Perception and Intelligence Driven Sensing to Monitor Personal Health

Dear Colleagues,

With the advancement of sensor technology, data analytics is not restricted to X-ray and MRI scans. Its scope has broadened from 1-K dimensional signal processing to multi-modality fusion and patient perception analysis, e.g. eye-gaze, gait, mood, pose and touch, for monitoring personal health and improvement of the quality of life. Connected health, e.g. using the Internet, Bluetooth and WIFI, offers better tele-health services to remote areas and provides richer information to society in general. These promises inevitably bring the challenges associated with dynamic big data, which include noise filtering, optimization, performance and accuracy evaluations. This special issue focuses on applying the latest state-of-the-art approaches in imaging and sensing, to intelligently acquire, process and analyze health patterns on different computer assisted diagnosis platforms, including but not limited to handheld, mobile and wearable devices. The goal is to help clinical experts and operators to accurately detect and diagnose symptoms faster in order to provide just-in-time treatments to patients. Topics include but are not limited to:

Sensor-based connected health

Sensor-based health data acquisition

Health data analytics 

Health pattern detection and recognition

Multi-modality health data fusion

Health data quality assessment

Health data optimization

Healthcare applications

Dr. Troy McDaniel
Dr. Irene Cheng
Guest Editors

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