AI Article Synopsis
- Gestures involve both motion (like finger movements) and force (the pressure used when interacting with objects) information.
- Current recognition methods mainly focus on motion, often overlooking force.
- A new bio-impedance wearable can identify various hand gestures using both motion and force data, achieving a remarkable average recognition accuracy of 98.96%, which is better than traditional medical electrodes at 98.05%.
Article Abstract
Gestures are composed of motion information (e.g. movements of fingers) and force information (e.g. the force exerted on fingers when interacting with other objects). Current hand gesture recognition solutions such as cameras and strain sensors primarily focus on correlating hand gestures with motion information and force information is seldom addressed. Here we propose a bio-impedance wearable that can recognize hand gestures utilizing both motion information and force information. Compared with previous impedance-based gesture recognition devices that can only recognize a few multi-degrees-of-freedom gestures, the proposed device can recognize 6 single-degree-of-freedom gestures and 20 multiple-degrees-of-freedom gestures, including 8 gestures in 2 force levels. The device uses textile electrodes, is benchmarked over a selected frequency spectrum, and uses a new drive pattern. Experimental results show that 179 kHz achieves the highest signal-to-noise ratio (SNR) and reveals the most distinct features. By analyzing the 49,920 samples from 6 participants, the device is demonstrated to have an average recognition accuracy of 98.96%. As a comparison, the medical electrodes achieved an accuracy of 98.05%.
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| http://dx.doi.org/10.1109/JBHI.2024.3417616 | DOI Listing |
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