دورية أكاديمية
Mapping Method of Human Arm Motion Based on Surface Electromyography Signals
| العنوان: | Mapping Method of Human Arm Motion Based on Surface Electromyography Signals |
|---|---|
| المؤلفون: | Yuanyuan Zheng, Gang Zheng, Hanqi Zhang, Bochen Zhao, Peng Sun |
| المصدر: | Sensors, Vol 24, Iss 9, p 2827 (2024) |
| بيانات النشر: | MDPI AG, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Chemical technology |
| مصطلحات موضوعية: | sEMG, gesture recognition, human arm motion mapping, deep learning, Chemical technology, TP1-1185 |
| الوصف: | This paper investigates a method for precise mapping of human arm movements using sEMG signals. A multi-channel approach captures the sEMG signals, which, combined with the accurately calculated joint angles from an Inertial Measurement Unit, allows for action recognition and mapping through deep learning algorithms. Firstly, signal acquisition and processing were carried out, which involved acquiring data from various movements (hand gestures, single-degree-of-freedom joint movements, and continuous joint actions) and sensor placement. Then, interference signals were filtered out through filters, and the signals were preprocessed using normalization and moving averages to obtain sEMG signals with obvious features. Additionally, this paper constructs a hybrid network model, combining Convolutional Neural Networks and Artificial Neural Networks, and employs a multi-feature fusion algorithm to enhance the accuracy of gesture recognition. Furthermore, a nonlinear fitting between sEMG signals and joint angles was established based on a backpropagation neural network, incorporating momentum term and adaptive learning rate adjustments. Finally, based on the gesture recognition and joint angle prediction model, prosthetic arm control experiments were conducted, achieving highly accurate arm movement prediction and execution. This paper not only validates the potential application of sEMG signals in the precise control of robotic arms but also lays a solid foundation for the development of more intuitive and responsive prostheses and assistive devices. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 24092827 1424-8220 |
| Relation: | https://www.mdpi.com/1424-8220/24/9/2827; https://doaj.org/toc/1424-8220 |
| DOI: | 10.3390/s24092827 |
| URL الوصول: | https://doaj.org/article/f200f528fe3c4e3e93d646b7bab1a3bd |
| رقم الأكسشن: | edsdoj.f200f528fe3c4e3e93d646b7bab1a3bd |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 24092827 14248220 |
|---|---|
| DOI: | 10.3390/s24092827 |