相关论文: ECG encryption and identification based security s…

The rapid development in Internet of Medical Things (IoMT) boosts the opportunity for real-time health monitoring using various data types such as electroencephalography (EEG) and electrocardiography (ECG). Security issues have…

This paper describes a highly integrated, low power chip solution for ECG signal processing in wearable devices. The chip contains an instrumentation amplifier with programmable gain, a band-pass filter, a 12-bit SAR ADC, a novel QRS…

The real time analysis and secure transmission of electrocardiogram (ECG) signals are critical for ensuring both effective medical diagnosis and patient data privacy. In this study, we developed a real time ECG monitoring system that…

This study introduces the development of a state of the art, real time ECG monitoring and analysis system, incorporating cutting edge medical technology and innovative data security measures. Our system performs three distinct functions…

Traditional authentication systems use alphanumeric or graphical passwords, or token-based techniques that require "something you know and something you have". The disadvantages of these systems include the risks of forgetfulness, loss, and…

The realtime analysis and secure transmission of electrocardiogram ECG signals are critical for accurate diagnosis and safeguarding patient privacy in telemedicine applications This study presents a novel realtime ECG monitoring system that…

The ongoing integration of fine-grained power management features already established in CPU-driven Systems-on-Chip (SoCs) enables both traditional Field Programmable Gate Arrays (FPGAs) and, more recently, hybrid Programmable SoCs (pSoCs)…

Over the course of the past two decades, a substantial body of research has substantiated the viability of utilising cardiac signals as a biometric modality. This paper presents a novel approach for patient identification in healthcare…

This paper presents a low power ECG recording Sys-tem-on-Chip (SoC) with on-chip low complexity lossless ECG compression for data reduction in wireless/ambulatory ECG sensor devices. The proposed algorithm uses a linear slope predictor to…

This dissertation proposes an electrocardiogram (ECG) tracking device that diagnoses cardiopulmonary problems using the Internet of Things (IoT) desired results. The initiative is built on the internet observing an electrocardiogram with…

The electrocardiogram (ECG) signal is one of the most vital signals that can be used to investigate the performance of heart. Based on the ECG graph, we can identify different disorders and diseases. Therefore, monitoring this signal is of…

The recent developments in wearable devices and the Internet of Medical Things (IoMT) allow real-time monitoring and recording of electrocardiogram (ECG) signals. However, continuous monitoring of ECG signals is challenging in low-power…

In the rapidly evolving landscape of modern healthcare, the integration of wearable & portable technology provides a unique opportunity for personalized health monitoring in the community. Devices like the Apple Watch, FitBit, and AliveCor…

This paper presents a low-power ECG recording system-on-chip (SoC) with on-chip low-complexity lossless ECG compression for data reduction in wireless/ambulatory ECG sensor devices. The chip uses a linear slope predictor for data…

An electrocardiogram (ECG) feature extraction system has been developed and evaluated using Virtex-6 FPGA kit which belongs to Xilinx Ltd. In time domain, Pan-Tompkins algorithm is used for QRS detection and it is followed by a feature…

Fog computing offers a scalable and effective solution to overcome the increasing processing and networking demands of Internet of Thing (IoT) devices. In this paper, we investigate the use of fog computing for health monitoring…

This paper is targeted in the area of biometric data enabled security system based on the machine learning for the digital health. The disadvantages of traditional authentication systems include the risks of forgetfulness, loss, and theft.…

Electrocardiogram (ECG) signal exhibits inherent uniqueness, making it a promising biometric modality for identity authentication. As a result, ECG authentication has gained increasing attention in recent years. However, most existing…

The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials and healthcare procedures. Cardiovascular diseases monitoring, usually involving electrocardiogram (ECG) traces analysis, is one of the most…

Authentication is vital for the Internet of Things (IoT) applications involving sensitive data (e.g., medical and financial systems). Digital signatures offer scalable authentication with non-repudiation and public verifiability, which are…