Wavelet denoising of the electrocardiogram signal based on the corrupted noise estimation

Chouakri, Sid Ahmed; Bereksi–Reguig, F.; Ahmaidi, Saïd; Fokapu, Odette

doi:10.1109/cic.2005.1588284

Cited by 60 publications

(35 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are various security systems evolved in the past, which work on iris [1], audio fingerprint [2], personal signatures [3] and facial features [7] to generate secret keys. The use of the electrocardiogram (ECG) signals for security key generation has also been carried out in the past years [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

DNA and Blum Blum Shub Random Number Generator Based Security Key Generation Algorithm

Sodhi¹,

Gaba²

2017

IJSIA

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

DNA and Blum Blum Shub Random Number Generator Based Security Key Generation Algorithm

Sodhi¹,

Gaba²

2017

IJSIA

View full text Add to dashboard Cite

show abstract

“…Several methods have been used to remove these artifacts: in the time-domain [4], [5], [6], [7]; in the frequency-domain [8] and in time-frequency domain [9], [10]. These methods are based on the use of digital filters.…”

Section: Introductionmentioning

confidence: 99%

Preprocessing of biomedical signals: Removing of the baseline artifacts

Khemiri

Aloui

Naceur

2013

10th International Multi-Conferences on Systems, Signals &Amp; Devices 2013 (SSD13)

View full text Add to dashboard Cite

In this paper, we propose a new preprocessing algorithm for biomedical signals to remove the baseline artifacts. The proposed algorithm is based on the least squares method. It can automatically estimate the form of the baseline artifacts and eliminate it. First, our algorithm consists in using the method of ordinary least squares (OLS) to estimate the slope of linear regression line. Then, we have developed a technique that allowed us to calculate the inclination angle. Finally, we eliminated these artifacts. To evaluate the reliability and robustness of our algorithm, we tested our method on biomedical signals from PHYSIOBANK database. The results obtained by our algorithm to remove the baseline artifacts set from 96.8% to 89.43%, whereas the results of the most common method consisting in applying a nonlinear median filter with a rectangular window are 64.2 to 52.38%.

show abstract

“…Israel et al [19] have demonstrated the viability of using cardiovascular function for human identification and proposed a set of ECG descriptors to identify individual. Chauakri et al [20] in their work presented an algorithm of filtering the noisy real ECG signal. Alfaouri and Daqrouq [21] proposed a new approach based on the threshold value of ECG signal determination using wavelet transform coefficients.…”

Section: Introductionmentioning

confidence: 99%

Generation of security key using ECG signal

Khokher¹,

Singh²

2015

International Conference on Computing, Communication &Amp; Automation

View full text Add to dashboard Cite

A system is proposed for generation of security key using R-R interval feature of electrocardiogram (ECG) signals as an input. The system provides a mechanism for verification and identification by generating a security key corresponding to an individual. The system comprises of two independent stages: registration and authentication. Biometric security key, created in the registration stage has been generated using Hamming Distance and the extended version of the triple DES algorithm. Biometric security key generation, verification, authentication and performance of the biometric security key have been assessed using R-R interval of ECG signals taken from the standard MIT-BIH database. The performance of the proposed biometric security key has been tested for the parameters like FAR, FRR, GAR, HTER and accuracy. The simulation results for 64-bit, 128-bit and 256-bit biometric security key indicate that the performance of the proposed biometric security key is reasonably good for a security system.

show abstract

Wavelet denoising of the electrocardiogram signal based on the corrupted noise estimation

Abstract: We present in this paper

Cited by 60 publications

References 13 publications

DNA and Blum Blum Shub Random Number Generator Based Security Key Generation Algorithm

DNA and Blum Blum Shub Random Number Generator Based Security Key Generation Algorithm

Preprocessing of biomedical signals: Removing of the baseline artifacts

Generation of security key using ECG signal

Contact Info

Product

Resources

About