High-Accuracy Hand Gesture Recognition on the Wrist Tendon Group Using Pneumatic Mechanomyography (pMMG)
Hand gesture recognition has received considerable attention as an intuitive interaction method in recent years. This research introduces a new wearable hand gesture recognition system that employs pneumatic mechanomyography (pMMG) to directly monitor the wrist tendon group, which transmits muscle f...
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| Veröffentlicht in: | IEEE transactions on industrial informatics 2024-02, Vol.20 (2), p.1550-1561 |
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| creator | An, Seongbin Feng, Jirou Song, Eunseok Kong, Kyoungchul Kim, Jung Choi, Hyunjin |
| description | Hand gesture recognition has received considerable attention as an intuitive interaction method in recent years. This research introduces a new wearable hand gesture recognition system that employs pneumatic mechanomyography (pMMG) to directly monitor the wrist tendon group, which transmits muscle force to the fingers. The experimental findings demonstrate that the proposed method provides raw observations proportional to the finger flexion force, with high R -squared values exceeding 0.94. The performance of the proposed system was evaluated by conducting a hand gesture experiment consisting of 28 hand gestures. The proposed method achieved an average accuracy of 98.12%, surpassing the surface electromyography (sEMG) system's accuracy of 93.89%. Furthermore, the fusion of pMMG and sEMG sensors yielded an accuracy of 99.18%. The results suggest that the proposed approach exhibits the potential to enhance the accuracy and efficiency of hand gesture recognition systems. |
| doi_str_mv | 10.1109/TII.2023.3280312 |
| format | Article |
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This research introduces a new wearable hand gesture recognition system that employs pneumatic mechanomyography (pMMG) to directly monitor the wrist tendon group, which transmits muscle force to the fingers. The experimental findings demonstrate that the proposed method provides raw observations proportional to the finger flexion force, with high R -squared values exceeding 0.94. The performance of the proposed system was evaluated by conducting a hand gesture experiment consisting of 28 hand gestures. The proposed method achieved an average accuracy of 98.12%, surpassing the surface electromyography (sEMG) system's accuracy of 93.89%. Furthermore, the fusion of pMMG and sEMG sensors yielded an accuracy of 99.18%. 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| subjects | Electromyography Fingers Force Gesture recognition Hand (anatomy) human–computer interaction (HCI) Joints Muscles pneumatic mechanomyography (pMMG) sensor fusion Sensors Tendons Wrist |
| title | High-Accuracy Hand Gesture Recognition on the Wrist Tendon Group Using Pneumatic Mechanomyography (pMMG) |
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