Multi

Big data and cloud computing are propelling research in human-computer interface within academia. However, the potential of wearable human-machine interaction (HMI) devices utilizing multiperformance ionic hydrogels remains largely unexplored. Here, we present a motion recognition-based HMI system that enhances movement training. We engineered dual-network PAM/CMC/TA (PCT) hydrogels by reinforcing polyacrylamide (PAM) and sodium carboxymethyl cellulose (CMC) polymers with tannic acid (TA). These hydrogels possess exceptional transparency, adhesion, and remodelling features. By combining an elastic PAM backbone with tunable amounts of CMC and TA, the PCT hydrogels achieve optimal electromechanical performance. As strain sensors, they demonstrate higher sensitivity (GF = 4.03), low detection limit (0.5 %), and good linearity (0.997). Furthermore, we developed a highly accurate (97.85 %) motion recognition system using machine learning and hydrogel-based wearable sensors. This system enables contactless real-time training monitoring and wireless control of trolley operations. Our research underscores the effectiveness of PCT hydrogels for real-time HMI, thus advancing next-generation HMI systems.

中文翻译：

大数据和云计算正在推动学术界对人机界面的研究。然而，利用多功能离子水凝胶的可穿戴人机交互（HMI）设备的潜力仍未得到充分开发。在这里，我们提出了一种基于运动识别的 HMI 系统，可以增强运动训练。我们通过用单宁酸（TA）增强聚丙烯酰胺（PAM）和羧甲基纤维素钠（CMC）聚合物来设计双网络PAM/CMC/TA（PCT）水凝胶。这些水凝胶具有卓越的透明度、附着力和重塑特性。通过将弹性 PAM 主链与可调节数量的 CMC 和 TA 相结合，PCT 水凝胶实现了最佳的机电性能。作为应变传感器，它们具有较高的灵敏度 (GF = 4.03)、较低的检测限 (0.5 %) 和良好的线性度 (0.997)。此外，我们利用机器学习和基于水凝胶的可穿戴传感器开发了高精度 (97.85%) 运动识别系统。该系统可实现非接触式实时训练监控和手推车操作的无线控制。我们的研究强调了 PCT 水凝胶对于实时 HMI 的有效性，从而推进了下一代 HMI 系统。