Triboelectric Bending Sensors for AI-Enabled Sign Language Recognition.

ABSTRACT: Human-machine interfaces and wearable electronics, as fundamentals to achieve human-machine interactions, are becoming increasingly essential in the era of the Internet of Things. However, contemporary wearable sensors based on resistive and capacitive mechanisms demand an external power, impeding them from extensive and diverse deployment. Herein, a smart wearable system is developed encompassing five arch-structured self-powered triboelectric sensors, a five-channel data acquisition unit to collect finger bending signals, and an artificial intelligence (AI) methodology, specifically a long short-term memory (LSTM) network, to recognize signal patterns. A slider-crank mechanism that precisely controls the bending angle is designed to quantitively assess the sensor's performance. Thirty si

SUBMITTER: Wang W 

PROVIDER: S-EPMC11848593 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature