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采用气溶胶喷射印刷技术开发可穿戴肌电图传感器。

Development of a Wearable Electromyographic Sensor with Aerosol Jet Printing Technology.

作者信息

Perilli Stefano, Di Pietro Massimo, Mantini Emanuele, Regazzetti Martina, Kiper Pawel, Galliani Francesco, Panella Massimo, Mantini Dante

机构信息

Department of Information Engineering, Electronics and Telecommunications, University of Rome "La Sapienza", 00184 Rome, Italy.

Comec Innovative s.r.l., Via Papa Leone XIII 34, 66100 Chieti, Italy.

出版信息

Bioengineering (Basel). 2024 Dec 17;11(12):1283. doi: 10.3390/bioengineering11121283.

DOI:10.3390/bioengineering11121283
PMID:39768101
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11673101/
Abstract

Electromyographic (EMG) sensors are essential tools for analyzing muscle activity, but traditional designs often face challenges such as motion artifacts, signal variability, and limited wearability. This study introduces a novel EMG sensor fabricated using Aerosol Jet Printing (AJP) technology that addresses these limitations with a focus on precision, flexibility, and stability. The innovative sensor design minimizes air interposition at the skin-electrode interface, thereby reducing variability and improving signal quality. AJP enables the precise deposition of conductive materials onto flexible substrates, achieving a thinner and more conformable sensor that enhances user comfort and wearability. Performance testing compared the novel sensor to commercially available alternatives, highlighting its superior impedance stability across frequencies, even under mechanical stress. Physiological validation on a human participant confirmed the sensor's ability to accurately capture muscle activity during rest and voluntary contractions, with clear differentiation between low and high activity states. The findings highlight the sensor's potential for diverse applications, such as clinical diagnostics, rehabilitation, and sports performance monitoring. This work establishes AJP technology as a novel approach for designing wearable EMG sensors, providing a pathway for further advancements in miniaturization, strain-insensitive designs, and real-world deployment. Future research will explore optimization for broader applications and larger populations.

摘要

肌电图(EMG)传感器是分析肌肉活动的重要工具,但传统设计常常面临诸如运动伪影、信号变异性和可穿戴性有限等挑战。本研究介绍了一种采用气溶胶喷射印刷(AJP)技术制造的新型EMG传感器,该传感器通过专注于精度、灵活性和稳定性来解决这些限制。创新的传感器设计将皮肤-电极界面处的空气介入降至最低,从而减少变异性并提高信号质量。AJP能够将导电材料精确地沉积在柔性基板上,实现更薄且更贴合的传感器,从而提高用户舒适度和可穿戴性。性能测试将新型传感器与市售替代品进行了比较,突出了其在不同频率下,甚至在机械应力下都具有卓越的阻抗稳定性。对一名人类受试者的生理验证证实了该传感器能够在休息和自主收缩期间准确捕捉肌肉活动,并且能够清晰区分低活动状态和高活动状态。研究结果突出了该传感器在临床诊断、康复和运动表现监测等多种应用中的潜力。这项工作将AJP技术确立为设计可穿戴EMG传感器的一种新方法,为在小型化、应变不敏感设计和实际应用方面的进一步发展提供了一条途径。未来的研究将探索针对更广泛应用和更大人群的优化方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/73ee3cd7fcbc/bioengineering-11-01283-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/665a3c717583/bioengineering-11-01283-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/e094e4638c9d/bioengineering-11-01283-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/b6db1c190aaa/bioengineering-11-01283-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/d5b2f5c055f4/bioengineering-11-01283-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/73ee3cd7fcbc/bioengineering-11-01283-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/665a3c717583/bioengineering-11-01283-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/f2300dfed7d7/bioengineering-11-01283-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/b37d8c6bc615/bioengineering-11-01283-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/715e6da1c268/bioengineering-11-01283-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/e094e4638c9d/bioengineering-11-01283-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/b6db1c190aaa/bioengineering-11-01283-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/d5b2f5c055f4/bioengineering-11-01283-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77f2/11673101/73ee3cd7fcbc/bioengineering-11-01283-g008.jpg

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本文引用的文献

1
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2
Biometric From Surface Electromyogram (sEMG): Feasibility of User Verification and Identification Based on Gesture Recognition.基于表面肌电图(sEMG)的生物特征识别:基于手势识别的用户验证与识别可行性
Front Bioeng Biotechnol. 2020 Feb 14;8:58. doi: 10.3389/fbioe.2020.00058. eCollection 2020.
3
Hand Gesture Recognition Using Compact CNN Via Surface Electromyography Signals.
Front Robot AI. 2025 May 2;12:1492275. doi: 10.3389/frobt.2025.1492275. eCollection 2025.
基于表面肌电信号的紧凑型卷积神经网络手势识别
Sensors (Basel). 2020 Jan 26;20(3):672. doi: 10.3390/s20030672.
4
Gesture recognition by instantaneous surface EMG images.基于瞬时表面肌电图图像的手势识别。
Sci Rep. 2016 Nov 15;6:36571. doi: 10.1038/srep36571.
5
Stretchable Multichannel Electromyography Sensor Array Covering Large Area for Controlling Home Electronics with Distinguishable Signals from Multiple Muscles.可拉伸多通道肌电图传感器阵列,可覆盖大面积,用于控制家用电器,可从多个肌肉中获得可区分的信号。
ACS Appl Mater Interfaces. 2016 Aug 17;8(32):21070-6. doi: 10.1021/acsami.6b05025. Epub 2016 Aug 8.
6
Stimulation map for control of functional grasp based on multi-channel EMG recordings.基于多通道肌电图记录的功能性抓握控制刺激图谱。
Med Eng Phys. 2016 Nov;38(11):1251-1259. doi: 10.1016/j.medengphy.2016.06.004. Epub 2016 Jun 25.
7
Investigating the possible effect of electrode support structure on motion artifact in wearable bioelectric signal monitoring.研究电极支撑结构对可穿戴生物电信号监测中运动伪影的可能影响。
Biomed Eng Online. 2015 May 15;14:44. doi: 10.1186/s12938-015-0044-2.
8
Changes in the electrical properties of the electrode-skin-underlying tissue composite during a week-long programme of neuromuscular electrical stimulation.电极-皮肤-下组织复合材料在为期一周的神经肌肉电刺激计划中电性能的变化。
Physiol Meas. 2014 Feb;35(2):231-52. doi: 10.1088/0967-3334/35/2/231. Epub 2014 Jan 16.
9
High-density surface EMG maps from upper-arm and forearm muscles.上肢和前臂肌肉的高密度表面肌电图图谱。
J Neuroeng Rehabil. 2012 Dec 10;9:85. doi: 10.1186/1743-0003-9-85.
10
Hand motion classification using a multi-channel surface electromyography sensor.使用多通道表面肌电图传感器进行手部运动分类。
Sensors (Basel). 2012;12(2):1130-47. doi: 10.3390/s120201130. Epub 2012 Jan 30.