access icon openaccess Effective automated method for detection and suppression of muscle artefacts from single-channel EEG signal

This Letter proposes an automated method for the detection and suppression of muscle artefacts (MAs) in the single-channel electroencephalogram (EEG) signal based on variational mode decomposition (VMD) and zero crossings count threshold criterion without the use of reference electromyogram (EMG). The proposed method involves three major steps: decomposition of the input EEG signal into two modes using VMD; detection of MAs based on zero crossings count thresholding in the second mode; retention of the first mode as MAs-free EEG signal only after detection of MAs in the second mode. The authors evaluate the robustness of the proposed method on a variety of EEG and EMG signals taken from publicly available databases, including Mendeley database, epileptic Bonn database and EEG during mental arithmetic tasks database (EEGMAT). Evaluation results using different objective performance metrics depict the superiority of the proposed method as compared to existing methods while preserving the clinical features of the reconstructed EEG signal.

Inspec keywords: electromyography; electroencephalography; medical signal processing

Other keywords: reconstructed EEG signal; reference electromyogram; VMD; effective automated method; threshold criterion; single-channel EEG signal; muscle artefacts; input EEG signal; mental arithmetic tasks database; single-channel electroencephalogram signal; publicly available databases; MAs-free EEG signal; variational mode decomposition; epileptic Bonn database; zero crossings; EMG signals; Mendeley database

Subjects: Biology and medical computing; Electrical activity in neurophysiological processes; Electrodiagnostics and other electrical measurement techniques; Other topics in statistics; Digital signal processing; Signal processing and detection; Bioelectric signals

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