Advanced Sensing and Image Processing Techniques for Healthcare Applications—2nd Edition

Dear Colleagues,

Developing new technologies for health and social care sections have always been of particular attention to researchers. Additionally, the recent increasing rate of aging population, particularly in developed countries, has doubled the demand for intelligent systems for the elderly. On the other hand, super-fast advances in technology and science have raised expectations of inventing new monitoring and assistive technologies for accurate and delay-sensitive acquisition, processing, transmission, and interpretation of humans’ physiological and behavioural data. Therefore, a variety of enabling techniques such as signal and image processing, machine learning, and compression techniques could be used to improve such systems and achieve the aforementioned goal. Therefore, the ultimate outcome would be increased quality of life and improve the healthcare services to the older populations.

Owing to the success of the first volume, we have edited this second one. This Special Issue aims to attract the latest research and findings in design, development and experimentation of healthcare-related technologies. This includes, but is not limited to, using novel sensing, imaging, data processing, machine learning, and artificial intelligent devices and algorithms to assist/monitor elderly, patients, and disabled population.

Topics of interest include, but are not restricted to:

• Biomedical signal and image processing;
• Smart monitoring and assisted living systems;
• Deep learning for healthcare data;
• Sensor fusion of biomedical data;
• Compressive sensing of biomedical data;
• Cloud/Edge/Fog computing for healthcare systems;
• Smart phone-based vital signal monitoring;
• Brain Computer Interface for disabled;
• Wireless body sensor networks;
• Risks and accidents detection for elderly care;
• Activity recognition;
• Big data analysis for healthcare applications;
• IoT Applications in healthcare;
• Sensors and actuators in healthcare systems;
• Mental disorder detection;
• Smart breathing activity monitoring;
• Non-invasive glucose monitoring.

Dr. Vahid Abolghasemi
Dr. Hossein Anisi
Dr. Saideh Ferdowsi
Guest Editors

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