Quality Assessment of ECG Compression Techniques Using a Wavelet-Based Diagnostic Measure

Abstract-This paper presents a generic programmable analog front-end (AFE) for acquisition and digitization of various biopotential signals. This includes a lead-off detection circuit, an ultra-low current capacitively coupled signal conditioning stage with programmable gain and bandwidth, a new mixed signal automatic gain control (AGC) mechanism and a medically cohesive reconfigurable Σ∆ ADC. The full system is designed in UMC 0.18µm CMOS. The AFE achieves an overall linearity of more 10 bits with 0.47µW power consumption. The ADC provides 2 nd order noise-shaping while using single integrator and an ENOB of ∼11 bits with 5µW power consumption. The system was successfully verified for various ECG signals from PTB database. This system is intended for portable batteryless u-Healthcare devices.

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“…The quality assessment of the reconstructed signal wrt. the input ECG signal is tabulated in Table III [30], [29]. As is shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

A reconfigurable medically cohesive biomedical front-end with ΣΔ ADC in 0.18µm CMOS

Jha

Patra

Naik

et al. 2015

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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“…The wavelet based distortion measures overcome the limitations in WPRD and WDD by assigning the weights through different parameters as energy and entropy. Al-Fahoum proposed an objective diagnostic distortion measure for evaluating the quality of compressed ECG signal [18]. In the wavelet domain, the clinical diagnostic features are captured through approximation and detail coefficients.…”

Section: Objective Diagnostic Distortion Measuresmentioning

confidence: 99%

Quantification of Diagnostic Information from Electrocardiogram Signal: A Review

Dandapat

Sharma

Tripathy

2015

Lecture Notes in Electrical Engineering

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Electrocardiogram (ECG) contains the information about the contraction and relaxation of heart chambers. This diagnostic information will change due to various cardiovascular diseases. This information is used by a cardiologist for accurate detection of various life-threatening cardiac disorders. ECG signals are subjected to number of processing, for computer aided detection and localization of cardiovascular diseases. These processing schemes are categorized as filtering, synthesis, compression and transmission. Quantifying diagnostic information from an ECG signal in an efficient way, is always a challenging task in the area of signal processing. This paper presents a review on state-of-art diagnostic information extraction approaches and their applications in various ECG signal processing schemes such as quality assessment and cardiac disease detection. Then, a new diagnostic measure for multilead ECG (MECG) is proposed. The proposed diagnostic measure (MSD) is defined as the difference between multivariate sample entropy values for original and processed MECG signals. The MSD measure is evaluated over MECG compression framework. Experiments are conducted over both normal and pathological MECG from PTB database. The results demonstrate that the proposed MSD measure is effective in quantifying diagnostic information in MECG. The MSD measure is also compare with other measures such as WEDD, PRD and RMSE.

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“…During evaluation of WEDD, each MECG data is wavelet decomposed at L = log 2 (F s ) − 2.96 level [17] where F s is the sampling frequency.…”

Section: Svd-based Training and Testingmentioning

confidence: 99%

SVD Analysis on Reduced 3-Lead ECG Data

Padhy

Dandapat

2015

Lecture Notes in Electrical Engineering

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This paper presents synthesis of Electrocardiogram (ECG) leads from reduced set of leads. The Singular Value Decomposition (SVD) is used to train subject-specific all desired leads for minimum of three beat periods. Then, in the testing phase, only 3-leads are used to reconstruct all other leads. The singular value matrix of the reduced 3-lead data is transformed to a higher dimension using a transform matrix. For evaluation purpose, the proposed method is applied to a publicly available database. It contains number of 12-lead ECG recordings with different cardiac patients data. After synthesis of ECG data, the performance of the method is measured using percent correlation present between the original and synthesized data.

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Quality Assessment of ECG Compression Techniques Using a Wavelet-Based Diagnostic Measure

Cited by 141 publications

References 18 publications

A reconfigurable medically cohesive biomedical front-end with ΣΔ ADC in 0.18µm CMOS

A reconfigurable medically cohesive biomedical front-end with ΣΔ ADC in 0.18µm CMOS

Quantification of Diagnostic Information from Electrocardiogram Signal: A Review

SVD Analysis on Reduced 3-Lead ECG Data

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