{"title":"遗传性痉挛性截瘫的仪器步态分析的结果测量:系统回顾。","authors":"Veronika Koch, Alzhraa Ibrahim, Juergen Winkler, Bjoern Eskofier, Martin Regensburger, Heiko Gassner","doi":"10.1186/s12984-025-01646-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Hereditary spastic paraplegias (HSPs) comprise a group of genetic movement disorders characterized by progressive spasticity and weakness of the lower limbs leading to gait deficits. Instrumented gait measures are applied to quantify gait patterns in HSP objectively. However, there is no consensus on the most relevant HSP-specific digital outcome measures for future clinical studies.</p><p><strong>Aim: </strong>This systematic review aims to summarize outcome measures of instrumented gait analysis in HSP patients, focusing on both traditional motion capture (MOCAP) and inertial sensor systems.</p><p><strong>Methods: </strong>Following PRISMA-2020 guidelines, a comprehensive literature search was conducted in PubMed, Scopus, and Web of Science to identify studies using instrumented gait analysis in HSP. Data on participant characteristics, measurement systems, outcome measures, results, and risk of bias were systematically extracted.</p><p><strong>Results: </strong>In total, 38 studies published between 2004 and 2024, including 29 observational studies and 9 interventional studies, met the inclusion criteria. Various gait parameters were used, including spatio-temporal, kinematic, kinetic, and electromyography (EMG) parameters. Walking speed and range-of-motion (ROM) knee were identified as important parameters for differentiating HSP patients from healthy controls, but these parameters are more general rather than disease-specific. Foot lift, ROM foot, and gait variability are promising, more disease-specific parameters, as they reflect disease severity and increased balance deficits. However, a deeper understanding of all gait parameter categories is necessary, particularly for the upper body. Few studies explored sub-cohorts that exhibit different HSP gait characteristics.</p><p><strong>Conclusion: </strong>While MOCAP provides valuable data in controlled hospital environments, there is a need for validated mobile sensor systems capturing the gait patterns of HSP patients in real-life without supervision. Future research must focus on better longitudinal multicenter studies with larger sample sizes to establish robust digital outcomes and monitor disease progression and therapeutic response in HSP.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"129"},"PeriodicalIF":5.2000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12139076/pdf/","citationCount":"0","resultStr":"{\"title\":\"Outcome measures of instrumented gait analysis in hereditary spastic paraplegia: a systematic review.\",\"authors\":\"Veronika Koch, Alzhraa Ibrahim, Juergen Winkler, Bjoern Eskofier, Martin Regensburger, Heiko Gassner\",\"doi\":\"10.1186/s12984-025-01646-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Hereditary spastic paraplegias (HSPs) comprise a group of genetic movement disorders characterized by progressive spasticity and weakness of the lower limbs leading to gait deficits. Instrumented gait measures are applied to quantify gait patterns in HSP objectively. However, there is no consensus on the most relevant HSP-specific digital outcome measures for future clinical studies.</p><p><strong>Aim: </strong>This systematic review aims to summarize outcome measures of instrumented gait analysis in HSP patients, focusing on both traditional motion capture (MOCAP) and inertial sensor systems.</p><p><strong>Methods: </strong>Following PRISMA-2020 guidelines, a comprehensive literature search was conducted in PubMed, Scopus, and Web of Science to identify studies using instrumented gait analysis in HSP. Data on participant characteristics, measurement systems, outcome measures, results, and risk of bias were systematically extracted.