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上肢意向性震颤评估:可穿戴技术的机遇与挑战。

Upper limb intention tremor assessment: opportunities and challenges in wearable technology.

机构信息

Institute for Cognitive Systems, Technical University of Munich, Arcisstraße 21, 80333, Munich, Germany.

Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany.

出版信息

J Neuroeng Rehabil. 2024 Jan 13;21(1):8. doi: 10.1186/s12984-023-01302-9.

Abstract

BACKGROUND

Tremors are involuntary rhythmic movements commonly present in neurological diseases such as Parkinson's disease, essential tremor, and multiple sclerosis. Intention tremor is a subtype associated with lesions in the cerebellum and its connected pathways, and it is a common symptom in diseases associated with cerebellar pathology. While clinicians traditionally use tests to identify tremor type and severity, recent advancements in wearable technology have provided quantifiable ways to measure movement and tremor using motion capture systems, app-based tasks and tools, and physiology-based measurements. However, quantifying intention tremor remains challenging due to its changing nature.

METHODOLOGY & RESULTS: This review examines the current state of upper limb tremor assessment technology and discusses potential directions to further develop new and existing algorithms and sensors to better quantify tremor, specifically intention tremor. A comprehensive search using PubMed and Scopus was performed using keywords related to technologies for tremor assessment. Afterward, screened results were filtered for relevance and eligibility and further classified into technology type. A total of 243 publications were selected for this review and classified according to their type: body function level: movement-based, activity level: task and tool-based, and physiology-based. Furthermore, each publication's methods, purpose, and technology are summarized in the appendix table.

CONCLUSIONS

Our survey suggests a need for more targeted tasks to evaluate intention tremors, including digitized tasks related to intentional movements, neurological and physiological measurements targeting the cerebellum and its pathways, and signal processing techniques that differentiate voluntary from involuntary movement in motion capture systems.

摘要

背景

震颤是一种不自主的有节奏运动,常见于帕金森病、特发性震颤和多发性硬化等神经系统疾病。意向性震颤是与小脑及其连接通路损伤相关的一种亚型,是与小脑病理相关疾病的常见症状。虽然临床医生传统上使用测试来识别震颤类型和严重程度,但可穿戴技术的最新进展为使用运动捕捉系统、基于应用程序的任务和工具以及基于生理学的测量来量化运动和震颤提供了定量方法。然而,由于其变化的性质,量化意向性震颤仍然具有挑战性。

方法和结果

本综述检查了上肢震颤评估技术的现状,并讨论了进一步开发新的和现有的算法和传感器以更好地量化震颤,特别是意向性震颤的潜在方向。使用与震颤评估技术相关的关键字在 PubMed 和 Scopus 上进行了全面搜索。然后,对筛选结果进行相关性和适宜性过滤,并进一步按技术类型进行分类。共有 243 篇出版物被选入本综述,并根据其类型进行分类:身体功能水平:基于运动的;活动水平:基于任务和工具的;以及基于生理学的。此外,附录表中总结了每篇出版物的方法、目的和技术。

结论

我们的调查表明,需要更有针对性的任务来评估意向性震颤,包括与意向运动相关的数字化任务、针对小脑及其通路的神经和生理学测量,以及运动捕捉系统中区分自主运动和非自主运动的信号处理技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b310/10787996/878b63c1d855/12984_2023_1302_Fig1_HTML.jpg

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