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6 articles for “ECG signals”
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Unveiling The Seamless Integration: The impact of IOT Technologies on everyday life and organizational Dynamics
Abstract: Internet of Things (IoT) is about connecting devices worldwide to simplify life and save energy. This study talks about these issues and looks ahead to what is next for IoT. Even though IoT mixes the digital and physical worlds, there is still a lot to learn. This study discusses the problems and suggests solution for future research. Currently, IoT is changing everything from homes to industries. This study explains IoT …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 1–9 Read article
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A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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A Review on Electro Cardio Graph a New Approach
Abstract: An electrocardiogram (ECG) records the heart's electrical activity during a cardiac cycle. A lightweight system for analyzing ECG signal strength, aimed for real-time use and automatic classification, will be developed. This system will utilize ECG sensors, Arduino microcontrollers, Android phones, Bluetooth connectivity, and cloud servers, with a focus on ensuring secure data transfer. Lightweight Access Control (LAC) and Lightweight Secure IoT (LS-IoT) will be employed for this purpose. The paper …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 1, 2024 · pp. 1–13 Read article
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AI-Powered ECG Prediction System for Detecting Cardiovascular Disease
Abstract: The proposed AI-powered CardioSmart Analyzer, an electrocardiogram (ECG) prediction system, presents an innovative and scientifically rigorous approach to the real-time automated analysis of ECG signals for diagnosing various heart conditions. This research focused on building a predictive model to identify cardiovascular diseases (CVD) using ECG data. A dataset comprising 2,840 12-lead ECG recordings was gathered from medical facilities in Gazipur, Bangladesh, over the period from June to August 2024. The …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 51–85 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article