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An innovative image encryption algorithm enhanced with the pan-tompkins algorithm for optimal security

MULTIMEDIA TOOLS AND APPLICATIONS 2024年第35期83卷 82589-82619页

作者： Ihsan, Ayseguel Dogan, Nurettin Selcuk Univ Dept Informat Technol Engn Grad Sch Nat & Appl Sci Alaeddin Keykubat Campus TR-42075 Konya Turkiye Selcuk Univ Dept Comp Engn Fac Technol Alaeddin Keykubat Campus TR-42075 Konya Turkiye

This study introduces a cutting-edge image encryption algorithm aimed at elevating security standards. The pan-tompkins algorithm (PTA) for key generation is proposed for the first time in this study. Additionally, employing steganography through the Least Significant Bit (LSB) method for embedding keys within the encrypted image enhances secure key distribution, thereby fortifying the encryption process. On the other hand, the integration of advanced algorithms, such as Zigzag scanning, the Affine Image Encryption algorithm (AA), and the Vigenere Image Encryption algorithm (VA), constitutes the fundamental innovation of the proposed image encryption algorithm. The proposed algorithm is named panAAVA:Affine algorithm and Vigenere algorithm Encryption with PTA-Based Key Generation. The panAAVA algorithm ensures unparalleled security by encrypting the positions and values of pixels using AA and VA. Notably, using PTA for key generation marks a distinctive and new key generation method feature of the algorithm. To assess the effectiveness of the panAAVA, a comprehensive comparative analysis is conducted against well-established encryption methodologies, including Lena, Baboon, Airplane, and *** panAAVA demonstrates exceptional proficiency in histogram analysis. The panAAVA demonstrates a Unified Average Changing Intensity (UACI) of 33.4044%. Additionally, the Number of Pixels Change Rate (NPCR) is measured at 99.7442%, showcasing the algorithm's effectiveness in inducing significant pixel changes. The proposed algorithm's Mean Square Error (MSE) is calculated at 3.20679E5%. The proposed algorithm's Peak Signal to Noise Ratio (PSNR) is recorded at 9.512475. The Key Space Size of the proposed algorithm is measured at 2209. Regarding correlation analysis, the panAAVA achieves a high correlation score of 7.9996. The proposed algorithm successfully passes the National Institute of Standards and Technology (NIST) analysis, demonstrating a remarkably strong correlation

关键词： Affine Image Encryption Key Generation pan-tompkins algorithm R-peak Least Significant Bit (LSB) Vigenere

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Automated QT Interval Measurement Using Modified pan-tompkins algorithm with Independent Isoelectric Line Approach

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JOURNAL OF BIOMIMETICS BIOMATERIALS AND BIOMEDICAL ENGINEERING 2020年第1期44卷 51-61页

作者： Jumahat, Shaliza Beng, Gan Kok Misran, Norbahiah Islam, Mohammad Tariqul Mahri, Nurhafizah Ja'afar, Mohd Hasni Univ Kebangsaan Malaysia Fac Engn & Built Environm Dept Elect Elect & Syst Engn Ukm Bangi 43600 Selangor Malaysia Int Islamic Univ Malaysia Kulliyyah Informat & Commun Technol POB 10 Kuala Lumpur 50728 Malaysia Pusat Perubatan Univ Kebangsaan Malaysia Jabatan Kesihatan Masyarakat Jalan Yaacob Latif Kuala Lumpur 56000 Malaysia

The QT interval on the electrocardiogram (ECG) signal is known to have an important role in monitoring heart's electrical activity because the presence of QT interval prolongation can be associated with life-threatening cardiac events. This interval can be identified and measured using either manual or automated techniques. Currently, studies on automated QT interval measurement algorithms are becoming a growing field, as they can provide the best solution to overcome misdiagnosis and timely issues resulting from manual identification. However, the physiological variability of the QRS complex and the fluctuation of the isoelectric line are prevalent issues that need to be considered in the automatic method. In this report, an algorithm to identify the QRS onset and T-wave offset for measuring the corrected QT interval (QTc) is proposed. This method uses an improved pan-tompkins algorithm from the previous work with independent of the isoelectric line approach for detecting the QRS onset and the T offset. The algorithm was implemented in Matlab and applied to the 60 seconds duration of 27 records in the PPUKM database with a sampling frequency of 500 Hz. The performance of the algorithm achieved a sensitivity of 100% for QRS onset detection and 100% for T offset detection. As for the accuracy, the algorithm's performance obtained 100% for QRS onset detection and 99.56% for T offset detection. The mean error results with respect to manual annotation were 37 +/- 18.5 ms for QRS onset detection and 32 +/- 22.3 ms for T offset detection which was within ANSI/AAMI-EC57:1998 standard tolerance. The proposed algorithm exhibits reliable automated QTc measurement. Besides insensitive to morphological variations of ECG waves, the computational method is simple and possibly implemented as the basis for future software development for portable device applications.

