可穿戴系统能在动态环境中操控机器人

Core Insights - A new wearable system developed by a team from the University of California, San Diego, allows users to control robotic devices using everyday hand gestures in dynamic environments such as running or driving [1][2] - The system overcomes limitations of traditional gesture sensing devices that struggle with signal distortion due to motion noise, enabling stable operation even under high-frequency vibrations and multiple interferences [1][2] Group 1 - The wearable system is designed as a soft patch attached to a fabric arm band, integrating motion and muscle sensors, a Bluetooth microcontroller, and a stretchable battery [1] - It utilizes a customized deep learning framework to capture and process signals from the arm in real-time, filtering out noise and recognizing gestures to send control commands to devices [1] Group 2 - This is the first wearable human-machine interaction system capable of stable operation under various motion disturbances, indicating broad application prospects [2] - Potential applications include enabling rehabilitation patients or individuals with mobility impairments to control assistive robots through natural gestures, and allowing industrial workers and rescue personnel to operate tools and robots in high-intensity or hazardous environments [2] - The system is also expected to enhance the reliability of gesture control in consumer electronic devices, paving the way for the development of next-generation wearable systems that are lighter, wireless, and capable of continuous learning from complex environments and user habits [2]