Sensor Analytics for Healthcare Improvement
The increasing proportion of older adults and corresponding costs associated with chronic disease management demand novel technological solutions. It is expected that new healthcare services will shift from clinical and hospital settings to a personalized and homebound environment. Along with the rapid advances in several technological domains including sensing, communication, and human factors design in the last decade, new technologies have led to the development of new mobile and personalized systems capable of analyzing and visualizing varying heterogeneous physiological signals. This dissertation presents an end-to-end research methodology for design and development of next generation wireless health applications, with a particular emphasis on innovative sensing systems design.
I summarize my research in wireless health domain: from On-bed physiological signals monitoring, Contactless vital signs monitoring, Augmented visualization, Virtual reality based rehabilitation, to Social activity promotion. Each project involved medical problem identification, feasible solution development, and clinical verification. In this dissertation, I address novel hardware and software sensing and interaction technologies, including sensor system design, sensor modeling, and sensor signal processing. The ultimate goals of this interdisciplinary research are to support our medical hypothesis, verify the feasibility of technological solutions in clinics, and eventually enable wireless health from concept to practice.