Adaptive Sampling of the Electrocardiogram Based on Generalized Perceptual Features
AGH University of Science and Technology, 30-059 Krakow, Poland
Sensors 2020, 20(2), 373; https://doi.org/10.3390/s20020373
Received: 19 November 2019
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Revised: 30 December 2019
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Accepted: 7 January 2020
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Published: 9 January 2020
(This article belongs to the Special Issue Sensors, Signal and Image Processing in Biomedicine and Assisted Living)
A non-uniform distribution of diagnostic information in the electrocardiogram (ECG) has been commonly accepted and is the background to several compression, denoising and watermarking methods. Gaze tracking is a widely recognized method for identification of an observer’s preferences and interest areas. The statistics of experts’ scanpaths were found to be a convenient quantitative estimate of medical information density for each particular component (i.e., wave) of the ECG record. In this paper we propose the application of generalized perceptual features to control the adaptive sampling of a digital ECG. Firstly, based on temporal distribution of the information density, local ECG bandwidth is estimated and projected to the actual positions of components in heartbeat representation. Next, the local sampling frequency is calculated pointwise and the ECG is adaptively low-pass filtered in all simultaneous channels. Finally, sample values are interpolated at new time positions forming a non-uniform time series. In evaluation of perceptual sampling, an inverse transform was used for the reconstruction of regularly sampled ECG with a percent root-mean-square difference (PRD) error of 3–5% (for compression ratios 3.0–4.7, respectively). Nevertheless, tests performed with the use of the CSE Database show good reproducibility of ECG diagnostic features, within the IEC 60601-2-25:2015 requirements, thanks to the occurrence of distortions in less relevant parts of the cardiac cycle.
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Keywords:
visual perception; electrocardiogram (ECG) coder; non-uniform sampling; telecardiology; compressed sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Augustyniak, P. Adaptive Sampling of the Electrocardiogram Based on Generalized Perceptual Features. Sensors 2020, 20, 373. https://doi.org/10.3390/s20020373
AMA Style
Augustyniak P. Adaptive Sampling of the Electrocardiogram Based on Generalized Perceptual Features. Sensors. 2020; 20(2):373. https://doi.org/10.3390/s20020373
Chicago/Turabian StyleAugustyniak, Piotr. 2020. "Adaptive Sampling of the Electrocardiogram Based on Generalized Perceptual Features" Sensors 20, no. 2: 373. https://doi.org/10.3390/s20020373
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