Implementation of Lightweight eHealth Applications on a Low-Power Embedded Processor

The rapid development of Internet of Things (IoT) has opened new opportunities for healthcare systems through so-called eHealth systems. With the help of monitoring using portable IoT devices with biomedical sensors, disease diagnoses can be conducted in real time. However, there is a challenge in that monitoring is an always-on activity that requires constant power supply and IoT devices are battery-powered and face heavy resource constraints. This work addresses a realistic implementation of a low-power eHealth device using both hardware and software approaches. We realize various lightweight eHealth applications (particularly monitoring applications) using a memory-conscious dynamic time warping (DTW) algorithm to be deployed on a small and low-power embedded processor. Actual prototypes of the processor are currently being fabricated. Our evaluation showcases the effectiveness of our work compared with other state-of-the-art embedded processors in terms of circuit area (fabrication cost) and power efficiency. We also demonstrated the scalability of the software implementation by varying the amount of data used in DTW for various eHealth monitoring applications.