Demo: Exploiting IMU Sensors for IoT Enabled Health Monitoring

Abstract

Inertial Measurement Units (IMUs) embedded in commercial mobile devices are a good choice for continuous monitoring in healthcare domain due to their attractive form factor and low power consumption. We present improved and accurate sensing algorithms to sense basic events like step count, stride length, fall, and calorie, with accuracies better than those of existing arts. The events can be directed to a server running event analytics, yielding important cues about subject's health. One of the important spheres is elderly health- care where such a system might promote a better insight to the subject's health parameters. Fall Detection. For an improved fall detection, we propose the algorithm as in Figure 1, which shows a substantial improvement on mobifall dataset [3] compared to existing arts, with an average sensitivity of 0:855 and a more robust false event rejections. The detection can be used to trigger an automatic alarm for the need of an urgent attention to the elderly subject.