A fast EMG-based algorithm for upper-limb motion intention detection by using Levant's differentiators
Electromyography (EMG) signals are widely used for predicting human movement intention in the operation of robotic assistive devices that improve the quality of people's lives with motor problems. One of the current challenges controlling such devices is achieving a natural interaction between...
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| Veröffentlicht in: | IEEE access 2022, Vol.10, p.1-1 |
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| creator | Uribe, Mayumi Hori Vazquez, Carlos Renato Antelis, Javier M. |
| description | Electromyography (EMG) signals are widely used for predicting human movement intention in the operation of robotic assistive devices that improve the quality of people's lives with motor problems. One of the current challenges controlling such devices is achieving a natural interaction between the device and the user. However, the most common algorithms applied in motion detection exhibit a slow time response. In this work, we propose the use of robust differentiator algorithms to extract features from EMG signals that allow a fast detection of movement intention. Experimental results show that by using robust differentiator algorithms, we can significantly reduce the latency between the detection movement intention and the real movement, without losing accuracy. |
| doi_str_mv | 10.1109/ACCESS.2022.3214531 |
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| subjects | Algorithms Classification algorithms Decoding Decoding motion intention Delays Detectors Differentiators Electromyography Electromyography (EMG) Feature extraction Human motion Motion detection Motion perception Robots Robustness Sliding mode control Sliding Mode Control (SMC) Time response |
| title | A fast EMG-based algorithm for upper-limb motion intention detection by using Levant's differentiators |
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