关键词： Electrocardiogram Myocardial Infarction QT Interval QRS Onset T Offset pan-tompkins algorithm Automatic Measurement

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Acceptable ECG Trace Selection Based on pan-tompkins algorithm 5

Acceptable ECG Trace Selection Based on Pan-Tompkins Algorit...

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5th International Conference on Informatics, Electronics and Vision (ICIEV)

作者： Nahiyan, K. M. Talha Al-Amin, Abdullah Univ Dhaka Dept Biomed Phys & Technol Dhaka Bangladesh

ISBN: (纸本)9781509012695

In a number of ECG systems the acceptable trace is still selected manually. An able technician decides whether a trace is good enough for final selection. This process at times can be error prone. In case of telemedicine, sometimes automatic detection of the acceptable trace is necessary, as there may not be available personnel to select an acceptable trace manually. Thus an algorithm for detecting acceptable trace automatically can be a simple yet very important aspect of an ECG system in certain conditions. In this paper a method is proposed to detect an ECG acceptable trace automatically. Information on amplitude and position of QRS complexes are acquired by applying pan-tompkins algorithm and based on those a decision making algorithm is developed which compares the normalized amplitude and position index of the QRS complexes with the raw ECG signal. The analysis leads to rejecting ECG signals which deviate from isoelectric line and accepts an ECG signal for tracing only when it is free of any such deviation.

关键词： ECG trace selection pan-tompkins algorithm

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ECG Signal Acquisition for the pan-tompkins algorithm Using Current-Mirror Filters

ECG Signal Acquisition for the Pan-Tompkins Algorithm Using ...

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23rd IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Vastarouchas, Costas Kapoulea, Stavroula Psychalinos, Costas Univ Patras Dept Phys Elect Lab GR-26504 Rion Greece

ISBN: (纸本)9781509061136

Bandpass (BP) and lowpass (LP) filter topologies implemented using current-mirrors as active blocks, as well as differentiator and squarer blocks are presented in this paper, in order to perform the acquisition of electrocardiogram (ECG) signals needed for the pan-tompkins algorithm. The simple structures of the utilized blocks and the operation of MOS transistors in the subthreshold region, offer the benefit of ultra low power consumption, making the proposed scheme attractive for enhancing the battery life in portable biomedical systems.

关键词： CMOS analog integrated circuits biomedical circuits current-mirror filters pan-tompkins algorithm

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Log-Domain Implementation of QRS Detection System Using the pan-tompkins algorithm with Fractional-Order Differentiator for Improved Noise Rejection

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JOURNAL OF LOW POWER ELECTRONICS 2016年第4期12卷 352-360页

作者： Beigh, I. N. Khanday, F. A. Psychalinos, C. Univ Kashmir Dept Elect & Instrumentat Technol Srinagar 190006 Jammu & Kashmir India Univ Patras Phys Dept Elect Lab GR-26504 Rion Greece

A low-voltage Log-Domain implementation of QRS detection system with pan-tompkins algorithm is introduced in this paper. The employed stages were: band-pass filter, fractional-order differentiator, and squarer. The reason was that replacing the integer-order differentiator by its fractional-order counterpart enhances the noise performance of the system as the gain for high frequency noise gets reduced. The performance of the system has been verified by HSPICE simulation software using the parameters of TSMC CMOS 130 nm CMOS process.

关键词： ECG Signal QRS Detection pan-tompkins algorithm Log-Domain Technique Fractional-Order Systems

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Acceptable ECG Trace Selection Based on pan-tompkins algorithm

Acceptable ECG Trace Selection Based on Pan-Tompkins Algorit...

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International Conference on Informatics, Electronics and Vision

作者： K. M. Talha Nahiyan Abdullah Al-Amin Department of Biomedical Physics and Technology University of Dhaka

ISBN: (纸本)9781509012701

关键词： ECG Trace selection pan-tompkins algorithm

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Determination of R-peaks in ECG Signal Using Hilbert Transform and pan-tompkins algorithms 25

Determination of R-peaks in ECG Signal Using Hilbert Transfo...

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25th Signal Processing and Communications Applications Conference (SIU)

作者： Diker, Aykut Avci, Engin Gedikpinar, Mehmet Bitlis Eren Univ Enformat Bolumu Bitlis Turkey Firat Univ Elekt Elekt Muhendisligi Yazilim Muhendisligi Elazig Turkey

ISBN: (纸本)9781509064946

Electrocardiogram (ECG) illustrates the electrical activity in the heart, and it is the most important physiological parameter that gives the correct assessment regarding the functioning of the heart. Accurate detection of R peaks in the ECG signal is an important parameter in determining of heart disorders. In this study, The R peaks of ECG records from the Physionet MIT-BIH arrhythmia database were detected using Hilbert Transform and pan-tompkins algorithms. The pan-tompkins R peak detector is validated using the ECG records of the MIT-BIH arrhythmia database, and achieves with detection accuracy of 97.12%, sensitivity of 98.46% and positive predictivity of 98.62%.

