A real-time adaptive filtering approach to motion artefacts removal from ECG signals

Motion artefacts represent a severe problem in Electrocardiogram (ECG) monitoring using portable devices, as they may overlap the characteristic ECG waveforms. In this study, an adaptive filtering technique for artefacts removal is investigated. The adopted approach exploits motion-related information coming from an accelerometer attached on the ECG electrode. The experimental results indicate that adaptive filtering technique removes a large amount of motion artefacts with a decreased number of beat detection errors, making our approach a useful pre-processing scheme for ECG analysis. The developed system, implemented on a commercial microcontroller, verified real-time requirements, hence resulting suitably for portable monitoring devices.

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