Empirical Mode Decomposition and Wavelet Transform Based ECG Data Compression Scheme

Jha, Chandan Kumar; Kolekar, Maheshkumar H.

doi:10.1016/j.irbm.2020.05.008

Cited by 56 publications

(32 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The direct lossy compression method extracts significant temporal information. Transformation techniques result in high energy distribution in fewer coefficients [3]. Among the various transformation techniques, wavelet based compression techniques have gained significant recognition due to its high efficacy.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Among the various transformation techniques, wavelet based compression techniques have gained significant recognition due to its high efficacy. These methods are found to yield good compression and less signal distortion [3,4]. The wavelet transform using the fourth order Daubechies function achieved better performance among various wavelet functions [4].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Hardware Implementation Of ECG Signal Compression Using SPIHT

sundari

Loganathan

Sujatha

2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Cardiovascular disorder is a primary cause of mortality throughout the world in both developed and underdeveloped countries. Continuous cardiac monitoring enables clinicians to identify arrhythmias and other heart conditions. Tele-cardiology introduces remote monitoring devices for tracking the cardiac activity of the patients. The large volume of Electrocardiogram (ECG) data needs to be stored, processed and transmitted by these portable health care devices. The implementation of ECG compression in hardware platform is crucial for continuous health monitoring applications. The aim of this work is to implement field programmable gate array based set partitioning in hierarchical trees-based electrocardiogram compression. Discrete wavelet transform method is employed to break up the signal into sub bands. The transformed coefficients after discrete wavelet transform are passed through dead zone quantization which rejects low magnitude values of transformed coefficients lying around zero. These quantized coefficients are then encoded by lossless set partitioning used in hierarchical trees compression approach. The introduction of dead zone quantization in the proposed technique is found to be effective and yields an increased compression ratio of 10.33 with decreased distortion value of 1.04 percent for ECG record 117 of MIT-BIH arrhythmia database.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Hardware Implementation Of ECG Signal Compression Using SPIHT

sundari

Loganathan

Sujatha

2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…[87] insignificant delay for the compression at low level distortion of the signal. In [88], empirical mode decomposition and wavelet transformation to compress the ECG signal was discussed. [89] utilize the 2D Discrete Cosine Transform coefficient and iterative JPEG2000 encoding for compression purposes that proved efficient.…”

Section: ) Ecg Compressionmentioning

confidence: 99%

Origins of ECG and Evolution of Automated DSP Techniques: A Review

Arora¹,

Mishra

2021

IEEE Access

View full text Add to dashboard Cite

Over the years researchers have studied the evolution of Electrocardiogram (ECG) and the complex classification of cardiovascular diseases. This review focuses on the evolution of the ECG and covers the most recent signal processing schemes with milestones over the last 150 years in a systematic manner. Development phases of ECG, ECG leads, portable ECG monitors, Signal Processing schemes and Complex Transformations are discussed. This paper summarizes the development of ECG features detection for cardiac anomalies and the history of the development of ECG monitors, beginning from String Galvanometer. It also discusses the automated detections on ECG beginning from 1960 to the most recent signal processing techniques. Additionally, this paper provides recommendations.

show abstract

“…In the biomedical applications, the EMD has been used for hypertension diagnosis [20], electrocardiogram (ECG) data compression [21], emotion recognition [22], telemedicine [23] and, when combined with a deep convolutional neural network (CNN), it performs well in fast and efficient medical imaging systems [24].…”

Section: Introductionmentioning

confidence: 99%

Empirical Mode Decomposition: Theory and Applications in Underwater Acoustics

Filho

Santos

Sinezio

et al. 2022

JCIS

View full text Add to dashboard Cite

Empirical mode decomposition (EMD) is a signal processing method that produces a data-driven multiresolution representation in time-domain suited to characterize time-varying and nonlinear phenomena. In EMD, intrinsic mode functions (IMF) are sequentially estimated from the signal of interest to represent different intrinsic oscillation modes and produce an orthogonal representation of the original information. Different algorithms have been proposed for IMF estimation to deal with limitations such as mode-mixing and noise sensitivity. EMD is usually associated with the Hilbert transform to obtain a frequency-domain representation. In this case, the method is referred to as the Hilbert-Huang transform (HHT). This paper presents a theoretical review of the fundamental aspects of both EMD and HHT, such as the IMF estimation procedure. Variations of the original EMD algorithm are also presented. Both simulated and experimental underwater acoustic signals are used to illustrate the efficiency of EMD/HHT in revealing relevant characteristics from time-varying and nonlinear phenomena.

show abstract

Empirical Mode Decomposition and Wavelet Transform Based ECG Data Compression Scheme

Cited by 56 publications

References 29 publications

Hardware Implementation Of ECG Signal Compression Using SPIHT

Hardware Implementation Of ECG Signal Compression Using SPIHT

Origins of ECG and Evolution of Automated DSP Techniques: A Review

Empirical Mode Decomposition: Theory and Applications in Underwater Acoustics

Contact Info

Product

Resources

About