Combination of EEMD and morphological filtering for baseline wander correction in EMG signals
This paper aims at proposing an effective method for Baseline Wander removal from the EMG signals. Ensemble Empirical Mode Decomposition (EEMD) Algorithm is first applied to the baseline corrupted EMG signals to decompose them into Intrinsic Mode Functions (IMFs). After this step, morphological filt...
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| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/81818/ http://dx.doi.org/10.1007/978-981-10-4280-5_38 |
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| Summary: | This paper aims at proposing an effective method for Baseline Wander removal from the EMG signals. Ensemble Empirical Mode Decomposition (EEMD) Algorithm is first applied to the baseline corrupted EMG signals to decompose them into Intrinsic Mode Functions (IMFs). After this step, morphological filtering employing octagon-shaped structuring element has been applied to filter out each IMF. Finally, the results of the proposed filtering methodology are compared with those of EMD- and EEMD-based filtering methods. Simulation results report that the methodology used in this study has eliminated the baseline wander from EMG signals with minimal distortions. |
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