Active noise cancellation using MEMS accelerometers for motion-tolerant wearable bio-sensors

Abstract

An active noise cancellation method using a MEMS accelerometer is developed for recovering corrupted wearable sensor signals due to body motion. The method is developed for a finger ring PPG sensor, the signal of which is susceptive to the hand motion of the wearer. A MEMS accelerometer (ACC) imbedded in the PPG sensor detects the hand acceleration, and is used for recovering the corrupted PPG signal. The correlation between the acceleration and the distorted PPG signal is analyzed, and a low-order FIR model relating the signal distortion to the hand acceleration is obtained. The model parameters are identified in real time with a recursive least square method. Experiments show that the active noise cancellation method can recover ring PPG sensor signals corrupted with 2G of acceleration in the longitudinal direction of the digital artery.