Centralized State Sensing Using Sensor Array on Wearable Device

Abstract

Signal acquisition from the wrist using wearable device is usually corrupted by noise, sometimes up to a level where the noise completely dominates the signal. In this paper, we use the acquisition of photoplethysmography (PPG) signal as an example to demonstrate our proposed algorithm implemented on a sensor array. To increase the chances of acquiring clean PPG signal, we develop a uniform linear sensor array located above the radial artery. We also develop a wearable device to integrate our sensor array and our proposed algorithm. We propose centralized state sensing (CSS), a centralized algorithm suited to our sensor array, to increase the efficiency in multi sensor estimation. To support our proposed algorithm, we use heart rate estimation as an example and compare it with the estimation of a single sensor and the statistical mean of the estimation of multiple sensors. Experimental results demonstrate that our proposal achieve a reduction in mean absolute error of 26.8%, compared to the estimation result obtained using the average of the estimation of all sensors. Operating on a 80 MHz processor, our algorithm introduces a 8 ms overhead, making it highly suitable for wearable devices.