Self-Adhesive, Anti-Freezing MXene-Based Hydrogel Strain Sensor for Motion Monitoring and Handwriting Recognition with Deep Learning

Flexible strain sensors based onself-adhesive, high-tensile,super-sensitiveconductive hydrogels have promising application in human-computerinteraction and motion monitoring. Traditional strain sensors havedifficulty in balancing mechanical strength, detection function, andsensitivity, which brings challenges to their practical applications.In this work, the double network hydrogel composed of polyacrylamide(PAM) and sodium alginate (SA) was prepared, and MXene and sucrosewere used as conductive materials and network reinforcing materials,respectively. Sucrose can effectively enhance the mechanical performanceof the hydrogels and improve the ability to withstand harsh conditions.The hydrogel strain sensor has excellent tensile properties (strain>2500%), high sensitivity with a gauge factor of 3.76 at 1400%strain,reliable repeatability, self-adhesion, and anti-freezing ability.Highly sensitive hydrogels can be assembled into motion detectionsensors that can distinguish between various strong or subtle movementsof the human body, such as joint flexion and throat vibration. Inaddition, the sensor can be applied in handwriting recognition ofEnglish letters by using the fully convolutional network (FCN) algorithmand achieved the high accuracy of 98.1% for handwriting recognition.The as-prepared hydrogel strain sensor has broad prospect in motiondetection and human-machine interaction, which provides greatpotential application of flexible wearable devices.