应用耦合角研究中风后上肢关节间协调性

IF 5.6 4区 医学 Q1 ENGINEERING, BIOMEDICAL
Irbm Pub Date : 2023-08-01 DOI:10.1016/j.irbm.2023.100769
S.G. Rozevink , K.A. Horstink , C.K. van der Sluis , J.M. Hijmans , A. Murgia
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引用次数: 0

摘要

目的脑卒中后关节间协调受到影响,限制了上肢的使用。目前确定关节间协调的方法缺乏可视化和量化运动的能力。因此,我们研究了耦合角是否可以用于可视化和解释中风后上肢关节间协调。方法对7例慢性脑卒中患者进行为期6周的家庭辅助训练。在检索任务中确定了运动学结果,即肘部和肩部的运动范围、运动持续时间和角度-角度图。肘关节屈曲角和肩关节外展角之间的关节间协调表示为耦合角相位和相位转换次数:近端/远端关节引导相位、同相和反相。比较两侧:测试前与测试后,两侧:受影响最大(MA)与受影响最小(LA)。结果PreMA与PreLA的肘部屈曲角度较小,PostMA与PostLA的肩部外展角度较小。LA侧显示出总体协调模式,但MA侧没有。有一种趋势显示,训练后MA一侧的相变较少,这表明运动更平稳。运动阶段的量化表明,在测试前,MA侧的肩关节受累更多。训练后,这些差异并不明显,这可能表明对肘关节的独立控制有所增强。结论耦合角和运动相位为研究脑卒中后关节间协调模式提供了一个很有前途的工具。重要的是,关节间协调的新可视化可能有利于中风幸存者的康复。注册本试验在荷兰试验登记处注册(NL7535)https://www.trialregister.nl/trial/7535.
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Application of the Coupling Angle to Investigate Upper Limb Interjoint Coordination After Stroke

Application of the Coupling Angle to Investigate Upper Limb Interjoint Coordination After Stroke

Objective

Interjoint coordination after stroke is affected, which limits the use of the upper limb. Current methods to determine interjoint coordination lack the ability to visualize and quantify the movement. Therefore we investigated if the coupling angle can be used to visualize and interpret upper limb interjoint coordination following a stroke.

Methods

Seven chronic stroke patients trained six weeks with an assistive home-training system (MERLIN). Kinematic outcomes, i.e. elbow and shoulder range of motion, movement duration, and angle-angle plots were determined in a retrieving task. Interjoint coordination between elbow flexion and shoulder abduction angles was expressed as the coupling angle phases and the number of phase transitions: proximal/distal joint leading phase, in-phase and anti-phase. Comparisons were made within sides: pre-test versus post-test, and between sides: most-affected (MA) versus least-affected (LA).

Results

Smaller elbow flexion angles were found PreMA versus PreLA, and smaller shoulder abduction angles in PostMA versus PostLA. A general coordination pattern was revealed on the LA side, but not on the MA side. A trend showed less phase transitions at the MA side after training, suggesting a smoother movement. Quantification of the movement phases indicated more involvement of the shoulder joint involvement in the MA side during pre-test. After training, these differences were not apparent, which might reveal an increased independent control of the elbow joint.

Conclusions

The coupling angle and the movement phases provide a promising tool to investigate post-stroke interjoint coordination patterns.

Significance

A new visualisation of the interjoint coordination may benefit rehabilitation of stroke survivors.

Registration

This trial was registered at the Netherlands Trial Register (NL7535) https://www.trialregister.nl/trial/7535.

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来源期刊
Irbm
Irbm ENGINEERING, BIOMEDICAL-
CiteScore
10.30
自引率
4.20%
发文量
81
审稿时长
57 days
期刊介绍: IRBM is the journal of the AGBM (Alliance for engineering in Biology an Medicine / Alliance pour le génie biologique et médical) and the SFGBM (BioMedical Engineering French Society / Société française de génie biologique médical) and the AFIB (French Association of Biomedical Engineers / Association française des ingénieurs biomédicaux). As a vehicle of information and knowledge in the field of biomedical technologies, IRBM is devoted to fundamental as well as clinical research. Biomedical engineering and use of new technologies are the cornerstones of IRBM, providing authors and users with the latest information. Its six issues per year propose reviews (state-of-the-art and current knowledge), original articles directed at fundamental research and articles focusing on biomedical engineering. All articles are submitted to peer reviewers acting as guarantors for IRBM''s scientific and medical content. The field covered by IRBM includes all the discipline of Biomedical engineering. Thereby, the type of papers published include those that cover the technological and methodological development in: -Physiological and Biological Signal processing (EEG, MEG, ECG…)- Medical Image processing- Biomechanics- Biomaterials- Medical Physics- Biophysics- Physiological and Biological Sensors- Information technologies in healthcare- Disability research- Computational physiology- …
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