Evidence map›Paper›PMID 41661410›Full record

ArticleAnnals of biomedical engineering2026

Analyzing Muscle Contraction Dynamics Through Continuous Vector Segmentation and Tracking.

Wenze Wu, Wenyu Chen, Liuhe Li, Junnan Feng, Zhe Liu, Wei Gu, Lin Gao, Jiankang He, Dichen Li

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Article in Annals of biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Wenze WuState Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
Wenyu ChenState Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
Liuhe LiState Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
Junnan FengState Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
Zhe LiuState Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
Wei GuSchool of Nursing, Health Science Center, Xi'an Jiaotong University, No.76 Yanta West Road, Xi'an, Shaanxi, 710061, China.
Lin GaoState Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China. gaolin2013@xjtu.edu.cn.
Jiankang HeState Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
Dichen LiState Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.

Funding

National Natural Science Foundation of China 52175276Program for Innovation Team of Shaanxi Province 2023-CX-TD-17
6 · The paper itself

Abstract

purposeMuscle tissues are core components of biohybrid robots. However, the lack of in-depth contraction dynamics analysis of muscle tissues affects their control and actuation methods, which in turn limits their performance. We aim to develop a new approach to explore muscle contraction properties to provide a reference and foundation for the control and actuation of muscle tissues.

methodsWe proposed a method using continuous vector sets (a sequence of vectors connected end-to-end) to characterize the flexible contraction properties of muscles on both of the overall and regional contraction. Based on this, we carried out electrical stimulation experiments on muscle tissues.

results(1) We found a nonlinear three-stage fatigue response of the muscle tissues under prolonged electric field stimulation with a significant performance degradation point (192 s at 1 Hz stimulation). (2) We investigated the effects of different parameters such as duty cycle, baseline voltage, and waveform on the contraction dynamics of the muscle tissues. We found that the muscle is highly sensitive to changes in electrical signals and could produce two different contraction behaviors within a single stimulation cycle under the appropriate duty cycle (14.5-85.5% at 1 Hz frequency). (3) We found significant regional response capability of muscle tissues under unsaturated external electric fields. The difference in contractile strain of the same region within the muscle was up to about 10% under different stimulus electric fields.

conclusionWe believe that this study provides a reference for the optimization of control strategies for biohybrid robots and is expected to offer the possibility of programmable muscle contraction behavior for further engineering applications.

Indexed as

Models, BiologicalMuscle ContractionMuscle, SkeletalAnimalsElectric StimulationElectrical stimulationIn vitro muscle tissuesMuscle contraction dynamicsMuscle contraction measurement

Identifiers

PMID41661410

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