The use of electromyography (EMG) for machine control in a manufacturing environment is challenging due to the inherent electrical noise, and also because machine operators lack anatomy knowledge of muscle location for electrode placement. In this research, an electrode placement scheme is proposed for this user group. An EMG preamp was constructed to observe EMG patterns in lower forearm when electrodes placed by untrained operators are in less optimal locations. Crosstalk was found to be a major issue when electrodes are placed in imperfect locations. The EMG preamplifier was deliberately constructed with low cost components to simulate the increased floor noise due to electrical interferences f however from the results, the resulting SNR is acceptable. This study shows that in designing a practical EMG input system, electrode placement is a bigger factor compared to electrical interference.
The right leg drive (RLD) is a circuit associated with electrocardiography acquisition circuits. For electromyography (EMG), the RLD circuit is used to a lesser degree. In general, the RLD circuit provides better noise reduction. This study compares the output of the EMG with and without the RLD circuit. The results indicate that with a good filter design, the direct grounding method can match the RLD in terms of noise reduction. As a result, EMG application, the RLD drive can be omitted.
The surface electromyogram (EMG) is widely studied and applied in machine control. Recent methods of classifying hand gestures reported classification rates of over 95%. However, the majority of the studies made were performed on a single user, focusing solely on the gesture classification. These studies are restrictive in practical sense: either focusing on just gestures, multi-user compatibility, or rotation independence. The variations in EMG signals due to these conditions present a challenge to the practical application of EMG devices, often requiring repetitious training per application. To the best of our knowledge, there is little comprehensive review of works done in EMG classification in the combined influence of user-independence, rotation and hand exchange. Therefore, in this paper we present a review of works related to the practical issues of EMG with a focus on the EMG placement, and recent acquisition and computing techniques to reduce training. First, we provided an overview of existing electrode placement schemes. Secondly, we compared the techniques and results of single-subject against multi-subject, multi-position settings. As a conclusion, the study of EMG classification in this direction is relatively new. However the results are encouraging and strongly indicate that EMG classification in a broad range of people and tolerance towards arm orientation is possible, and can pave way for more flexible EMG devices.
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