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Efficient Data Compression of ECG Signal Based on Modified Discrete Cosine Transform

Computers, Materials & Continua 2022年第6期71卷 4391-4408页

作者： Ashraf Mohamed Ali Hassan Mohammed S.Alzaidi Sherif S.M.Ghoneim waleed el nahal electronics and Communications Engineering Department Faculty of EngineeringSinai UniversityArishCO 45511Egypt Department of electrical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia Faculty of Technology and Education Suez UniversitySuez43527Egypt electronics and Communications Engineering Department Faculty of EngineeringMSA UniversityCO 12585Egypt

This paper introduced an efficient compression technique that uses the compressive sensing(CS)method to obtain and recover sparse electrocardiography(ECG)*** recovery of the signal can be achieved by using sampling rates lower than the Nyquist frequency.A novel analysis was proposed in this *** apply CS on ECG signal,the first step is to generate a sparse signal,which can be obtained using Modified Discrete Cosine Transform(MDCT)on the given *** transformation is a promising key for other transformations used in this search domain and can be considered as the main contribution of this paper.A small number of wavelet components can describe the ECG signal as related work to obtain a sparse *** technique for ECGsignal compression,which is a novel area of research,is *** signals are introduced randomly between any successive beats of the ***-BIH database can be represented as the experimental database in this domain of ***-BIH database consists of various ECG signals involving a patient and standard ECG *** can be considered as the simulation tool used in this *** proposed method’s uniqueness was inspired by the compression ratio(CR)and achieved by *** performance measurement of the recovered signal was done by calculating the percentage root mean difference(PRD),mean square error(MSE),and peak signal to noise ratio(PSNR)besides the calculation of ***,the simulation results indicated that this work is one of the most important works in ECG signal compression.

关键词： Compressive sensing sparse beats of hearts compression ratio percentage root mean difference

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Robust and High Accuracy Algorithm for Detection of Pupil Images

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Computers, Materials & Continua 2022年第10期73卷 33-50页

作者： waleed el nahal Hatim G.Zaini Raghad H.Zaini Sherif S.M.Ghoneim Ashraf Mohamed Ali Hassan electronics and Communications Engineering Department Faculty of EngineeringMSA UniversityCO12585Egypt Computer Engineering Department College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia Faculty of Health and Rehabilitation Sciences Princess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia Department of electrical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia electronics and Communications Engineering Department Faculty of EngineeringSinai UniversityArishCO45511Egypt

Recently,many researchers have tried to develop a robust,fast,and accurate *** algorithm is for eye-tracking and detecting pupil position in many applications such as head-mounted eye tracking,gaze-based human-computer interaction,medical applications(such as deaf and diabetes patients),and attention *** real-world conditions challenge the eye appearance,such as illumination,reflections,and *** the other hand,individual differences in eye physiology and other sources of noise,such as contact lenses or *** present work introduces a robust pupil detection algorithm with and higher accuracy than the previous attempts for real-time analytics *** proposed circular hough transform with morphing canny edge detection for Pupillometery(CHMCEP)algorithm can detect even the blurred or noisy images by using different filtering methods in the pre-processing or start phase to remove the blur and noise and finally the second filtering process before the circular Hough transform for the center fitting to make sure better *** performance of the proposed CHMCEP algorithm was tested against recent pupil detection *** and results show that the proposed CHMCEP algorithm achieved detection rates of 87.11,78.54,58,and 78 according to´Swirski,ExCuSe,else,and labeled pupils in the wild(LPW)data sets,*** results show that the proposed approach performs better than the other pupil detection methods by a large margin by providing exact and robust pupil positions on challenging ordinary eye pictures.

关键词： Pupil detection eye tracking pupil edge morphing techniques eye images dataset

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