Wearable Sensors for Continuous Health Monitoring and Analysis: 2nd Edition

Dear Colleagues,

Improvements in wearable technology and the ability to embed sensors in wearable devices in recent years have had a significant impact on a wide range of fields, including healthcare, sports, entertainment, and fitness, among others. Indeed, wearable devices incorporate multiple sensing elements, such as accelerometers, gyroscopes, temperature sensors, microelectromechanical systems (MEMSs), and biosensors, which are designed to be energy-efficient, wireless, and noninvasive; they thus provide a more comprehensive view of a user's health and wellness. These sensors enable the monitoring of dynamic and noninvasive measurements, acquire biomedical and biomechanical signals, and provide continuous and real-time functional tracking information. They have the advantages of being small-sized, easy to install, lightweight, portable, highly efficient, and low-cost.

The data collected by wearable sensors can be transmitted directly to a smartphone or any other device, which then forwards the data to a smart IoT system for their storage, analysis, and interpretation. This allows for a wide range of healthcare activities, including disease prevention, diagnosis, treatment, and management. In addition, they can be applied to monitor athletic performance, track movements, prevent injuries, detect falls, and alert caregivers or emergency services by using artificial intelligence.

This Special Issue aims to attract the latest research and findings in the design, development, and validation of wearable sensors and devices, as well as their integration into the IoT ecosystem to be used for analysis and continuous monitoring in applications of health, wellness, and physical activity, among others. We welcome the submission of original, technical, or critical papers focused on, but not limited to, the following topics:

Wireless body sensor networks;

Gesture recognition with wearable sensors;

Novel sensors for monitoring health data and physical activity;

Cloud/Edge/Fog computing for healthcare and wellness systems;

Vital signal continuous monitoring;

Multisensor data fusion;

Human activity recognition;

IoT Applications in healthcare and sports activity;

Wearable sensors for m-health and u-health;

New algorithms and methods for physical activity analysis;

Real-time artificial intelligence-based health monitoring;

Pattern recognition in routines for high-performance athletes;

Data analytics and machine learning for wearable sensor data in health analysis;

Ethical and privacy issues in wearable sensor-based health monitoring.

Prof. Dr. Juan Antonio Holgado-Terriza
Dr. Zilu Liang
Guest Editors

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