IoT-based telemedicine for disease prevention and health promotion: State-of-the-Art

AS Albahri, JK Alwan, ZK Taha, SF Ismail… - Journal of Network and …, 2021‏ - Elsevier
Numerous studies have focused on making telemedicine smart through the Internet of
Things (IoT) technology. These works span a wide range of research areas to enhance …

ECG monitoring systems: Review, architecture, processes, and key challenges

MA Serhani, H T. El Kassabi, H Ismail, A Nujum Navaz - Sensors, 2020‏ - mdpi.com
Health monitoring and its related technologies is an attractive research area. The
electrocardiogram (ECG) has always been a popular measurement scheme to assess and …

Machine learning techniques in emerging cloud computing integrated paradigms: A survey and taxonomy

D Soni, N Kumar - Journal of Network and Computer Applications, 2022‏ - Elsevier
Cloud computing offers Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and
Software as a Service (SaaS) to provide compute, network, and storage capabilities to the …

A survey on application of machine learning for Internet of Things

L Cui, S Yang, F Chen, Z Ming, N Lu, J Qin - International Journal of …, 2018‏ - Springer
Abstract Internet of Things (IoT) has become an important network paradigm and there are
lots of smart devices connected by IoT. IoT systems are producing massive data and thus …

Online heart monitoring systems on the internet of health things environments: A survey, a reference model and an outlook

MAG Santos, R Munoz, R Olivares, PP Rebouças Filho… - Information …, 2020‏ - Elsevier
Abstract The Internet of Health Things promotes personalized and higher standards of care.
Its application is diverse and attracts the attention of a substantial section of the scientific …

Unraveling Attacks to Machine Learning-Based IoT Systems: A Survey and the Open Libraries Behind Them

C Liu, B Chen, W Shao, C Zhang… - IEEE Internet of …, 2024‏ - ieeexplore.ieee.org
The advent of the Internet of Things (IoT) has brought forth an era of unprecedented
connectivity, with an estimated 80 billion smart devices expected to be in operation by the …

Machine learning and the electrocardiogram over two decades: Time series and meta-analysis of the algorithms, evaluation metrics and applications

K Rjoob, R Bond, D Finlay, V McGilligan… - Artificial Intelligence in …, 2022‏ - Elsevier
Background The application of artificial intelligence to interpret the electrocardiogram (ECG)
has predominantly included the use of knowledge engineered rule-based algorithms which …

Wearables, artificial intelligence, and the future of healthcare

OF El-Gayar, LS Ambati, N Nawar - AI and Big Data's Potential for …, 2020‏ - igi-global.com
Common underlying risk factors for chronic diseases include physical inactivity
accompanying modern sedentary lifestyle, unhealthy eating habits, and tobacco use …

Personalized wearable systems for real-time ECG classification and healthcare interoperability: Real-time ECG classification and FHIR interoperability

A Walinjkar, J Woods - 2017 Internet Technologies and …, 2017‏ - ieeexplore.ieee.org
Continuous monitoring of an individual's health using wearable biomedical devices is
becoming a norm these days with a large number of wearable kits becoming easily …

Applications of big data analytics and machine learning in the internet of things

S Yousefi, F Derakhshan, H Karimipour - Handbook of big data privacy, 2020‏ - Springer
Nowadays, the efficiency of Machine Learning (ML) mechanisms in the Internet of Things
(IoT) prompts the researchers and developers to use these emerging technology in different …