Y. Mendelson and G. Comtois (USA)
– Telemedicine, pulse oximeter, adaptive noise cancellation, accelerometry.
The implementation of wearable diagnostic devices would enable real-time remote physiological assessment and facilitate triage of injured persons operating in dangerous and high-risk environments. For example, a wearable pulse oximeter to monitor arterial oxygen saturation (SpO2) and heart rate (HR) could enable field medics to monitor vital physiological information following critical injuries, thereby prioritizing live saving medical intervention. However, since photoplethysmographic (PPG) signals, from which SpO2 and HR measurements are I derived, I are I compromised I during I movements, I the applications of commercially available pulse oximeters require the wearer to remain at rest. This study was undertaken to investigate if accelerometry-based adaptive noise cancellation is effective in minimizing SpO2 and HR errors induced during jogging exercises to simulate artifacts expected to occur in the field. Since transmission-type pulse oximeters utilizing fingertip sensors are highly vulnerable to motion artifacts, measurements were performed using a custom, forehead mounted pulse oximeter. Preliminary tests revealed that processing the motion corrupted PPG signals by a simple least mean squared (LMS) adaptive noise cancellation (ANC) algorithm can improve the signal-to-noise ratio of motion-corrupted PPG signals, thereby reducing SpO2 and HR errors during jogging.
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