Personalized rehabilitation training provides maximum help to stroke patients to alleviate the after-effects and restore the body to normal function. However, available monitoring devices have the disadvantages of being large, requiring professional guidance, and lacking intuitive signal display capabilities. Herein, a bio-inspired wearable high-performance strain sensor with a simple structure can simultaneous electrical signals and optical visualization in response to external stimuli. The sensor comprises a conductive layer with significant electromechanical behaviors of cellulose nanocrystals (CNC)/carbon nanotubes (CNTs)/MXene nanohybrid network, and a stretchable elastomer layer consisting of thermoplastic polyurethane and fluorescent agent. Benefiting from the designed microcracks and fluorescent material, the strain sensor exhibits ultra-high sensitivity (476800), ultra-low detection limit (0.005%), low response time (60 ms), wide working range (0–100%), and enables strain visualization for applications in visually rehabilitation training monitoring. Based on these sensing characteristics, the sensor shows great advantages in human motion and sound monitoring, the integration of digital signals and visual images makes it show great potential in visually personalized rehabilitation training monitoring.

个性化的康复训练为中风患者减轻后遗症、恢复身体正常功能提供最大限度的帮助。然而，现有的监测设备存在体积大、需要专业指导、缺乏直观的信号显示能力等缺点。这里，一种结构简单的仿生可穿戴高性能应变传感器可以同时响应外部刺激而产生电信号和光学可视化。该传感器包括具有显着机电行为的纤维素纳米晶体（CNC）/碳纳米管（CNT）/MXene纳米混合网络的导电层，以及由热塑性聚氨酯和荧光剂组成的可拉伸弹性体层。得益于设计的微裂纹和荧光材料，应变传感器具有超高灵敏度（476800）、超低检测限（0.005%）、低响应时间（60 ms）、宽工作范围（0–100%）和为视觉康复训练监测应用提供应变可视化。基于这些传感特性，传感器在人体运动和声音监测方面显示出巨大的优势，数字信号与视觉图像的融合使其在视觉个性化康复训练监测方面显示出巨大的潜力。