</p><p><strong>Results: </strong>In total, 38 studies published between 2004 and 2024, including 29 observational studies and 9 interventional studies, met the inclusion criteria. Various gait parameters were used, including spatio-temporal, kinematic, kinetic, and electromyography (EMG) parameters. Walking speed and range-of-motion (ROM) knee were identified as important parameters for differentiating HSP patients from healthy controls, but these parameters are more general rather than disease-specific. Foot lift, ROM foot, and gait variability are promising, more disease-specific parameters, as they reflect disease severity and increased balance deficits. However, a deeper understanding of all gait parameter categories is necessary, particularly for the upper body. Few studies explored sub-cohorts that exhibit different HSP gait characteristics.</p><p><strong>Conclusion: </strong>While MOCAP provides valuable data in controlled hospital environments, there is a need for validated mobile sensor systems capturing the gait patterns of HSP patients in real-life without supervision. 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引用次数: 0
摘要
背景:遗传性痉挛性截瘫(HSPs)包括一组以进行性痉挛和下肢无力导致步态缺陷为特征的遗传性运动障碍。采用仪器步态测量客观量化HSP的步态模式。然而,对于未来临床研究中最相关的hsp特异性数字结果测量方法尚无共识。目的:本系统综述旨在总结HSP患者仪器步态分析的结果测量,重点是传统的运动捕捉(MOCAP)和惯性传感器系统。方法:根据PRISMA-2020指南,在PubMed、Scopus和Web of Science中进行了全面的文献检索,以确定在HSP中使用仪器步态分析的研究。系统地提取了参与者特征、测量系统、结局测量、结果和偏倚风险的数据。结果:2004年至2024年间共发表38项研究,包括29项观察性研究和9项介入性研究,符合纳入标准。使用了各种步态参数,包括时空、运动学、动力学和肌电图(EMG)参数。步行速度和膝关节活动度(ROM)被认为是区分HSP患者和健康对照的重要参数,但这些参数更一般,而不是疾病特异性。足部抬升、ROM足和步态变异性是有希望的,更多的疾病特异性参数,因为它们反映了疾病的严重程度和增加的平衡缺陷。然而,更深入地了解所有步态参数类别是必要的,特别是对于上半身。很少有研究探讨表现出不同热休克步态特征的亚队列。结论:虽然MOCAP在受控的医院环境中提供了有价值的数据,但仍需要经过验证的移动传感器系统来捕捉HSP患者在没有监督的现实生活中的步态模式。未来的研究必须集中在更大样本量的纵向多中心研究上,以建立可靠的数字结果,并监测HSP的疾病进展和治疗反应。
Outcome measures of instrumented gait analysis in hereditary spastic paraplegia: a systematic review.
Background: Hereditary spastic paraplegias (HSPs) comprise a group of genetic movement disorders characterized by progressive spasticity and weakness of the lower limbs leading to gait deficits. Instrumented gait measures are applied to quantify gait patterns in HSP objectively. However, there is no consensus on the most relevant HSP-specific digital outcome measures for future clinical studies.
Aim: This systematic review aims to summarize outcome measures of instrumented gait analysis in HSP patients, focusing on both traditional motion capture (MOCAP) and inertial sensor systems.
Methods: Following PRISMA-2020 guidelines, a comprehensive literature search was conducted in PubMed, Scopus, and Web of Science to identify studies using instrumented gait analysis in HSP. Data on participant characteristics, measurement systems, outcome measures, results, and risk of bias were systematically extracted.
Results: In total, 38 studies published between 2004 and 2024, including 29 observational studies and 9 interventional studies, met the inclusion criteria. Various gait parameters were used, including spatio-temporal, kinematic, kinetic, and electromyography (EMG) parameters. Walking speed and range-of-motion (ROM) knee were identified as important parameters for differentiating HSP patients from healthy controls, but these parameters are more general rather than disease-specific. Foot lift, ROM foot, and gait variability are promising, more disease-specific parameters, as they reflect disease severity and increased balance deficits. However, a deeper understanding of all gait parameter categories is necessary, particularly for the upper body. Few studies explored sub-cohorts that exhibit different HSP gait characteristics.
Conclusion: While MOCAP provides valuable data in controlled hospital environments, there is a need for validated mobile sensor systems capturing the gait patterns of HSP patients in real-life without supervision. Future research must focus on better longitudinal multicenter studies with larger sample sizes to establish robust digital outcomes and monitor disease progression and therapeutic response in HSP.
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.