26 citations · 55 across the 10 of their papers we have counts for
11 papers
DCentNet: Decentralized Multistage Biomedical Signal Classification using Early Exits
Xiaolin Li, Binhua Huang, Barry Cardiff +1
DCentNet is a novel decentralized multistage signal classification approach designed for biomedical data from IoT wearable sensors, integrating early exit points (EEP) to enhance e…
A Review on Multisensor Data Fusion for Wearable Health Monitoring
Arlene John, Barry Cardiff, Deepu John
The growing demand for accurate, continuous, and non-invasive health monitoring has propelled multi-sensor data fusion to the forefront of healthcare technology. This review aims t…
Atrial Fibrillation Detection Using Weight-Pruned, Log-Quantised Convolutional Neural Networks
Xiu Qi Chang, Ann Feng Chew, Benjamin Chen Ming Choong +6
Deep neural networks (DNN) are a promising tool in medical applications. However, the implementation of complex DNNs on battery-powered devices is challenging due to high energy co…
Classification of ECG based on Hybrid Features using CNNs for Wearable Applications
Li Xiaolin, Fang Xiang, Rajesh C. Panicker +2
Sudden cardiac death and arrhythmia account for a large percentage of all deaths worldwide. Electrocardiography (ECG) is the most widely used screening tool for cardiovascular dise…
A predictive analytics approach for stroke prediction using machine learning and neural networks
Soumyabrata Dev, Hewei Wang, Chidozie Shamrock Nwosu +3
The negative impact of stroke in society has led to concerted efforts to improve the management and diagnosis of stroke. With an increased synergy between technology and medical di…
Identifying Stroke Indicators Using Rough Sets
Muhammad Salman Pathan, Jianbiao Zhang, Deepu John +2
Stroke is widely considered as the second most common cause of mortality. The adverse consequences of stroke have led to global interest and work for improving the management and d…
Multistage Pruning of CNN Based ECG Classifiers for Edge Devices
Xiaolin Li, Rajesh Panicker, Barry Cardiff +1
Using smart wearable devices to monitor patients electrocardiogram (ECG) for real-time detection of arrhythmias can significantly improve healthcare outcomes. Convolutional neural…
SomnNET: An SpO2 Based Deep Learning Network for Sleep Apnea Detection in Smartwatches
Arlene John, Koushik Kumar Nundy, Barry Cardiff +1
The abnormal pause or rate reduction in breathing is known as the sleep-apnea hypopnea syndrome and affects the quality of sleep of an individual. A novel method for the detection…
Continuous User Authentication using IoT Wearable Sensors
Conor Smyth, Guoxin Wang, Rajesh Panicker +3
Over the past several years, the electrocardiogram (ECG) has been investigated for its uniqueness and potential to discriminate between individuals. This paper discusses how this d…
A Generalized Signal Quality Estimation Method for IoT Sensors
Arlene John, Barry Cardiff, Deepu John
IoT wearable devices are widely expected to reduce the cost and risk of personal healthcare. However, ambulatory data collected from such devices are often corrupted or contaminate…
Predicting Stroke from Electronic Health Records
Chidozie Shamrock Nwosu, Soumyabrata Dev, Peru Bhardwaj +2
Studies have identified various risk factors associated with the onset of stroke in an individual. Data mining techniques have been used to predict the occurrence of stroke based o…