Faculty Advisor or Committee Member
Yitzhak Mendelson, Advisor
Faculty Advisor or Committee Member
Dr. R. James Duckworth, Committee Member
Faculty Advisor or Committee Member
Dr. Glenn R. Gaudette, Committee Member
Identifier
etd-083107-202452
Abstract
"A wireless wearable battery-operated pulse oximeter has been developed in our laboratory for field triage applications. The wearable pulse oximeter, which uses a forehead-mounted sensor to provide arterial oxygen saturation (SpO2) and heart rate (HR) information, would enable field medics to monitor vital physiological information following critical injuries, thereby helping to prioritize life saving medical interventions. This study was undertaken to investigate if accelerometry (ACC)-based adaptive noise cancellation (ANC) is effective in minimizing SpO2 and HR errors induced during jogging to simulate certain motion artifacts expected to occur in the field. Preliminary tests confirmed that processing the motion corrupted photoplethysmographic (PPG) signals by simple Least-Mean-Square (LMS) and Recursive Least-Squares (RLS) ANC algorithms can help to improve the signal-to-noise ratio of motion-corrupted PPG signals, thereby reducing SpO2 and HR errors during jogging. The study showed also that the degree of improvement depends on filter order. In addition, we found that it would be more feasible to implement an LMS adaptive filter within an embedded microcontroller environment since the LMS algorithm requires significantly less operations."
Publisher
Worcester Polytechnic Institute
Degree Name
MS
Department
Biomedical Engineering
Project Type
Thesis
Date Accepted
2007-08-31
Copyright Statement
All authors have granted to WPI a nonexclusive royalty-free license to distribute copies of the work. Copyright is held by the author or authors, with all rights reserved, unless otherwise noted. If you have any questions, please contact wpi-etd@wpi.edu.
Accessibility
Unrestricted
Repository Citation
Comtois, Gary W., "Implementation of Accelerometer-Based Adaptive Noise Cancellation in a Wireless Wearable Pulse Oximeter Platform for Remote Physiological Monitoring and Triage" (2007). Masters Theses (All Theses, All Years). 1005.
https://digitalcommons.wpi.edu/etd-theses/1005
Subjects
remote physiological monitoring, wearable pulse oximetry, adaptive noise cancellation, motion artifact