Visualization of Health Monitoring Data Acquired from Distributed Sensors for Multiple Patients

As global healthcare systems transition into the digital era, remote patient health monitoring will be widespread through the use of inexpensive monitoring devices, such as ECG patches, glucose monitors, etc. Once a sensor-concentrator-cloudlet-cloud infrastructure is in place, it is not unrealistic to imagine a scenario where a physician monitors 20-30 patients remotely. Such an infrastructure will revolutionize clinical diagnostics and preventative medicine by allowing the doctors to access long-term and real-time information, which cannot be obtained from short-term in-hospital ECG recordings. While the large amount of sensor data available to a physician is incredibly valuable clinically, it is overwhelming in raw form. In this paper, the data handling aspect of such a long term health monitoring system is studied. Novel ways to record, aggregate, and visualize this flood of sensory data in an intuitive manner are introduced which allow a doctor to review days worth of data in a matter of seconds. This system is one of the first attempts to provide a tool that allows the visualization of long-term monitoring data acquired from multiple sensors.