Zhang Hongyu, Wang Keer, Suo Jiao, Cheng Clio Yuen Man, Chen Meng, Lai King Wai Chiu, Or Calvin Kalun, Hu Yong, Roy Vellaisamy A L, Lam Cindy Lo Kuen, Xi Ning, Lou Vivian W Q, Li Wen Jung
Department of Mechanical Engineering, City University of Hong Kong, Hong Kong 999077, China.
Department of Social Work and Social Administration; Sau Po Centre on Ageing, The University of Hong Kong, Hong Kong 999077, China.
ACS Sens. 2025 Aug 22;10(8):5484-5494. doi: 10.1021/acssensors.4c03379. Epub 2025 Jul 24.
Muscle function and composition are important indicators of age-related health. However, current assessment methods are often complex and expensive, making the early detection of related problems difficult. Therefore, developing a cost-effective and easily accessible daily based detection method is an essential research focus. This study introduces a novel portable porous-structured (i.e., CNT/PDMS nanocomposite) and flexible piezoresistive sensor for evaluating muscle function and relative skeletal muscle mass index, offering advantages of cost-effectiveness, safety, and user-friendliness. The porous architecture significantly enhances sensitivity, while the flexible design ensures excellent conformability to the skin and adaptability to complex body movements. The prototype sensor demonstrates a linear detection range of 0-39 kPa with dual-stage sensitivities of 0.03398 kPa (0-7 kPa) and 0.000922 kPa (7-39 kPa). The sensor maintains stable performance for over a week and exhibits reliable operation unaffected by body temperature or perspiration, and the material cost does not exceed 10 HKD. The gait data can be easily collected by wearing the sensor on the left gastrocnemius muscle. Our study encompassed 23 participants from both the elderly and young age groups. The supervised learning achieved a maximum accuracy of 93.48% in distinguishing between the elderly and the young subjects. Unsupervised learning analysis further validated the efficacy of our flexible sensor in muscle function assessment. Additionally, an Adaboost regression model was employed to predict the relative skeletal muscle mass index, achieving a mean error of 2.8%. This flexible sensor demonstrates significant potential for the daily monitoring of muscle function and mass, enabling early detection and prevention of sarcopenia and other muscle-related disorders. Its wearable and noninvasive characteristics make it an attractive solution for muscle assessment in clinical, sports, and home environments.
肌肉功能和组成是与年龄相关健康状况的重要指标。然而，目前的评估方法通常复杂且昂贵，使得相关问题的早期检测变得困难。因此，开发一种经济高效且易于获取的日常检测方法是一项重要的研究重点。本研究引入了一种新型便携式多孔结构（即碳纳米管/聚二甲基硅氧烷纳米复合材料）且灵活的压阻式传感器，用于评估肌肉功能和相对骨骼肌质量指数，具有成本效益高、安全且用户友好的优点。多孔结构显著提高了灵敏度，而灵活的设计确保了对皮肤的出色贴合性以及对复杂身体运动的适应性。该原型传感器的线性检测范围为0 - 39 kPa，具有0.03398 kPa（0 - 7 kPa）和0.000922 kPa（7 - 39 kPa）的双阶段灵敏度。该传感器在一周多的时间内保持稳定性能，并且不受体温或汗液影响，表现出可靠的运行，材料成本不超过10港元。通过将传感器佩戴在左腓肠肌上，可以轻松收集步态数据。我们的研究涵盖了23名来自老年和青年年龄组的参与者。监督学习在区分老年人和年轻人受试者方面达到了93.48%的最高准确率。无监督学习分析进一步验证了我们的柔性传感器在肌肉功能评估中的有效性。此外，采用了Adaboost回归模型来预测相对骨骼肌质量指数，平均误差为2.8%。这种柔性传感器在肌肉功能和质量的日常监测方面显示出巨大潜力，能够早期检测和预防肌肉减少症及其他与肌肉相关的疾病。其可穿戴和非侵入性的特点使其成为临床、运动和家庭环境中肌肉评估的有吸引力的解决方案。
