Wearable Smart Band for American Sign Language Recognition with Polymer Carbon Nanocomposite based Pressure Sensors

Conventional camera-based systems and electronic gloves for gesture recognition are limited by the influence of lighting conditions, occlusions, and movement restrictions. A wearable smart band with integrated nanocomposite pressure sensors has been developed to overcome these shortcomings. The sensors consist of homogeneously dispersed carbon nanotubes in a polydimethylsiloxane polymer matrix prepared by an optimized synthesis process. The sensor band can actively monitor contractions/relaxations of muscles in the arm due to the sensor high sensitivity in the low forces and stability. The band has 8 sensors placed on a stretchable, adhesive textile material and connected to a data logger with a multiplexed sensor interface and wireless communication capabilities. The novel smart band was validated by measurements on 10 subjects to perform numerical gestures in American Sign Language from 0 to 9 with 10 trials each. The data were recorded at 100 Hz and a total of 100 data sets were generated for each subject. By feeding the data sets to an extreme machine learning algorithm that selects features, weights, and biases to classify the gestures, an overall gesture recognition accuracy of 93% could be achieved.