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17 May 2005 Active motion artifact cancellation for wearable health monitoring sensors using collocated MEMS accelerometers
Peter T. Gibbs; Levi B. Wood; H. Harry Asada
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Proceedings Volume 5765, Smart Structures and Materials 2005: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems; (2005) https://doi.org/10.1117/12.600781
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2005, San Diego, California, United States
Abstract
This paper presents an active noise cancellation technique for recovering wearable biosensor signals corrupted by bodily motion. A finger mounted photoplethysmograph (PPG) ring sensor with a collocated MEMS accelerometer is considered. The system by which finger acceleration disturbs PPG output is identified and a means of modeling this relationship is prescribed using either FIR or Laguerre models. This means of modeling motivates the use of a recursive least squares active noise cancellation technique using the MEMS accelerometer reading as an input for a FIR or Laguerre model. The model parameters are identified and tuned in real time to minimize the power of the recovered PPG signal. Experiments show that the active noise cancellation method can recover pulse information from PPG signals corrupted with up to 2G of acceleration with 85% improvement in mean squared error.
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Peter T. Gibbs, Levi B. Wood, and H. Harry Asada "Active motion artifact cancellation for wearable health monitoring sensors using collocated MEMS accelerometers", Proc. SPIE 5765, Smart Structures and Materials 2005: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (17 May 2005); https://doi.org/10.1117/12.600781
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