Evidence map›Paper›PMID 42356813›Full record

ArticleSensors (Basel, Switzerland)2026

Comparison of Neuromuscular Control Characteristics in Forehand Stroke Between International- and National-Level Squash Players: An sEMG-Based Analysis of Muscle Synergy and Intermuscular Coherence.

Hao Zhang, Bingnan Wang, Jiao Tong, Yanan Shen

Abstract readComparative Study
In one paragraph

Article in Sensors (Basel, Switzerland), 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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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

4 authors.

Hao ZhangDepartment of P.E., Central South University, Changsha 410083, China.
Bingnan WangDepartment of P.E., Central South University, Changsha 410083, China.
Jiao TongDepartment of P.E., Central South University, Changsha 410083, China.
Yanan ShenDepartment of P.E., Central South University, Changsha 410083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to compare the neuromuscular control characteristics of international- and national-level squash players during forehand strokes using a multichannel surface electromyography (sEMG)-based sensing framework. By integrating wearable biosignal acquisition with muscle synergy and intermuscular coherence analyses, this study sought to identify sensor-derived markers of performance-related neuromuscular control and to provide evidence for sensor-informed squash training and athlete monitoring.

methodsParticipants performed standardized forehand strokes, during which multichannel sEMG signals were synchronously collected from major upper-limb, lower-limb, and trunk muscles. The recorded sensor signals were preprocessed and analyzed using non-negative matrix factorization to extract muscle synergies, including the number of synergies, muscle weightings, and synergy activation durations. In addition, time-frequency intermuscular coherence analysis was performed on the sEMG sensor data to quantify coherence differences in the α, β, and γ frequency bands between upper-limb-trunk and lower-limb-trunk muscle pairs.

resultsNo significant difference was found between the two groups in the number of muscle synergies, with both groups clustering into four synergy modules. However, the sEMG sensor-based analysis revealed clear between-group differences in synergy structure and coordination patterns. International-level players showed higher muscle weightings in major proximal muscles, including the deltoid, pectoralis major, erector spinae, and gluteus maximus, and lower weightings in relatively smaller or more distal muscles such as the biceps brachii and lateral gastrocnemius. In terms of synergy timing, international-level players exhibited significantly shorter activation durations in SYN1 and SYN2, but a significantly longer activation duration in SYN3, than national-level players. For intermuscular coherence, international-level players showed significantly lower coherence in the α, β, and γ bands for multiple upper-limb-trunk and lower-limb-trunk muscle pairs.

conclusionsA multichannel sEMG sensing approach was effective in detecting performance-level differences in neuromuscular control during the squash forehand stroke. International-level players exhibited more efficient and refined neuromuscular coordination, characterized by optimized proximal muscle recruitment, more task-specific synergy timing, and reduced intermuscular coherence across selected muscle pairs. These findings highlight the value of wearable EMG sensors and sensor-based neuromuscular feature extraction for quantitative athlete assessment, movement monitoring, and the development of sensor-guided training strategies in squash.

Indexed as

ElectromyographyMuscle, SkeletalRacquet SportsAdultAthletesHumansMaleUpper ExtremityYoung Adultathlete monitoringbiosignal sensingintermuscular coherencemuscle synergyneuromuscular controlsports biomechanicssquashsurface electromyographywearable sensors

Identifiers

PMID42356813
PMCPMC13306439

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.