Time–frequency localization using three-tap biorthogonal wavelet filter bank for electrocardiogram compressions

Kumar, Ashish; Komaragiri, Rama; Kumar, Manjeet

doi:10.1007/s13534-019-00117-9

Cited by 18 publications

(4 citation statements)

References 18 publications

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“…A single-channel EEG signal was segmented into 30-s epochs, which served as input to the HMM algorithm [ 61 ]; further, the frequency band powers of these epochs were calculated after being filtered using wavelet transform [ 49 , 62 , 63 ] (Wake: 35–50 Hz, REM: 20–30 Hz, Light: 10.15–15.75 Hz and Deep: 1–3 Hz). There are three parameters for the HMM algorithm, which are an initial probability (

), a transition matrix ( Q ), and an emission matrix ( R ).…”

Section: Methodsmentioning

confidence: 99%

Effect of an Inflatable Air Mattress with Variable Rigidity on Sleep Quality

Shin

Kim

et al. 2020

Sensors

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Several studies, wherein the structure or rigidity of a mattress was varied, have been conducted to improve sleep quality. These studies investigated the effect of variation in the surface characteristics of mattresses on sleep quality. The present study developed a mattress whose rigidity can be varied by controlling the amount of air in its air cells. To investigate the effect of the variable rigidity of the air mattress on sleep quality, participants (Male, Age: 23.9 ± 2.74, BMI: 23.3 ± 1.60) were instructed to sleep on the air mattress under different conditions, and their sleep quality was subjectively and objectively investigated. Subjectively, sleep quality is assessed based on the participants’ evaluations of the depth and length of their sleep. Objectively, sleep is estimated using the sleep stage information obtained by analysing the movements and brain waves of the participants during their sleep. A subjective assessment of the sleep quality demonstrates that the participants’ sleep was worse with the adjustment of the air mattress than that without; however, the objective sleep quality results demonstrates an improvement in the sleep quality when the rigidity of the air mattress is varied based on the participant’s preference. This paper proposes a design for mattresses that can result in more efficient sleep than that provided by traditional mattresses.

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), a transition matrix ( Q ), and an emission matrix ( R ).…”

Section: Methodsmentioning

confidence: 99%

Effect of an Inflatable Air Mattress with Variable Rigidity on Sleep Quality

Shin

Kim

et al. 2020

Sensors

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“…A long-term ECG monitoring requires a large memory to store and transmit raw ECG data. Therefore, data compression makes an efficient transmission with large bandwidth 23,32 . Using the high-level transformations, a combined system can be developed which performs detection and data compression with minimal hardware.…”

Section: Synthesis Results Of Folded Glrt the Novelty Of The Paper Fmentioning

confidence: 99%

Area efficient folded undecimator based ECG detector

Uma

Kalpana

2021

Sci Rep

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This paper presents an area-efficient folded wavelet filter-based Electrocardiogram (ECG) detector for cardiac pacemakers. The modified folded undecimator based detector consists of Wavelet Filter Bank, QRS complex detector with Generalized Likelihood Ratio Test (GLRT) block and noise detector. A high-level transformation technique such as folding transformation and Cutset retiming are applied to the GLRT block in order to reduce the silicon area. Folding is a high-level transformation applied at the architectural level to enhance the performance of DSP architectures. It reduces the number of adders, multipliers and delay elements in the architecture. The Cutset retiming reduces clock period of the architecture by changing position of delay elements in the critical path. The folding transformation and cutset retiming implement the functional blocks of the GLRT circuit with minimum hardware. The modified folded ECG detector is tested for short term and long-term MIT-BIH databases. The results show that the modified folded undecimator detector has hardware savings and achieves sensitivity of 99.95%, positive prediction of 99.97% and Detection Error Rate (DER) of 0.061. The folded GLRT block architecture is synthesized with FPGA Zed board XC7Z010CLG484-1. Results show that the device utilization and power consumption are lesser than the conventional GLRT structure.

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“…In this section, the proposed method is implemented and simulated using Matlab® R2019a. ECG signals from different databases, like MIT-BIH database, PTB diagnostic ECG database, Fantasia database, LTST database, and QT database, are used to evaluate the performance of the proposed design (Kumar et al 2018(Kumar et al , 2019a(Kumar et al , 2019b. All the ECG records of each dataset described earlier have been utilized to evaluate the performance of the proposed method.…”

Section: Performance Resultsmentioning

confidence: 99%

“…The performance of the proposed method is evaluated using compression ratio (CR), compressed signal-to-noise ratio (CSNR), root-mean-square error (RMSE) (Das and Ari 2013, Kumar et al 2019a, 2019b, maximum absolute error (MAE), percentage root-mean-square difference (PRD), and quality score (QS) which are defined in Eqs. (1) to (6).…”

Section: Methodsmentioning

confidence: 99%

A robust digital ECG signal watermarking and compression using biorthogonal wavelet transform

et al. 2020

Self Cite

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Purpose With the advent of the technological era, the complexity of data security and privacy has gained utmost importance. People are becoming more conscious about the security and confidentiality of their crucial information. Methods The present study is first of its kind effort in for safeguarding an individual's electrocardiogram (ECG) data. ECG data not only does hold medical significance but also is of crucial and critical importance for purposes related to biometric information. Hence, a deciding factor for recognizing and validating personal information. The study progresses and proposes a new technique in ECG watermarking compression. Results This method ensures high reliability of data and information with confidentiality. The efficiency of the proposed research is evaluated in terms of compression ratio (CR), compressed signal-to-noise-ratio (CSNR), root-mean-square error (RMSE), maximum absolute error, percentage root-mean-square difference (PRD), and quality score. Conclusion After a comprehensive evaluation, the final results show that the proposed work is robust and feasible.

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Time–frequency localization using three-tap biorthogonal wavelet filter bank for electrocardiogram compressions

Cited by 18 publications

References 18 publications

Effect of an Inflatable Air Mattress with Variable Rigidity on Sleep Quality

Effect of an Inflatable Air Mattress with Variable Rigidity on Sleep Quality

Area efficient folded undecimator based ECG detector

A robust digital ECG signal watermarking and compression using biorthogonal wavelet transform

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