Application of the Max–Lloyd quantizer for ECG compression in diving mammals

Rodríguez, María Candelaria Gil; Ayala, Alejandro; Rodriguez, Stephen; Rosa, F.; Díaz-González, Mario

doi:10.1016/s0169-2607(03)00016-6

Cited by 6 publications

(9 citation statements)

References 14 publications

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“…Therefore, very good performances are obtained: high quality of quantized ECG signal and high level of compression. Our model gives better performances compared to the model described in [1], where Lloyd-Max quantizer was used.…”

Section: Introductionmentioning

confidence: 84%

“…Measurement signals should be stored or transmitted to some distant location for further processing. Due to limited resources, the compression of the measurement signals is desirable [1]. One of the most effective techniques for signal compression is the prediction, where the prediction of the current sample is formed based on the previous samples, and after that the difference between the current sample and its prediction is quantized and transmitted.…”

Section: Introductionmentioning

confidence: 99%

“…The efficiency of the prediction depends on the degree of correlation between samples: the prediction is more effective if samples are more correlated. DPCM technique is based on the linear prediction, where the prediction of the current sample is calculated as the linear combination of previous samples [1]- [4].…”

Section: Introductionmentioning

confidence: 99%

“…Namely, the device for ECG monitoring can be mounted on the patient body, recording and transmitting ECG signal to the hospital. Therefore, in modern systems for ECG monitoring, a large amount of data should be stored or transmitted, which requires application of some compression technique [1], [7]- [10]. Due to the high correlation of ECG signal, high degree of compression can be achieved using prediction.…”

Section: Introductionmentioning

confidence: 99%

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Compression of the Highly Correlated Measurement Signals using DPCM Technique

Jocic

Perić

Dincic

et al. 2014

ElAEE

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Compression of highly correlated measurement signals is considered using DPCM/ADPCM (Difference Pulse Code Modulation/Adaptive Difference Pulse Code Modulation) technique. It is important since very often transmission and storage of measurement signals are needed. Theory is applied on ECG (Electrocardiogram) signal, as an example of highly correlated signals. Very good performances are achieved: high compression rate and high improvement of performances are obtained.

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Section: Introductionmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Compression of the Highly Correlated Measurement Signals using DPCM Technique

Jocic

Perić

Dincic

et al. 2014

ElAEE

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“…In particular, we adopt optimal quantisers obtained by the well‐known Lloyd–Max algorithm, which minimises the mean‐squared quantisation error. Lloyd–Max quantisation has been previously used in ECG compression for transmission purposes [36]. Our proposal is that a Lloyd–Max quantiser is obtained for each user after the enrolment process, and the selected heartbeat waveforms (user's model) be encoded with that user‐tuned quantiser.…”

Section: Proposed Approachesmentioning

confidence: 99%

Novel fiducial and non‐fiducial approaches to electrocardiogram‐based biometric systems

et al. 2013

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The electrocardiogram (ECG) is a non-invasive and widely used technique for cardiac electrophysiological assessment. Although the ECG has traditionally only been used for functional diagnostic and evaluation, several advances in electrophysiological sensing have made available robust signal acquisition devices, particularly suited for ambulatory conditions, widening its range of applications. In particular, recent work has shown the potential of the ECG as a biometric trait, both for human identification and authentication. This study sets the ground for an ECG-based real-time biometric system. The authors describe an experimental setup and the evaluation of new fiducial and non-fiducial approaches, including data acquisition, signal processing, feature extraction and analysis and classification methodologies, showing the applicability of the ECG as a real-time biometric. Performance evaluation was done in clinical-grade ECG recording from 51 healthy control individuals (of a publicly available benchmark dataset) as well as on data collected from 26 healthy volunteers performing computer activities without any posture or motion limitations, thus simulating a regular computer usage scenario.

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Compression of Physiological Signals

Naït‐Ali¹

2008

Compression of Biomedical Images and Signals

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Application of the Max–Lloyd quantizer for ECG compression in diving mammals

Cited by 6 publications

References 14 publications

Compression of the Highly Correlated Measurement Signals using DPCM Technique

Compression of the Highly Correlated Measurement Signals using DPCM Technique

Novel fiducial and non‐fiducial approaches to electrocardiogram‐based biometric systems

Compression of Physiological Signals

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