gait patterns. Here, we proposed new index values for four abnormal gait patterns, which are anterior trunk tilt, excessive trunk shifts over the affected side, excessive knee joint flexion, and swing difficulty; we investigated the criterion validity of the WW-2000 gait analysis system in healthy adults for these new index values.

METHODS

Twelve healthy participants simulated four abnormal gait patterns manifested in individuals with hemiparetic stroke while wearing the robot. Each participant was instructed to perform 16 gait trials, with four grades of severity for each of the four abnormal gait patterns. Twenty strides were recorded for each gait trial using a gait analysis system in the WW-2000 and video cameras. Abnormal gait patterns were assessed using the two parameters: the index values calculated for each stride from the WW-2000 gait analysis system, and assessor's severity scores for each stride. The correlation of the index values between the two methods was evaluated using the Spearman rank correlation coefficient for each gait pattern in each participant.

RESULTS

The median (minimum to maximum) values of Spearman rank correlation coefficient among the 12 participants between the index value calculated using the WW-2000 gait analysis system and the assessor's severity scores for anterior trunk tilt, excessive trunk shifts over the affected side, excessive knee joint flexion, and swing difficulty were 0.892 (0.749-0.969), 0.859 (0.439-0.923), 0.920 (0.738-0.969), and 0.681 (0.391-0.889), respectively.

DISCUSSION

The WW-2000 gait analysis system captured four new abnormal gait patterns observed in individuals with hemiparetic stroke with high validity, in addition to nine previously validated abnormal gait patterns. Assessing abnormal gait patterns is important as improving them contributes to stroke rehabilitation.

CLINICAL TRIAL REGISTRATION

https://jrct.niph.go.jp, identifier jRCT 042190109.

摘要

引言

步态机器人除了能辅助个体运动外,还可利用安装的传感器在步态训练期间分析步态特征。然而,尚未有系统被提出用于分析机器人辅助步态训练期间的步态表现。我们新开发的步态机器人“Welwalk WW - 2000(WW - 2000)”配备了步态分析系统,以在机器人辅助步态训练期间分析异常步态模式。我们之前研究了九种异常步态模式指标值的有效性。在此,我们提出了四种异常步态模式的新指标值,即前躯干倾斜、患侧过度躯干偏移、膝关节过度屈曲和摆动困难;我们研究了WW - 2000步态分析系统在健康成年人中针对这些新指标值的标准效度。

方法

12名健康参与者在佩戴机器人时模拟了偏瘫性中风个体表现出的四种异常步态模式。每位参与者被要求进行16次步态试验,每种异常步态模式有四个严重程度等级。使用WW - 2000中的步态分析系统和摄像机为每次步态试验记录20步。使用两个参数评估异常步态模式:从WW - 2000步态分析系统为每一步计算的指标值,以及评估者对每一步的严重程度评分。使用Spearman等级相关系数评估每位参与者每种步态模式下两种方法之间指标值的相关性。

结果

12名参与者中,使用WW - 2000步态分析系统计算的指标值与评估者对前躯干倾斜、患侧过度躯干偏移、膝关节过度屈曲和摆动困难的严重程度评分之间的Spearman等级相关系数的中位数(最小值至最大值)分别为0.892(0.749 - 0.969)、0.859(0.439 - 0.923)、0.920(0.738 - 0.969)和0.681(0.391 - 0.889)。

讨论

WW - 2000步态分析系统除了能有效捕捉之前验证的九种异常步态模式外,还能高度有效地捕捉在偏瘫性中风个体中观察到的四种新的异常步态模式。评估异常步态模式很重要,因为改善这些模式有助于中风康复。

临床试验注册

https://jrct.niph.go.jp,标识符jRCT 042190109。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc88/12133724/b7359b70a9c5/fnbot-19-1558009-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验