关键词： ECG Hilbert Transform pan-tompkins algorithm MIT-BIH

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A novel IRBF-RVM model for diagnosis of atrial fibrillation

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019年 177卷 183-192页

作者： Kong, Dongdong Zhu, Junjiang Wu, Shangshi Duan, Chaoqun Lu, Lixin Chen, Dongxing Shanghai Univ Sch Mechatron Engn & Automat 99 Shanghai Rd Shanghai Peoples R China China Jiliang Univ Coll Mech & Elect Engn Hangzhou Zhejiang Peoples R China Shanghai Tenth Peoples Hosp Dept Cardiovasc Med Shanghai Peoples R China

Background and objective: Atrial fibrillation (AF) is one of the common cardiovascular diseases, and electrocardiography (ECG) is a key indicator for the detection and diagnosis of AF and other heart diseases. In this study, an improved machine learning method is proposed for rapid modeling and accurate diagnosis of AF. Methods: This paper presents a novel IRBF-RVM model that combines the integrated radial basis function (IRBF) and relevance vector machine (RVM), which is utilized for the diagnosis of AF. The synchronous 12-lead ECG signals are collected from the human body surface so as to fully reflect the electrical activity of the whole heart. RR intervals of the QRS-waves in ECG signals are obtained by means of the classical pan-tompkins algorithm. The RR-features extracted from RR intervals are adopted as the diagnostic features for AF patients. In addition, the conventional RBF-RVM model, support vector machine (SVM) and other machine learning methods are also investigated for the diagnosis of AF so as to reflect the advantage of the proposed IRBF-RVM model. The open MIT-BIH arrhythmia database (MITDB) is also used to evaluate the predictive performance of these state-of-the-art methods. Results: Altogether 1056 AF patients and 904 healthy people are participated in this study and validate the effectiveness of each channel of the 12-lead ECG signals. Experimental results show that the classification rate of IRBF-RVM can reach up to 98.16% by recurring to Channel II of the 12-lead ECG signals. Conclusions: IRBF-RVM absorbs the advantages of IRBF, which makes the kernel parameter of IRBF-RVM have a much larger selectable region than RBF-RVM. In addition, RVM has faster modeling and recognition speed in comparison with SVM. This work lays the foundation for the application of RVM to accurate diagnosis of AF. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Atrial fibrillation pan-tompkins algorithm Integrated radial basis function Relevance vector machine

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Combining algorithms in automatic detection of QRS complexes in ECG signals

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IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE 2006年第3期10卷 468-475页

作者： Meyer, Carsten Fernandez Gavela, Jose Harris, Matthew Philips Res Lsbs D-52066 Aachen Germany

QRS complex and specifically R-Peak detection is the crucial first step in every automatic electrocardiogram analysis. Much work has been carried out in this field, using various methods ranging from filtering and threshold methods, through wavelet methods, to neural networks and others.. Performance is generally good, but each method has situations where it fails. In this paper, we suggest an approach to automatically combine different QRS complex detection algorithms, here the pan-tompkins and wavelet algorithms, to benefit from the strengths of both methods. In particular, we introduce parameters allowing to balance the contribution of the individual algorithms;these parameters are estimated in a data-driven way. Experimental results and analysis are provided on the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia Database. We show that our combination approach outperforms both individual algorithms.

关键词： automatic QRS complex detection automatic R-peak detection combination algorithm ensemble method Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia Database pan-tompkins algorithm wavelet algorithm

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PcHD: Personalized classification of heartbeat types using a decision tree

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COMPUTERS IN BIOLOGY AND MEDICINE 2014年第1期54卷 79-88页

作者： Park, Juyoung Kang, Kyungtae Hanyang Univ Dept Comp Sci & Engn Ansan 426791 South Korea

The computer-aided interpretation of electrocardiogram (ECG) signals provides a non-invasive and inexpensive technique for analyzing heart activity under various cardiac conditions. Further, the proliferation of smartphones and wireless networks makes it possible to perform continuous Holter monitoring. However, although considerable attention has been paid to automated detection and classification of heartbeats from ECG data, classifier learning strategies have never been used to deal with individual variations in cardiac activity. In this paper, we propose a novel method for automatic classification of an individual's ECG beats for Holter monitoring. We use the pan-tompkins algorithm to accurately extract features such as the QRS complex and P wave, and employ a decision tree to classify each beat in terms of these features. Evaluations conducted against the MIT-BIH arrhythmia database before and after personalization of the decision tree using a patient's own ECG data yield heartbeat classification accuracies of 94.6% and 99%, respectively. These are comparable to results obtained from state-of-the-art schemes, validating the efficacy of our proposed method. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Heartbeat classification Decision tree model Personalization Electrocardiogram pan-tompkins algorithm Holter monitoring

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