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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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Quantum leap in cardiac prognosis: EMIP-cardioPPG's pioneering approach to early myocardial infarction prediction

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SIGNAL IMAGE AND VIDEO PROCESSING 2024年第12期18卷 8723-8737页

作者： Shrivastava, Abhishek Kumar, Santosh Naik, N. Srinivas IIIT Naya CSE Sect 24 Raipur 493661 Chhattisgarh India IIITDM Kurnool CSE Jagannathagattu Hill Kurnool 518007 Andhra Pradesh India

Cardiovascular disease encompasses conditions affecting the heart and blood vessels, leading to ailments such as coronary artery disease, heart failure, and myocardial infarction (MI), which occurs when blood flow to the heart is obstructed. Early prediction of MI is vital to prevent severe damage and enhance survival rates. Traditionally, an electrocardiogram (ECG) is employed to detect cardiovascular anomalies, but its requirement for multiple electrodes placed on various body locations makes continuous monitoring difficult. Current research gaps involve the necessity for medical assistance during ECG monitoring, data variability, accuracy, early symptom prediction, and limited data availability due to the sensitive nature of medical records. To address these issues, introduce EMIP-CardioPPG, a novel mathematical framework for early MI prediction using CardioPPG, a non-invasive method that utilizes photoplethysmography (PPG) signals to monitor heart rate (HR) and detect cardiovascular abnormalities. Our approach comprises four steps: first, acquiring data from the same individual using two different sources, a self-created IoMT device and a 4-channel BIOPAC-Mp-36 device;second, preprocessing the data by denoising, filtering, normalizing, and removing motion artifacts;and third, employing mathematical calculations to determine heart rate variability (HRV) and HR, enhancing PPG signal features for early MI prediction. Fourth, evaluate our model performance using machine learning algorithms such as ridge regression, support vector classifier, independent component analysis, singular value decomposition, random forest, and XGBoost, pan-tompkins algorithm achieving overall accuracy of 97.91% for HRV from our IomT device and 98.83% for HR from our BIOPAC-MP-36.

关键词： Myocardial infarction Heart rate variability Electrocardiogram Photoplethysmogram Internet of medical things pan-tompkins algorithm

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Improving Energy Efficiency in Medical Edge Devices for ECG Feature Detection via Approximate Computing 5

Improving Energy Efficiency in Medical Edge Devices for ECG ...

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5th IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2023

作者： Nagatomo, Taiki Sato, Toshinori Fukuoka University Department of Electronics Engineering and Computer Science Graduate School of Engineering Fukuoka Japan Fukuoka University Department of Electronics Engineering and Computer Science Faculty of Engineering Fukuoka Japan

ISBN: (纸本)9798350314694

Improving the energy efficiency of battery-powered medical edge devices is a challenge. In this study, we explored electrocardiogram (ECG) feature detection using the pan-tompkins algorithm and integrated approximate computing techniques involving addition and multiplication into the process to enhance power efficiency. We adopted eight approximate multipliers from EvoApproxLib along with a Carry-Maskable Adder (CMA). We evaluated the impact of applying approximate computing on feature detection accuracy, as well as its influence on enhancing the power efficiency of the arithmetic circuits. When replacing just one of the arithmetic circuits with its approximate counterpart, the most power-efficient multiplier had dynamic power reduced by 48.3% in multiplications while maintaining a detection accuracy of 99.96%, while the CMA reduced dynamic power reduction by 95.2% while maintaining a detection accuracy 99.4%. When the CMA and approximate multiplication were applied, detection accuracy was maintained at 99.4%. In terms of power efficiency, the multiplier played a predominant role and the overall dynamic power consumption was reduced by 48.7%. © 2023 IEEE.

