Rescio Gabriele, Sciurti Elisa, Giampetruzzi Lucia, Carluccio Anna Maria, Francioso Luca, Leone Alessandro
Institute for Microelectronics and Microsystems, National Research Council of Italy, 73100 Lecce, Italy.
Sensors (Basel). 2025 Mar 6;25(5):1618. doi: 10.3390/s25051618.
Surface electromyography (sEMG) is increasingly important for prevention, diagnosis, and rehabilitation in healthcare. The continuous monitoring of muscle electrical activity enables the detection of abnormal events, but existing sEMG systems often rely on disposable pre-gelled electrodes that can cause skin irritation and require precise placement by trained personnel. Wearable sEMG systems integrating textile electrodes have been proposed to improve usability; however, they often suffer from poor skin-electrode coupling, leading to higher impedance, motion artifacts, and reduced signal quality. To address these limitations, we propose a preliminary model of smart socks, integrating biocompatible hybrid polymer electrodes positioned over the target muscles. Compared with commercial Ag/AgCl electrodes, these hybrid electrodes ensure lower the skin-electrode impedance, enhancing signal acquisition (19.2 ± 3.1 kΩ vs. 27.8 ± 4.5 kΩ for Ag/AgCl electrodes). Moreover, to the best of our knowledge, this is the first wearable system incorporating hydrogel-based electrodes in a sock specifically designed for the analysis of lower limb muscles, which are crucial for evaluating conditions such as sarcopenia, fall risk, and gait anomalies. The system incorporates a lightweight, wireless commercial module for data pre-processing and transmission. sEMG signals from the Gastrocnemius and Tibialis muscles were analyzed, demonstrating a strong correlation (R = 0.87) between signals acquired with the smart socks and those obtained using commercial Ag/AgCl electrodes. Future studies will further validate its long-term performance under real-world conditions and with a larger dataset.
表面肌电图（sEMG）在医疗保健的预防、诊断和康复方面正变得越来越重要。对肌肉电活动的持续监测能够检测异常事件，但现有的sEMG系统通常依赖一次性预凝胶电极，这种电极会引起皮肤刺激，并且需要训练有素的人员进行精确放置。已有人提出集成纺织电极的可穿戴sEMG系统来提高可用性；然而，它们往往存在皮肤与电极耦合不佳的问题，导致阻抗更高、运动伪影以及信号质量下降。为了解决这些限制，我们提出了一种智能袜子的初步模型，该模型集成了位于目标肌肉上方的生物相容性混合聚合物电极。与商用Ag/AgCl电极相比，这些混合电极可确保降低皮肤与电极之间的阻抗，增强信号采集（Ag/AgCl电极的阻抗为27.8±4.5kΩ，而混合电极的阻抗为19.2±3.1kΩ）。此外，据我们所知，这是首个在专为分析下肢肌肉而设计的袜子中纳入水凝胶基电极的可穿戴系统，下肢肌肉对于评估诸如肌肉减少症、跌倒风险和步态异常等状况至关重要。该系统集成了一个用于数据预处理和传输的轻量级无线商用模块。对腓肠肌和胫骨前肌的sEMG信号进行了分析，结果表明智能袜子采集的信号与使用商用Ag/AgCl电极获得的信号之间存在很强的相关性（R = 0.87）。未来的研究将在实际条件下并使用更大的数据集进一步验证其长期性能。
