ABSTRACT
Continuous monitoring of blood oxygen saturation (SpO2) level and heart rate is critical in surgery, ICUs and patients suffering from Chronic Obstructive Pulmonary Diseases. Pulse oximeters which compute SpO2 using transmittance photoplethysmography (PPG), is widely accepted for continuous monitoring. Presence of motion artifacts in PPG signals is a major obstacle in the extraction of reliable cardiovascular parameters, in real time and continuous monitoring applications. In this paper, a wrist worn device with a custom finger probe with an integrated accelerometer to remove motion artifacts is presented. An algorithm which can run on low power systems with processing constraints is implemented on the device. The device does continuous acquisition of PPG and accelerometer waveforms and computes SpO2 using the proposed light weight algorithm. The measurement results are continuously synced with an Android tablet, which acts as a gateway and is pushed on to the cloud for further analysis. The accuracy in SpO2 measured by the device was validated using Fluke ProSim 8 SpO2 simulator and the efficiency in accurately computing SpO2 in the presence of motion was validated over 40 healthy volunteers in a controlled setting.
