Machine learning for healthcare wearable devices: the big picture
Using artificial intelligence and machine learning techniques in healthcare applications has
been actively researched over the last few years. It holds promising opportunities as it is …
been actively researched over the last few years. It holds promising opportunities as it is …
Deep learning for detecting and locating myocardial infarction by electrocardiogram: A literature review
P Xiong, SMY Lee, G Chan - Frontiers in cardiovascular medicine, 2022 - frontiersin.org
Myocardial infarction is a common cardiovascular disorder caused by prolonged ischemia,
and early diagnosis of myocardial infarction (MI) is critical for lifesaving. ECG is a simple and …
and early diagnosis of myocardial infarction (MI) is critical for lifesaving. ECG is a simple and …
AHAR: Adaptive CNN for energy-efficient human activity recognition in low-power edge devices
N Rashid, BU Demirel… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Human activity recognition (HAR) is one of the key applications of health monitoring that
requires continuous use of wearable devices to track daily activities. This article proposes an …
requires continuous use of wearable devices to track daily activities. This article proposes an …
Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis
The integration of artificial intelligence in precision medicine has revolutionized healthcare
delivery. Precision medicine identifies the phenotype of particular patients with less-common …
delivery. Precision medicine identifies the phenotype of particular patients with less-common …
[HTML][HTML] Artificial intelligence for detection of cardiovascular-related diseases from wearable devices: a systematic review and meta-analysis
Purpose Several artificial intelligence (AI) models for the detection and prediction of
cardiovascular-related diseases, including arrhythmias, diabetes, and sleep apnea, have …
cardiovascular-related diseases, including arrhythmias, diabetes, and sleep apnea, have …
Stress detection using context-aware sensor fusion from wearable devices
N Rashid, T Mortlock… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Wearable medical technology has become increasingly popular in recent years. One
function of wearable health devices is stress detection, which relies on sensor inputs to …
function of wearable health devices is stress detection, which relies on sensor inputs to …
A modified and effective blockchain model for e-healthcare systems
B Assiri - Applied Sciences, 2023 - mdpi.com
The development of e-healthcare systems requires the application of advanced
technologies, such as blockchain technology. The main challenge of applying blockchain …
technologies, such as blockchain technology. The main challenge of applying blockchain …
Template matching based early exit cnn for energy-efficient myocardial infarction detection on low-power wearable devices
Myocardial Infarction (MI), also known as heart attack, is a life-threatening form of heart
disease that is a leading cause of death worldwide. Its recurrent and silent nature …
disease that is a leading cause of death worldwide. Its recurrent and silent nature …
Feature augmented hybrid cnn for stress recognition using wrist-based photoplethysmography sensor
Stress is a physiological state that hampers mental health and has serious consequences to
physical health. More-over, the COVID-19 pandemic has increased stress levels among …
physical health. More-over, the COVID-19 pandemic has increased stress levels among …
Eexnas: Early-exit neural architecture search solutions for low-power wearable devices
Equipping wearable devices with intelligence is essential for promoting mobile healthcare
applications. However, challenges remain due to the resource limitations of these devices …
applications. However, challenges remain due to the resource limitations of these devices …