Wavelet-Based Low-Delay ECG Compression Algorithm for Continuous ECG Transmission

Kim, B.S.; Yoo, Sun Kook; Lee, Moon Hyoung

doi:10.1109/titb.2005.856854

Cited by 70 publications

(31 citation statements)

References 14 publications

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“…The first three methods have poor CR and the PRD performance. The Kim's method [14] had the similar CR but showed higher PRD, because the transformation compression method produces some reconstruction distortions. The Fira's method [27] also used the two-step compression algorithm, skeleton, and the LZW.…”

Section: A Ecg Compression Coding Performancementioning

confidence: 99%

“…The ECG signal can be divided into a crucial part and a plain part [14]. The QRS complex wave is the most important part of the cardiology system to determine arrhythmia [13].…”

Section: A Skeleton Of Ecg Datamentioning

confidence: 99%

“…in comparison with the plain part [14]. The complex block with high STD has more crucial information than the plain block with low STD.…”

Section: A Skeleton Of Ecg Datamentioning

confidence: 99%

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ECG Signal Compression and Classification Algorithm With Quad Level Vector for ECG Holter System

Kim

Yazıcıoğlu

Merken

et al. 2010

IEEE Trans. Inform. Technol. Biomed.

122

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Abstract-An ECG signal processing method with quad level vector (QLV) is proposed for the ECG holter system. The ECG processing consists of the compression flow and the classification flow, and the QLV is proposed for both flows to achieve better performance with low-computation complexity. The compression algorithm is performed by using ECG skeleton and the Huffman coding. Unit block size optimization, adaptive threshold adjustment, and 4-bit-wise Huffman coding methods are applied to reduce the processing cost while maintaining the signal quality. The heartbeat segmentation and the R-peak detection methods are employed for the classification algorithm. The performance is evaluated by using the Massachusetts Institute of Technology-Boston's Beth Israel Hospital Arrhythmia Database, and the noise robust test is also performed for the reliability of the algorithm. Its average compression ratio is 16.9:1 with 0.641% percentage root mean square difference value and the encoding rate is 6.4 kbps. The accuracy performance of the R-peak detection is 100% without noise and 95.63% at the worst case with −10-dB SNR noise. The overall processing cost is reduced by 45.3% with the proposed compression techniques.

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Section: A Ecg Compression Coding Performancementioning

confidence: 99%

“…The ECG signal can be divided into a crucial part and a plain part [14]. The QRS complex wave is the most important part of the cardiology system to determine arrhythmia [13].…”

Section: A Skeleton Of Ecg Datamentioning

confidence: 99%

See 1 more Smart Citation

ECG Signal Compression and Classification Algorithm With Quad Level Vector for ECG Holter System

Kim

Yazıcıoğlu

Merken

et al. 2010

IEEE Trans. Inform. Technol. Biomed.

122

View full text Add to dashboard Cite

show abstract

“…However, the ECG signal has a great amount of redundant data as some of its main features such as the QRS complex are used for many diagnoses procedures. There are many algorithms that compress ECG signal in the range of 20:1 ratio [27,28]. Hence, with the proposed algorithm, it is possible to embed real ECG signal records of a patient (1-4 min) in his/her medical images.…”

Section: Performance Of the Watermarking Algorithmmentioning

confidence: 99%

A contextual based double watermarking of PET images by patient ID and ECG signal

Nambakhsh

Ahmadian

Zaidi

2011

Computer Methods and Programs in Biomedicine

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Abstractc o m p u t e r m e t h o d s a n d p r o g r a m s i n b i o m e d i c i n e 1 0 4 ( 2 0 1 1 ) [418][419][420][421][422][423][424][425] j o u r n a l h o m e p a g e : w w w . i n t l . e l s e v i e r h e a l t h . c o m / j o u r n a l s / c m p b A contextual based double watermarking of PET images by patient ID and ECG signal a b s t r a c tThis paper presents a novel digital watermarking framework using electrocardiograph (ECG) and demographic text data as double watermarks. It protects patient medical information and prevents mismatching diagnostic information. The watermarks are embedded in selected texture regions of a PET image using multi-resolution wavelet decomposition.Experimental results show that modifications in these locations are visually imperceptible. The robustness of the watermarks is verified through measurement of peak signal to noise ratio (PSNR), cross-correlation (CC%), structural similarity measure (SSIM) and universal image quality index (UIQI). Their robustness is also computed using pixel-based metrics and human visual system metrics. Additionally, beta factor (ˇ) as an edge preservation measure is used for degradation evaluation of the image boundaries throughout the watermarked PET image. Assessment of the extracted watermarks shows watermarking robustness to common attacks such as embedded zero-tree wavelet (EZW) compression and median filtering.© 2010 Elsevier Ireland Ltd. All rights reserved. IntroductionThe huge amounts of acquired digital medical images in hospitals are usually stored in a database along with the demographic text data and the bio-signals of patients. Unauthorized tampering, mismatching and mishandling of information are problems with such data in large databases. Additionally, exchange of bio-signals, demographic texts and medical images between hospitals needs efficient and reliable transmission and storage techniques. Moreover, storing different information of a patient in separate files increases the risk of mismatching and diagnostic mistakes. Unauthorized * Corresponding author. viewing of patients' healthcare information is one of the main concerns in hospital information systems. Recently, watermarking has been an active area of research for strengthening healthcare information security. Generally, watermarking algorithms have been aimed to protect digital images by hiding information into them. The main advantage of watermarking is information invisibility and anonymity. Authentication is considered a genuine application for them. A large number of watermarking techniques for medical images are available in literature which almost most of them focus on two areas, namely, tamper detection and authentication, and electronic patient record (EPR) embedding in medical images. Significantly, embedding of EPR or metadata 0169-2607/$ -see front matter

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“…More recently, transform-based methods have demonstrated their superiority in compressing EGC signals, converting the signal to another representation more suitable to detect and remove the redundancies. Among them, the wavelet transforms [15,25,13] have been extensively used because of their properties of good location in time and frequency domains. Nowadays a new paradigm, namely Compressed Sensing (CS), has 15 gained increasing attention, having proven its effectiveness [16,14].…”

Section: Introductionmentioning

confidence: 99%

High-rate compression of ECG signals by an accuracy-driven sparsity model relying on natural basis

Grossi

Lanzarotti

Lin

2015

Digital Signal Processing

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Long duration recordings of ECG signals require high compression ratios, in particular when storing on portable devices. Most of the ECG compression methods in literature are based on wavelet transform while only few of them rely on sparsity promotion models. In this paper we propose a novel ECG signal compression framework based on sparse representation using a set of ECG segments as natural basis. This approach exploits the signal regularity, i.e. the repetition of common patterns, in order to achieve high compression ratio (CR). We apply k-LiMapS as finetuned sparsity solver algorithm guaranteeing the required signal reconstruction quality (PRD). Extensive experiments of our method and of four competitors (namely ARLE, Rajoub, SPIHT, TRE) have been conducted on all the 48 records of MIT-BIH Arrhythmia Database. Our method achieves average performances that are 3 times higher than the competitor results. In particular the compression ratio gap between our method and the others increases with the PRD growing.

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Wavelet-Based Low-Delay ECG Compression Algorithm for Continuous ECG Transmission

Cited by 70 publications

References 14 publications

ECG Signal Compression and Classification Algorithm With Quad Level Vector for ECG Holter System

ECG Signal Compression and Classification Algorithm With Quad Level Vector for ECG Holter System

A contextual based double watermarking of PET images by patient ID and ECG signal

High-rate compression of ECG signals by an accuracy-driven sparsity model relying on natural basis

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