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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
