As its first year wraps up, the Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) has made significant progress toward its goal of using mobile sensor data to realize precision medicine. Through their involvement with MD2K, researchers at Rice University are using human sensing technology to study underserved populations.
The MD2K Center is tasked with developing the means to gather, analyze, visualize and interpret health-related mobile sensor data. This capability is critical to discovering new insights on the role of behavioral and environmental context in the onset and progression of disease. The ultimate goal is to develop timely and personalized mobile health interventions for early detection and prevention of disease, which will help realize President Barack Obama’s vision of precision medicine.
An example of the MD2K team’s progress in converting mobile sensor data into markers of poor health and risk factors is a computational model that automatically detects when a newly abstinent smoker lapses for the first time in a smoking-cessation attempt. Called “puffMarker,” the model uses hand gestures from smartwatches and breathing signature from a respiration sensor.
“Development of the puffMarker model has fulfilled a long-standing need in smoking cessation research to precisely pinpoint the timing of first lapse,” said Santosh Kumar, director of MD2K. “This work has opened the doors to discover potent markers in the data collected by mobile sensors that can be used to deliver just-in-time mHealth intervention to improve smoking-cessation rates.” (mHealth is a term used for the practice of medicine and public health supported by mobile devices.)
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