Multi-functional MXene/helical multi-walled carbon nanotubes flexible sensor for tire pressure detection and speech recognition enabled by machine learning

Flexible sensors exhibit exceptional mechanical adaptability, enabling them to accommodate diverse operational settings. They seamlessly conform to the deformation requirements of the human body or irregular object surfaces and have found extensive applications in human motion tracking, tire pressure monitoring, and human–computer interactions. Here, we have prepared a sandwich-structured MXene/helical multi-walled carbon nanotubes (Hs-MWCNTs) flexible strain sensor. The fabricated sensor has a wide detection range (0–77 %), high sensitivity (gauge factor 243.6 at 70–77 % strain), reliable repeatability (over 35000 s), and other excellent sensing performance. MXene/Hs-MWCNTs flexible strain sensor has significant advantages in detecting tiny signals such as human pulse and tire pressure. The constructed 4 × 4 flexible sensing arrays can achieve pressure distribution detection of objects with different shapes. In addition, based on MXene/Hs-MWCNTs flexible strain sensor and continuous wavelet transform convolutional neural network algorithms, speech recognition of some English words is successfully achieved with a recognition accuracy of 94.4 %. The results indicate that MXene/Hs-MWCNTs flexible strain sensor has great potential for application in fields such as human motion detection, health monitoring and speech recognition.