Med Biol Eng Comput - Adaptive motion artefact reduction in respiration and ECG signals for wearable healthcare monitoring systems.

Tópicos

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Resumo

Wearable healthcare monitoring systems (WHMSs) have received significant interest from both academia and industry with the advantage of non-intrusive and ambulatory monitoring. The aim of this paper is to investigate the use of an adaptive filter to reduce motion artefact (MA) in physiological signals acquired by WHMSs. In our study, a WHMS is used to acquire ECG, respiration and triaxial accelerometer (ACC) signals during incremental treadmill and cycle ergometry exercises. With these signals, performances of adaptive MA cancellation are evaluated in both respiration and ECG signals. To achieve effective and robust MA cancellation, three axial outputs of the ACC are employed to estimate the MA by a bank of gradient adaptive Laguerre lattice (GALL) filter, and the outputs of the GALL filters are further combined with time-varying weights determined by a Kalman filter. The results show that for the respiratory signals, MA component can be reduced and signal quality can be improved effectively (the power ratio between the MA-corrupted respiratory signal and the adaptive filtered signal was 1.31 in running condition, and the corresponding signal quality was improved from 0.77 to 0.96). Combination of the GALL and Kalman filters can achieve robust MA cancellation without supervised selection of the reference axis from the ACC. For ECG, the MA component can also be reduced by adaptive filtering. The signal quality, however, could not be improved substantially just by the adaptive filter with the ACC outputs as the reference signals.

Resumo Limpo

wearabl healthcar monitor system whmss receiv signific interest academia industri advantag nonintrus ambulatori monitor aim paper investig use adapt filter reduc motion artefact ma physiolog signal acquir whmss studi whms use acquir ecg respir triaxial acceleromet acc signal increment treadmil cycl ergometri exercis signal perform adapt ma cancel evalu respir ecg signal achiev effect robust ma cancel three axial output acc employ estim ma bank gradient adapt laguerr lattic gall filter output gall filter combin timevari weight determin kalman filter result show respiratori signal ma compon can reduc signal qualiti can improv effect power ratio macorrupt respiratori signal adapt filter signal run condit correspond signal qualiti improv combin gall kalman filter can achiev robust ma cancel without supervis select refer axi acc ecg ma compon can also reduc adapt filter signal qualiti howev improv substanti just adapt filter acc output refer signal

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