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Motion artefact removal in electroencephalography and electrocardiography by using multichannel inertial measurement units and adaptive filtering

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posted on 09.07.2021, 16:08 by Christopher BeachChristopher Beach, Mingjie Li, Ertan Balaban, Alex CassonAlex Casson
This paper presents a new active electrode design for electroencephalogram (EEG) and electrocardiogram (ECG) sensors based on inertial measurement units to remove motion artefacts during signal acquisition. Rather than measuring motion data from a single source for the entire recording unit, inertial measurement units are attached to each individual EEG or ECG electrode to collect local movement data. This data is then used to remove the motion artefact by using normalised least mean square adaptive filtering. Results show that the proposed active electrode design can reduce motion contamination from EEG and ECG signals in chest movement and head swinging motion scenarios. However, it is found that the performance varies, necessitating the need for the algorithm to be paired with more sophisticated signal processing to identify scenarios where it is beneficial in terms of improving signal quality. The new instrumentation hardware allows data driven artefact removal to be performed, providing a new data driven approach compared to widely used blind-source separation methods, and helps enable in the wild EEG recordings to be performed.

Funding

Passively Powered Non-invasive Human Body Sensing on Bio-Degradable Conformal Substrates

Engineering and Physical Sciences Research Council

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MultiSense - Devising and Manufacturing mm-Wave High Data Rate Low Latency On-Skin Technologies

Engineering and Physical Sciences Research Council

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History

Email Address of Submitting Author

christopher.beach@manchester.ac.uk

ORCID of Submitting Author

0000-0003-4964-3173

Submitting Author's Institution

The University of Manchester

Submitting Author's Country

United Kingdom