The traditional healthcare industry is undergoing a major paradigm shift due to rapid advancements and developments of mobile, wearable, and other digital technologies in computing and networking. These eHealth technologies promise to bring tremendous benefits and opportunities to the diagnosis, prognosis, treatment, and prevention of human diseases for a better quality of life. Particularly, during the current global pandemic, such technologies have been rapidly developed and widely used.

Meanwhile, eHealth presents unprecedented technical challenges in the entire process of data collection, processing, analysis, synthesis, and visualization. For example, the advent of wearable technology has made it possible to constantly monitor sophisticated biometrics for many people ranging from non-professional athletes to chronic healthcare patients. A wide spectrum of devices is being designed as either a replacement of an existing healthcare monitor or a proposition for a new multifunction one. These devices typically require communication with a central healthcare system via cell phones or tablets. It is crucial to design and implement new eHealth technologies to build reliable, accurate, and efficient healthcare environments for optimal patient care. The wide deployments of such wearable monitoring devices have also raised a critical issue regarding health informatics caused by the sheer volume and high complexity of health data that is collected anywhere and anytime. Machine learning and big data-oriented algorithms, models, systems, and platforms are needed to support the analysis, use, interpretation, and integration of diverse health data.

The purpose of this Special Issue is to publish original and high-quality research papers as well as review articles addressing recent eHealth advances and developments that use mobile and wireless devices and all digital technologies to improve health outcomes, healthcare services and health research. Potential topics include, but are not limited to:

Potential topics include but are not limited to the following:

• Advances in sensor devices for biomedical monitoring
• eHealth informatics and information/management systems
• Energy management and optimization for eHealth
• Big data analytics, machine learning, and visualization techniques for eHealth
• Crowdsourcing for public health surveillance, prevention, and emergencies using eHealth
• Patient diagnostics via eHealth solutions
• Decision support systems for eHealth
• Pervasive and ubiquitous computing technologies for health and wellbeing
• Electronic health records storage and transmission
• Case studies in eHealth for healthcare
• Applications of machine learning and artificial intelligence
• Data analytics research
• Health system solutions using Internet of Medical Things (IoMT)