Intelligent Gesture Recognition Gloves for Real-Time Monitoring in Wireless Human-Computer Interaction

Flexible sensors mimic the sensing ability of human skin, and have unique flexibility and adaptability, allowing users to interact with intelligent systems in a more natural and intimate way. To overcome the issues of low sensitivity and limited operating range of flexible strain sensors, this study presents a highly innovative preparation method to develop a conductive elastomeric sensor with a cracked thin film by combining polydimethylsiloxane (PDMS) with multiwalled carbon nanotubes (MCNT). This novel design significantly increases both the sensitivity and operating range of the sensor (strain range 0-50%; the maximum tensile sensitivity of this sensor reaches 4.97), marking a breakthrough in flexible sensor technology. The sensor can also be fabricated easily and inexpensively which is suitable for large-scale production, indicating its significant application potential. Combined with a dedicated hardware and software system, the sensors enable real-time monitoring of the finger status and accurate gesture recognition. Furthermore, machine-learning algorithms were used to identify American Sign Language gestures with an accuracy of up to 97%. This innovative human-machine interface provides important support for the future development of intelligent interactive systems, and is of great significance in promoting the progress of advanced human-computer interaction technologies.