关键词： approximate computing ECG medical edge devices pan-tompkins algorithm signal processing

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Feasibility Analysis of ECG-Based pH Estimation for Asphyxia Detection in Neonates

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SENSORS 2024年第11期24卷 3357页

作者： Hussain, Nadia Muhammad Amin, Bilal McDermott, Barry James Dunne, Eoghan O'Halloran, Martin Elahi, Adnan Univ Galway Elect & Elect Engn Galway H91 TK33 Ireland Univ Galway Translat Med Device Lab Galway H91 TK33 Ireland Univ Galway Sch Med Galway H91 TK33 Ireland

Birth asphyxia is a potential cause of death that is also associated with acute and chronic morbidities. The traditional and immediate approach for monitoring birth asphyxia (i.e., arterial blood gas analysis) is highly invasive and intermittent. Additionally, alternative noninvasive approaches such as pulse oximeters can be problematic, due to the possibility of false and erroneous measurements. Therefore, further research is needed to explore alternative noninvasive and accurate monitoring methods for asphyxiated neonates. This study aims to investigate the prominent ECG features based on pH estimation that could potentially be used to explore the noninvasive, accurate, and continuous monitoring of asphyxiated neonates. The dataset used contained 274 segments of ECG and pH values recorded simultaneously. After preprocessing the data, principal component analysis and the pan-tompkins algorithm were used for each segment to determine the most significant ECG cycle and to compute the ECG features. Descriptive statistics were performed to describe the main properties of the processed dataset. A Kruskal-Wallis nonparametric test was then used to analyze differences between the asphyxiated and non-asphyxiated groups. Finally, a Dunn-& Scaron;id & aacute;k post hoc test was used for individual comparison among the mean ranks of all groups. The findings of this study showed that ECG features (T/QRS, T Amplitude, Tslope, Tslope/T, Tslope/|T|, HR, QT, and QTc) based on pH estimation differed significantly (p < 0.05) in asphyxiated neonates. All these key ECG features were also found to be significantly different between the two groups.

关键词： asphyxiated neonates arterial blood gas analysis birth asphyxia Dunn-& Scaron id & aacute k post hoc test ECG features Kruskal-Wallis nonparametric test pan-tompkins algorithm

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Recognition of positive and negative valence states in children with autism spectrum disorder (ASD) using discrete wavelet transform (DWT) analysis of electrocardiogram signals (ECG)

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2021年第1期12卷 405-416页

作者： Bagirathan, Anandhi Selvaraj, Jerritta Gurusamy, Anusuya Das, Himangshu Vels Inst Sci Technol & Adv Studies VISTAS Chennai Tamil Nadu India Natl Inst Empowerment Persons Multiple Disabil Di Chennai Tamil Nadu India

Children with autism spectrum disorder (ASD) are deficit in communication, social skills, empathy, emotional responsiveness and have significant behavioral pattern. They have difficulty in understanding other feelings and their own emotions. This leads to the sudden emotional outburst and aggressive behavior in these children. Parents, caretakers and doctors find it very difficult to prevent such extreme behaviors. Learning the positive and negative valence leads in determining the early indications before the onset of emotional outbursts in children with ASD. The present study measures the psycho physiological electrocardiogram (ECG) signal from the typically developed (TD) children and children with ASD in the age group of 5-11 years. Personalized protocol was developed for every child with ASD to induce positive and negative valence and ECG data was collected using wearable Shimmer ECG device. The heart rate variability (HRV) and the QRS amplitude were derived from ECG signal using pan-tompkins algorithm and eleven features were extracted using DWT (db2, db4 and db8) mother wavelet. The significant features of ECG, HRV and QRS amplitude were classified using the K nearest neighbor (KNN), support vector machine (SVM) and ensemble classifier. Ensemble and KNN classifier achieved maximum accuracy of 81% and 76.2% for children with ASD and Ensemble and SVM classifiers obtained maximum accuracy of 87.4% and 83.8% for TD children using HRV data.

关键词： Autism spectrum disorder (ASD) Heart rate variability (HRV) pan-tompkins algorithm K nearest neighbor (KNN)

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