Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/15485
Title: Gabor Filter-Based One-Dimensional Local Phase Descriptors for Obstructive Sleep Apnea Detection Using Single-Lead ECG
Authors: Kumar, T. Sunil
Kanhangad, Vivek
Keywords: 1-D local phase quantization;electrocardiograph (ECG) classification;obstructive sleep apnea;one-dimensional (1-D) local phase patterns;Sensor signals processing
Issue Date: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Kumar, T. S., & Kanhangad, V. (2018). Gabor Filter-Based One-Dimensional Local Phase Descriptors for Obstructive Sleep Apnea Detection Using Single-Lead ECG. IEEE Sensors Letters, 2(1), 1–4. https://doi.org/10.1109/LSENS.2018.2807584
Abstract: Obstructive sleep apnea (OSA) is a sleep disorder that causes abnormal and periodic breath interruptions during sleep. In this article, we present a novel one-dimensional (1-D) phase descriptor (PD) based methodology for single-lead electrocardiograph (ECG) based OSA detection. Specifically, we introduce two 1-D local PDs, referred to as 1-D local phase patterns and 1-D local phase quantization, and study their discriminative ability for OSA detection. Essentially, these PDs are computed using phase information extracted from the ECG signal. In our approach, PDs extracted from the Gabor filter phase responses are used to form the feature vector, which is utilized by a least-squares support vector machine (LS-SVM) for classification. Experimental evaluations on Physionet single-lead ECG dataset suggest that the proposed approach achieves state-of-the-art performance for OSA detection. Specifically, the proposed OSA detection approach achieves an average classification accuracy of 93.31 on ECG signals of 1-min duration, thereby providing a considerable improvement over the existing methods. © 2017 IEEE.
URI: https://doi.org/10.1109/LSENS.2018.2807584
https://dspace.iiti.ac.in/handle/123456789/15485
ISSN: 2475-1472
Type of Material: Journal Article
Appears in Collections:Department of Electrical Engineering

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