Embedded Machine Intelligence Lab

We research design, development, and validation of algorithms, tools, and technologies that enhance utilization and large-scale adoption of pervasive systems.

Embedded Machine Intelligence Lab

Embedded Machine Intelligence Lab

Research Lab

Arizona State University

About EMIL

Medical embedded systems seamlessly connect human users to the physical world that is richly and invisibly interwoven with sensors, actuators, displays, and networks embedded in the everyday objects. The pervasive nature of such systems will transform the way people interact with each other and their environment and will revolutionize the way next generation medical services are provided. When realized properly, the resulting unparalleled information extracted from these systems enables emerging applications in mobile and remote healthcare, wellness, emergency response, fitness monitoring, elderly care support, long-term preventive chronic care, smart environments, gaming and sports.

The current focus of our research is on design, development, and validation of algorithms, tools, and technologies that enhance utilization and large-scale adoption of sensor-based systems in the real-world. To validate and refine the new technology, we conduct clinical studies involving individuals with or at risk for heart failure, diabetes, cancer, visual impairment, Parkinson’s, and cognitive impairment. Studies are conducted in close collaboration with clinical partners. This end-to-end approach results in innovative, evidence-based and cost-conscious solutions for patients, doctors and medical centers.

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