Real-time pulse oximetry extraction using a lightweight algorithm and a task pipeline scheme

Pulse oximetry is a popular non-invasive method for monitoring the oxygen saturation levels (SpO2) in blood as well as the heart rate (HR) of a patient. The photoplethysmographic signal (PPG) is used to estimate SpO2 and HR. It indicates the light absorption of oxygenated and deoxygenated hemoglobin at a certain wavelength. Red and IR wavelengths are often used to extract PPG signals. Subsequently, various algorithms can be applied to the PPG signals in order to obtain SpO2 and HR. In this paper, we propose a pulse oximetry system in which a lightweight algorithm is applied for HR and SpO2 estimation. Our study was based on PPG signals derived from the MAX30102 sensor. PIC18F46Q43 microcontroller unit (MCU) was selected as the system processor, which was responsible for the sensor readouts and for the implementation of the algorithm. Communication with each external device was accomplished by using Direct Memory Access (DMA) transfers. Furthermore, the required functionality was deployed by adopting a task pipeline firmware scheme. In that scheme, operations were completed in parallel. This technique accelerated the execution and maximized the time in which the MCU can be put in low power mode. Interconnection between our system and a personal computer was also realized by using an external USB-to-serial module. Associated Octave scripts for receiving, analyzing and processing of PPG signal data were also developed.