This study reports on the implementation of a novel system to detect and reduce movement artifact (MA) contribution in electrocardiogram (ECG) recordings acquired from horses in free movement conditions. The system comprises both integrated textile electrodes for ECG acquisition and one triaxial accelerometer for movement monitoring. Here, ECG and physical activity are continuously acquired from seven horses through the wearable system and a model that integrates cardiovascular and movement information to estimate the MA contribution is implemented. Moreover, in this study we propose a new algorithm where the Stationary Wavelet Transform (SWT) decomposition algorithm is employed to identify and remove movement artifacts from ECG recodigns. Achieved results showed a reduction of MA percentage greater than 40% between before- and after- the application of the proposed algorithm to seven hours of recordings.

Removing movement artifacts from equine ECG recordings acquired with textile electrodes / Lanata, Antonio; Guidi, Andrea; Baragli, Paolo; Paradiso, Rita; Valenza, Gaetano; Scilingo, Enzo Pasquale. - 2015-:(2015), pp. 1955-1958. (Intervento presentato al convegno 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 tenutosi a MiCo Center, Milano Congressi Center, ita nel 2015) [10.1109/EMBC.2015.7318767].

Removing movement artifacts from equine ECG recordings acquired with textile electrodes

Lanata, Antonio;
2015

Abstract

This study reports on the implementation of a novel system to detect and reduce movement artifact (MA) contribution in electrocardiogram (ECG) recordings acquired from horses in free movement conditions. The system comprises both integrated textile electrodes for ECG acquisition and one triaxial accelerometer for movement monitoring. Here, ECG and physical activity are continuously acquired from seven horses through the wearable system and a model that integrates cardiovascular and movement information to estimate the MA contribution is implemented. Moreover, in this study we propose a new algorithm where the Stationary Wavelet Transform (SWT) decomposition algorithm is employed to identify and remove movement artifacts from ECG recodigns. Achieved results showed a reduction of MA percentage greater than 40% between before- and after- the application of the proposed algorithm to seven hours of recordings.
2015
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
MiCo Center, Milano Congressi Center, ita
2015
Lanata, Antonio; Guidi, Andrea; Baragli, Paolo; Paradiso, Rita; Valenza, Gaetano; Scilingo, Enzo Pasquale
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1192209
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