A smart IoT-enabled heart disease monitoring system using meta-heuristic-based Fuzzy-LSTM model

NK Munagala, LRR Langoju, AD Rani… - biocybernetics and …, 2022‏ - Elsevier
A continuous heart disease monitoring system is one of the significant applications specified
by the Internet of Things (IoT). This goal might be achieved by combining sophisticated …

Remote mobile heath monitoring frameworks and mobile applications: Taxonomy, open challenges, motivation, and recommendations

SA Butt, M Naseer, A Ali, A Khalid, T Jamal… - … Applications of Artificial …, 2024‏ - Elsevier
Advancements in mobile technology have propelled the rapid progress of remote health
monitoring, particularly in the domain of mobile health (mHealth). This progress is …

Dense neural network based arrhythmia classification on low-cost and low-compute micro-controller

MAO Zishan, HM Shihab, SS Islam, MA Riya… - Expert Systems with …, 2024‏ - Elsevier
The electrocardiogram (ECG) monitoring device is an expensive albeit essential device for
the treatment and diagnosis of cardiovascular diseases (CVD). The cost of this device …

Internet of Things-based ECG and vitals healthcare monitoring system

J Heaney, J Buick, MU Hadi, N Soin - Micromachines, 2022‏ - mdpi.com
Health monitoring and its associated technologies have gained enormous importance over
the past few years. The electrocardiogram (ECG) has long been a popular tool for assessing …

ECGencode: Compact and computationally efficient deep learning feature encoder for ECG signals

L Bontinck, K Fonteyn, T Dhaene… - Expert Systems with …, 2024‏ - Elsevier
The visual interpretation of electrocardiogram (ECG) data is driven by human pattern
recognition and requires in-depth medical knowledge. Although state-of-the-art deep …

Evolution of Bioamplifiers: From Vacuum Tubes to Highly Integrated Analog Front-Ends

AA Anisimov, AV Belov, TV Sergeev, EE Sannikova… - Electronics, 2022‏ - mdpi.com
The past century has seen the ongoing development of amplifiers for different
electrophysiological signals to study the work of the heart. Since the vacuum tube era …

Automatic detection of short-term atrial fibrillation segments based on frequency slice wavelet transform and machine learning techniques

Y Yue, C Chen, P Liu, Y **ng, X Zhou - Sensors, 2021‏ - mdpi.com
Atrial fibrillation (AF) is the most frequently encountered cardiac arrhythmia and is often
associated with other cardiovascular and cerebrovascular diseases, such as ischemic heart …

Ensemble classifier fostered detection of arrhythmia using ECG data

M Ramkumar, M Alagarsamy, A Balakumar… - Medical & Biological …, 2023‏ - Springer
Electrocardiogram (ECG) is a non-invasive medical tool that divulges the rhythm and
function of the human heart. This is broadly employed in heart disease detection including …

A joint cross-dimensional contrastive learning framework for 12-lead ECGs and its heterogeneous deployment on SoC

W Liu, H Zhang, S Chang, H Wang, J He… - Computers in Biology and …, 2023‏ - Elsevier
The utilization of unlabeled electrocardiogram (ECG) data is always a critical topic in
artificial intelligence healthcare, as the manual annotation for ECG data is a time-consuming …

A fully-mapped and energy-efficient FPGA accelerator for dual-function AI-based analysis of ECG

W Liu, Q Guo, S Chen, S Chang, H Wang, J He… - Frontiers in …, 2023‏ - frontiersin.org
In this paper, a fully-mapped field programmable gate array (FPGA) accelerator is proposed
for artificial intelligence (AI)-based analysis of electrocardiogram (ECG). It consists of a fully …