Integrated Iontronic FMG-sEMG Sensing for Decoding Muscle Activation Mechanisms and Force Assessment.

IF 10 2区 医学 Q1 ENGINEERING, BIOMEDICAL
Peikai Zou, Junhan Wang, Xian Zhao, Xigong Zhang, Kehan Hua, Yejun Zha, Ruya Li, Yubo Fan
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引用次数: 0

Abstract

Muscle activity generates both physiological electrical and mechanical signals, the monitoring of which is crucial in rehabilitation and sports medicine, underpinning effective diagnosis, treatment, and rehabilitation processes. Advances in flexible electronics enable force myography (FMG) and surface electromyography (sEMG) signals for muscle activation monitoring, but the multi-sensor integration and physiological mechanisms underlying FMG signals remain poorly studied, limiting the accuracy of muscle function assessments and underutilizes the high sensitivity of the flexible sensors. This study introduces a novel thin-film iontronic force-electromyography (iFEMG) sensor, integrating a high-sensitivity iontronic pressure sensor and sEMG electrodes for high-fidelity muscle physiological signal acquisition. Based on ultrasound imaging and statistical analysis, the relationship between muscle force, muscle geometric features, and FMG signals is established, providing evidence for elucidating the physiological mechanisms of FMG signals. Based on these findings, an effective and highly adaptable method is proposed for precise muscle force prediction. The iFEMG system is successfully applied to assess motor nerve and muscle function in patients, demonstrating its clinical utility. This system holds significant potential for broader applications, such as rehabilitation training and early diagnosis of musculoskeletal disorders, paving the way for advanced personalized healthcare solutions.

集成离子电子FMG-sEMG传感解码肌肉激活机制和力评估。
肌肉活动产生生理电信号和机械信号,对这些信号的监测在康复和运动医学中至关重要,是有效诊断、治疗和康复过程的基础。柔性电子技术的进步使得肌力图(FMG)和肌表电图(sEMG)信号能够用于肌肉激活监测,但多传感器集成和FMG信号背后的生理机制研究仍然很少,限制了肌肉功能评估的准确性,并且没有充分利用柔性传感器的高灵敏度。本研究介绍了一种新型薄膜离子电子力肌电(iFEMG)传感器,该传感器集成了高灵敏度离子电子压力传感器和表面肌电信号电极,用于高保真的肌肉生理信号采集。基于超声成像和统计分析,建立了肌肉力量、肌肉几何特征与FMG信号之间的关系,为阐明FMG信号的生理机制提供了依据。在此基础上,提出了一种有效且适应性强的肌肉力精确预测方法。iFEMG系统成功应用于评估患者的运动神经和肌肉功能,证明了其临床应用价值。该系统具有更广泛的应用潜力,如康复训练和肌肉骨骼疾病的早期诊断,为先进的个性化医疗解决方案铺平了道路。
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来源期刊
Advanced Healthcare Materials
Advanced Healthcare Materials 工程技术-生物材料
CiteScore
14.40
自引率
3.00%
发文量
600
审稿时长
1.8 months
期刊介绍: Advanced Healthcare Materials, a distinguished member of the esteemed Advanced portfolio, has been dedicated to disseminating cutting-edge research on materials, devices, and technologies for enhancing human well-being for over ten years. As a comprehensive journal, it encompasses a wide range of disciplines such as biomaterials, biointerfaces, nanomedicine and nanotechnology, tissue engineering, and regenerative medicine.
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