Quantitative real-time pulse oximetry with ultrafast frequency-domain diffuse optics and deep neural network processing.

Abstract

Pulse oximetry is a ubiquitous optical technology, widely used for diagnosis and treatment guidance. Current pulse oximeters provide indications of arterial oxygen saturation. We present here a new quantitative methodology that extends the capability of pulse oximetry and provides real-time molar concentrations of oxy- and deoxy-hemoglobin at rates of up to 27 Hz by using advanced digital hardware, real-time firmware processing, and ultra-fast optical property calculations with a deep neural network (DNN). The technique utilizes a high-speed frequency domain spectroscopy system with five frequency-multiplexed wavelengths. High-speed demultiplexing and data reduction were performed in firmware. The DNN inversion algorithm was benchmarked as five orders of magnitude faster than conventional iterative methods for optical property extractions. The DNN provided unbiased optical property extractions, with an average error of 0 ± 5.6% in absorption and 0 ± 1.4% in reduced scattering. Together, these improvements enabled the measurement, calculation, and real-time continuous display of hemoglobin concentrations. A proof-of-concept cuff occlusion measurement was performed to demonstrate the ability of the device to track oxy- and deoxy-hemoglobin, and measure quantitative photoplethysmographic changes during the cardiac cycle. This technique substantially extends the capability of pulse oximetry and provides unprecedented real-time non-invasive functional information with broad applicability for cardiopulmonary applications.