Clinical performance of infrared consumer-grade thermometers.

BACKGROUND AND PURPOSE: Technology of ear infrared (IR) thermometers has improved. This study compared a modern ear thermometer to forehead or temporal artery thermometers. METHODS: Temperatures were measured with a heated-tip ear thermometer, a temporal artery thermometer, 3 forehead thermometers, and a thermistor-based reference thermometer in monitor mode. RESULTS: In 171 subjects, mean bias with the forehead thermometers was significantly higher (p < .001) than with the ear thermometer (0.01 degrees C +/- 0.41 degrees C). In 64 febrile subjects, bias with the ear thermometer was significantly lower than with 3 of the other thermometers. A false-negative reading was less likely with the ear thermometer (8%) versus the others (55%, 56%, 28%, and 47%). CONCLUSIONS: Modem ear thermometry provides more precise measurements closer to those of a reference thermometer and is less likely to give false-negative readings than forehead or temporal artery measurements.

Optimizing the input feature sets and machine learning algorithms for reliable and accurate estimation of continuous, cuffless blood pressure.

The advent of mobile devices, wearables and digital healthcare has unleashed a demand for accurate, reliable, and non-interventional ways to measure continuous blood pressure (BP). Many consumer products claim to measure BP with a cuffless device, but their lack of accuracy and reliability limit clinical adoption. Here, we demonstrate how multimodal feature datasets, comprising: (i) pulse arrival time (PAT); (ii) pulse wave morphology (PWM), and (iii) demographic data, can be combined with optimized Machine Learning (ML) algorithms to estimate Systolic BP (SBP), Diastolic BP (DBP) and Mean Arterial Pressure (MAP) within a 5 mmHg bias of the gold standard Intra-Arterial BP, well within the acceptable limits of the IEC/ANSI 80601-2-30 (2018) standard. Furthermore, DBP's calculated using 126 datasets collected from 31 hemodynamically compromised patients had a standard deviation within 8 mmHg, while SBP's and MAP's exceeded these limits. Using ANOVA and Levene's test for error means and standard deviations, we found significant differences in the various ML algorithms but found no significant differences amongst the multimodal feature datasets. Optimized ML algorithms and key multimodal features obtained from larger real-world data (RWD) sets could enable more reliable and accurate estimation of continuous BP in cuffless devices, accelerating wider clinical adoption.

Threshold for defining fever varies with age, especially in children: A multi-site diagnostic accuracy study.

AIM: The American Academy of Pediatrics and the European Centre for Pediatric and Adolescent Medicine guideline define fever as a temperature >38.0°C for all ages and recommend use of rectal thermometers in children <3 years. Based on new literature, this definition of fever using a fixed threshold of 38.0°C needs to be re-examined. DESIGN: A multi-site diagnostic accuracy study was conducted to compare an "age-based" threshold model with a "fixed" threshold over 38.0°C on a total of 894 patients of which 373 were ill. METHODS: The "age-based" and "fixed" threshold fever determinations were then compared to a clinical categorization ("well" or "ill") conducted by a clinician through a comprehensive examination. RESULTS: The sensitivity and accuracy for the age-based thresholds were found to be superior to the fixed thresholds in all ages and current ear thermometers were found equivalent to rectal thermometers in infants <6 months.

Evaluation of key design parameters for mitigating motion artefact in the mobile reflectance PPG signal to improve estimation of arterial oxygenation.

OBJECTIVE: Pulse oximetry, a widely accepted method for non-invasive estimation of arterial oxygen saturation (SpO2) and pulse rate (PR), is increasingly being adapted for mobile applications. Previous work in mitigating motion artefact, which corrupts the photoplethysmogram (PPG) used in pulse oximetry, has focused on reducing noise using signal processing algorithms or through sensor design that controlled only one variable at a time. In this work, we have investigated the effect of several variables such as sensor weight, relative motion, placement, and contact force against the skin that can impact motion artefact independently or by interacting with each other. APPROACH: We have identified a unique combination of these variables that is most optimal in reducing motion artefacts using a full factorial design of experiments methodology and evaluated the effect of these factors on PPG readings with and without motion. MAIN RESULTS: Data collected on 10 diverse subjects showed that placement (p = 0.03), contact force (p = 0.004), and sensor-to-skin adhesion or relative motion when combined with force (p < 0.001) had the most significant effect on reducing the motion artefact signal. Sensor weight (p = 0.822) by itself had no significant effect, however when combined with sensor adhesion (p < 0.001) had a significant impact. SIGNIFICANCE: This lays the foundation for future development of more robust sensors that can significantly reduce the effect of motion artefacts in reflectance-based pulse oximetry and could have great clinical value due to significant reduction of SpO2 errors and false alarms associated with motion artefact, making wearable pulse oximetry more reliable in mobile applications.