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The contaminated electrocardiography (ECG) is a big problem in the surface electromyography (SEMG) signal detection and analysis. The objective of the current study is to propose and validate an algorithm for the automated feature cognition and identification for eliminating ECG artifact from the raw SEMG signals. The utilization of Independent Component Analysis (ICA) method is to decompose the raw...
Traditional hand gesture identification systems require designers to use multiple serial interfaces or multiplexer as tools to record surface Electromyography (sEMG). These ways lead to complicated circuit connection and unreliability of hardware. It is therefore imperative to have good methods to explore a more suitable design choice, which can avoid the problems mentioned above as more as possible...
This paper has experimentally verified and compared features of sEMG (Surface Electromyogram) such as ICA (Independent Component Analysis) and Fractal Dimension (FD) for identification of low level forearm muscle activities. The fractal dimension was used as a feature as reported in the literature. The normalized feature values were used as training and testing vectors for an artificial neural network...
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