Data Glove for the Recognition of the Letters of the Polish Sign Language Alphabet

This article presents the results of a study on the classification of 36 letters of the Polish Sign Alphabet (PSL) using a data glove. The data glove includes a Raspberry Pi, a PCB with four 16-bit ADS1115 ADCs, and ten piezoresistive sensors. The sensors function as potentiometers that respond to finger bending. A neural network consisting of LSTM and convolutional layers was used for classification, achieving an efficiency of 99% on data from a single subject, which underwent prior augmentation. The study suggests that the device could potentially be calibrated solely from the target user. This is the first study of its kind on PSL.