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Authors: Peng Wu 1 ; Dongmei Jiang 2 and Hichem Sahli 3

Affiliations: 1 Vrije Universiteit Brussel (VUB), Belgium ; 2 Northwestern Polytechnical University (NPU), China ; 3 Vrije Universiteit Brussel (VUB) and Interuniversity Microelectronics Centre (IMEC), Belgium

Keyword(s): Signal Denoising, QRS Detection, Electromyography Segmentation.

Related Ontology Subjects/Areas/Topics: Affective Computing ; Applications ; Biomedical Engineering ; Biomedical Signal Processing ; Biosignal Acquisition, Analysis and Processing ; Devices ; Health Information Systems ; Human-Computer Interaction ; Methodologies and Methods ; Physiological Computing Systems ; Wearable Sensors and Systems

Abstract: This paper introduces new approaches of physiological signal processing prior to feature extraction from electrocardiogram (ECG) and electromyography (EMG). Firstly a new signal denoising approach based on the Empirical mode decomposition (EMD) is presented. The EMD can decompose the noisy signal into a number of Intrinsic Mode Functions (IMFs). The proposed algorithm estimates the noise level of each IMF. Experiments show that the proposed EMD-based method provides better denoising results compared to state-of-art. In addition, a real-time QRS detection approach is proposed to be directly applied on the noisy ECG signals. Moreover, an adaptive thresholding approach is employed for the EMG segmentation. Both approaches are validated using synthetic and real physiological data resulting in good performances.

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Paper citation in several formats:
Wu, P.; Jiang, D. and Sahli, H. (2014). Physiological Signal Processing for Emotional Feature Extraction. In Proceedings of the International Conference on Physiological Computing Systems - PhyCS; ISBN 978-989-758-006-2; ISSN 2184-321X, SciTePress, pages 40-47. DOI: 10.5220/0004727500400047

@conference{phycs14,
author={Peng Wu. and Dongmei Jiang. and Hichem Sahli.},
title={Physiological Signal Processing for Emotional Feature Extraction},
booktitle={Proceedings of the International Conference on Physiological Computing Systems - PhyCS},
year={2014},
pages={40-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004727500400047},
isbn={978-989-758-006-2},
issn={2184-321X},
}

TY - CONF

JO - Proceedings of the International Conference on Physiological Computing Systems - PhyCS
TI - Physiological Signal Processing for Emotional Feature Extraction
SN - 978-989-758-006-2
IS - 2184-321X
AU - Wu, P.
AU - Jiang, D.
AU - Sahli, H.
PY - 2014
SP - 40
EP - 47
DO - 10.5220/0004727500400047
PB - SciTePress

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