"Non-invasive remote physiological monitoring of soldiers on the battlefield has the potential to provide fast, accurate status assessments that are key to improving the survivability of critical injuries. The development of WPIâ€™s wearable wireless pulse oximeter, designed for field-based applications, has allowed for the optimization of important hardware features such as physical size and power management. However, software-based digital signal processing (DSP) methods are still required to perform physiological assessments. This research evaluated DSP methods that were capable of providing arterial oxygen saturation (SpO2), heart rate (HR), heart rate variability (HRV), and respiration rate (RR) measurements derived from data acquired using a single optical sensor. In vivo experiments were conducted to evaluate the accuracies of the processing methods across ranges of physiological conditions. Of the algorithms assessed, 13 SpO2 methods, 1 HR method, 6 HRV indices, and 4 RR methods were identified that provided clinically acceptable measurement accuracies and could potentially be employed in a wearable pulse oximeter."
Worcester Polytechnic Institute
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Johnston, William S., "Development of a Signal Processing Library for Extraction of SpO2, HR, HRV, and RR from Photoplethysmographic Waveforms" (2006). Masters Theses (All Theses, All Years). 919.
wearable medical sensors, arterial oxygen saturation, software development, embedded systems, heart rate, respiration rate, heart rate variability, pulse oximetry, digital signal processing, Pulse oximeters, Design and construction, Signal processing, Digital techniques