Objective We investigated how a commercially available smartwatch that measures peripheral blood oxygen saturation (SpO2) can detect hypoxemia compared to a medical-grade pulse oximeter. Methods We recruited 24 healthy participants. Each participant wore a smartwatch (Apple Watch Series 6) on the left wrist and a pulse oximeter sensor (Masimo Radical-7) on the left middle finger. The participants breathed via a breathing circuit with a three-way non-rebreathing valve in three phases. First, in the 2-minute initial stabilization phase, the participants inhaled the ambient air. Then in the 5-minute desaturation phase, the participants breathed the oxygen-reduced gas mixture (12% O2), which temporarily reduced their blood oxygen saturation. In the final stabilization phase, the participants inhaled the ambient air again until SpO2 returned to normal values. Measurements of SpO2 were taken from the smartwatch and the pulse oximeter simultaneously in 30-s intervals. Results There were 642 individual pairs of SpO2 measurements. The bias in SpO2 between the smartwatch and the oximeter was 0.0% for all the data points. The bias for SpO2 less than 90% was 1.2%. The differences in individual measurements between the smartwatch and oximeter within 6% SpO2 can be expected for SpO2 readings 90%–100% and up to 8% for SpO2 readings less than 90%. Conclusions Apple Watch Series 6 can reliably detect states of reduced blood oxygen saturation with SpO2 below 90% when compared to a medical-grade pulse oximeter. The technology used in this smartwatch is sufficiently advanced for the indicative measurement of SpO2 outside the clinic. Trial Registration ClinicalTrials.gov NCT04780724

Photoplethysmography signal (PPG) provides information about the cardiovascular, respiratory, or nervous system activity. Recent studies proposed methods of apnea identification from PPG using amplitude or baseline modulation, or area under the curve. We hypothesized that analysis of the dicrotic notch could improve the sensitivity and specificity of apnea detection. We applied four methods to detect apnea from PPG records experimentally obtained from 10 volunteers, where each volunteer simulated three apneic pauses. We adopted the Area under the PPG and Pulse wave amplitude parameters, and we proposed the Dicrotic notch area parameter. For the methods, we determined the delay in apnea detection and the sensitivity and specificity of apnea detection. The average delay in detecting an apneic pause from the PPG using the Dicrotic notch area was 6.1 s. Combining the parameters of the Area under the PPG with the Dicrotic notch area increased the specificity of apnea detection from 73.8% to 80.0%, although sensitivity decreased from 91.1% to 85.6%. The newly proposed parameter Dicrotic notch area showed its potential for automatic apnea detection.

A pulse oximeter model linking arterial (SaO2) and peripheral (SpO2) oxygen saturation is the terminal part of a mathematical model of neonatal oxygen transport. Previous studies have confirmed the overestimation of oxygen saturation measured by pulse oximetry in neonates compared to arterial oxygen saturation and the large variability of measured values over time caused by measurement inaccuracies. This work aimed to determine the SpO2 measurement noise that affects the biased SpO2 value at each time point and integrate the noise description with the systematic bias between SaO2 and SpO2. The SaO2–SpO2 bias was based on previously published clinical data from pathological patients younger than 60 days requiring ventilatory support. The statistical properties of the random SpO2 measurement noise were estimated from the SpO2 continuous recordings of 21 pathological and 21 physiological neonates. The result of the work is a comprehensive characterization of the properties of a pulse oximeter model describing the transfer of the input SaO2 value to the output SpO2 value, including the bias and noise typical for the bedside monitoring of neonates. These results will help to improve a computer model of neonatal oxygen transport.

A model of the pulse oximeter, which consists of a transfer function between arterial and peripheral blood oxygen saturation (SpO2) and the noise typical for SpO2 records, is an important part of a mathematical model of oxygenation in neonates that is designed to test and compare different algorithms of oxygen control. The noise level in the SpO2 signal is affected by the averaging time setting of the pulse oximeter. This study aimed to characterize the noise level in the SpO2 signal at the set pulse oximeter averaging times of 2- 4, 8, and 16 seconds. We evaluated SpO2 records of 17 healthy volunteers who underwent a laboratory experiment in which they evoked different types of artifacts. The noise level in the SpO2 signal was characterized by two parameters, the deviation of SpO2 from the true value and the SpO2 time stability, defined as the interval during which the measured SpO2 value remained unchanged. Statistical properties of the noise level for the three averaging times were represented by normalized histograms of both the parameters and varied according to the type of artifact. With motion artifacts, the SpO2 readings deviated from the true value by more than ±2% SpO2 in 10%, 7%, or 5% of the measurements when the set averaging time was 2-4 s, 8 s, or 16 s. The length of the interval over which the SpO2 value remained unchanged was most frequently 2 seconds for all set averaging times. Implementation of the noise characteristics into the computer model of oxygenation in neonates will allow more faithful simulations of the output SpO2 signal that better match clinical observations.