Automatic detection of human gait events: a simple but versatile 3D algorithm.

IF 5.2 2区 医学 Q1 ENGINEERING, BIOMEDICAL
Théo Vancanneyt, Camille Le Moal, Maxence Blard, Juliette Lenoir, Nicolas Roche, Céline Bonnyaud, Fabien Dubois
{"title":"Automatic detection of human gait events: a simple but versatile 3D algorithm.","authors":"Théo Vancanneyt, Camille Le Moal, Maxence Blard, Juliette Lenoir, Nicolas Roche, Céline Bonnyaud, Fabien Dubois","doi":"10.1186/s12984-025-01544-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Detecting Foot Strike and Foot Off events in human gait, which is cyclic yet variable, consistently requires expert correction. This subjective correction can reduce spatiotemporal parameters, joint kinematic and kinetic accuracy, regardless of the gait event detection algorithm used from the literature. Recently developed methods have combined existing algorithms to better capture this gait variability, using Ground Reaction Forces. However, those methods do not fully account for intra-individual variability, particularly in the case of multiple and simultaneous gait patterns.</p><p><strong>Method: </strong>We developed a deterministic algorithm called the Multi-Condition algorithm. This algorithm identifies the Foot Strike when the first of the foot markers loses its degrees of freedom and the Foot Off when the last of the foot markers regains its degrees of freedom.</p><p><strong>Results: </strong>This algorithm was tested on 819 C3D gait files from 9 healthy individuals and 50 individuals with stroke, multiple sclerosis, spinal cord injury, cerebral palsy, polio, neuromuscular disease or amputation. The Multi-Condition algorithm detected both Foot Strike and Foot Off within a range of three frames, which was more accurate and precise than the inter-rater variability of expert correction. Detection of gait events required only a few seconds, regardless of the pathology or gait pattern, even when considering intra-individual variability.</p><p><strong>Conclusion: </strong>Accurately identifying gait events is the first critical step in providing reliable gait analysis parameters for clinicians. The Multi-Condition algorithm aims to achieve deterministic consensus in the accurate and precise identification of gait events, regardless of the pathology or the gait pattern. To promote its adoption and ongoing testing, the Multi-Condition algorithm is available as an open-access resource.</p><p><strong>Ethical committee: </strong>The study was approved by the University of Paris-Saclay Research Ethics Committee (No. CER-Paris-Saclay-2024-35) and was performed in accordance with the Declaration of Helsinki.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"110"},"PeriodicalIF":5.2000,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12077026/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of NeuroEngineering and Rehabilitation","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1186/s12984-025-01544-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Detecting Foot Strike and Foot Off events in human gait, which is cyclic yet variable, consistently requires expert correction. This subjective correction can reduce spatiotemporal parameters, joint kinematic and kinetic accuracy, regardless of the gait event detection algorithm used from the literature. Recently developed methods have combined existing algorithms to better capture this gait variability, using Ground Reaction Forces. However, those methods do not fully account for intra-individual variability, particularly in the case of multiple and simultaneous gait patterns.

Method: We developed a deterministic algorithm called the Multi-Condition algorithm. This algorithm identifies the Foot Strike when the first of the foot markers loses its degrees of freedom and the Foot Off when the last of the foot markers regains its degrees of freedom.

Results: This algorithm was tested on 819 C3D gait files from 9 healthy individuals and 50 individuals with stroke, multiple sclerosis, spinal cord injury, cerebral palsy, polio, neuromuscular disease or amputation. The Multi-Condition algorithm detected both Foot Strike and Foot Off within a range of three frames, which was more accurate and precise than the inter-rater variability of expert correction. Detection of gait events required only a few seconds, regardless of the pathology or gait pattern, even when considering intra-individual variability.

Conclusion: Accurately identifying gait events is the first critical step in providing reliable gait analysis parameters for clinicians. The Multi-Condition algorithm aims to achieve deterministic consensus in the accurate and precise identification of gait events, regardless of the pathology or the gait pattern. To promote its adoption and ongoing testing, the Multi-Condition algorithm is available as an open-access resource.

Ethical committee: The study was approved by the University of Paris-Saclay Research Ethics Committee (No. CER-Paris-Saclay-2024-35) and was performed in accordance with the Declaration of Helsinki.

人类步态事件的自动检测:一个简单但通用的3D算法。
背景:在人类步态中检测脚撞击和脚离开事件,这是循环的,但变量,始终需要专家纠正。无论文献中使用的步态事件检测算法如何,这种主观修正都会降低时空参数、关节运动学和动力学精度。最近开发的方法结合了现有的算法,利用地面反作用力更好地捕捉这种步态变异性。然而,这些方法并不能完全解释个体内部的变异性,特别是在多种同时步态模式的情况下。方法:我们开发了一种确定性算法,称为多条件算法。当第一个脚标记失去其自由度时,该算法识别出Foot Strike,当最后一个脚标记恢复其自由度时,该算法识别出Foot Off。结果:该算法对9名健康个体和50名中风、多发性硬化症、脊髓损伤、脑瘫、脊髓灰质炎、神经肌肉疾病或截肢患者的819个C3D步态文件进行了测试。多条件算法在三帧范围内同时检测足部撞击和足部偏离,比专家校正的帧间变异性更准确和精确。步态事件的检测只需要几秒钟,无论病理或步态模式,即使考虑到个体内的变异性。结论:准确识别步态事件是为临床医生提供可靠的步态分析参数的第一步。多条件算法的目的是在准确和精确地识别步态事件时达到确定性共识,而不考虑病理或步态模式。为了促进其采用和持续测试,多条件算法可作为开放获取资源。伦理委员会:本研究已获得巴黎萨克雷大学研究伦理委员会(No. 5)批准。CER-Paris-Saclay-2024-35),并按照赫尔辛基宣言进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of NeuroEngineering and Rehabilitation
Journal of NeuroEngineering and Rehabilitation 工程技术-工程:生物医学
CiteScore
9.60
自引率
3.90%
发文量
122
审稿时长
24 months
期刊介绍: Journal of NeuroEngineering and Rehabilitation considers manuscripts on all aspects of research that result from cross-fertilization of the fields of neuroscience, biomedical engineering, and physical medicine & rehabilitation.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信