A broad range of challenges faces the use of assistive technologies and signal processing techniques for human physiological monitoring, however, the use of novel and unobtrusive sensing architectures and algorithms represents a fundamental step towards the development of applications that are ready to use by a broad spectrum of users, from frail and older people to athletes and regular gym-goers.

Furthermore, recent technological developments in wearable and environmental sensors mean they have become increasingly robust and reliable when acquiring fundamental parameters for the analysis of people's physiology and health. Wearable systems can be used during typical daily and goal-oriented physical activities, thus offering the opportunity to record user data in real-time, continuously and without discomfort. Consequently, these systems can offer new treatments, assistance, or novel training opportunities to people. Due to their small size and ability to integrate within mobile computing applications, these proposed sensing technologies will allow for the continuous long-term monitoring of human physiological and behavioral parameters during common activities and in all contexts within equipped laboratories. These technologies will also be able to assist users by giving them information on their health conditions and their behavior, such as sleep, registering body movements, gait analysis, and activity tracking, through direct feedback, increasing the user's proprioception. This helps users to sense where they are in space during their activities and is critical in helping with balance and movement issues that can be enhanced with the support of novel sensing technologies and techniques.

This Special Issue aims to present recent advances in sensing technologies and mobile computing applications that are relevant for physiological human monitoring systems. Researchers and practitioners are invited to submit cutting-edge technologies, novel research, and tutorial overviews on topics related to the future development of human physiological monitoring. In this context, novel solutions for coping with Internet of Things or wireless communication-related issues and requirements, like low latency and edge processing capabilities, are also welcomed. We accept both original research and review articles.

Potential topics include but are not limited to the following:

• Mobile data acquisition, signal processing, and data analysis
• Wireless and radio frequency sensing systems
• Mobile computing for wearables for physiological signals
• Sensors and devices for physical training
• Signal processing for motion and gesture detection and classification
• Assistive devices, technologies, and sensors
• Machine learning for wearable applications
• New sensing technologies for activity recognition, gait analysis, and sleep monitoring