With the increasing use of wearable technologies (smartphones and smartwatches), it has become possible to measure vital signs outside healthcare institutions without the need for an additional medical device. With the advancement in technologies, the accuracy of vital signs measured by smartphones and smartwatches has also increased. In this study, the accuracy of smart devices in the measurement of heart rate and saturation, which are two vital signs that are difficult to detect in conditions such as hypotension were investigated. The study was prospectively conducted in a tertiary healthcare center. In hypotensive patients who presented to the emergency department (ED) and required an arterial blood gas evaluation, oxygen saturation and heart rate values measured by a smartphone, those measured with a vital signs monitor (VSM) at the time of admission to the ED and oxygen saturation values measured by a blood gas analyzer (BGA) were compared. A total of 200 patients, 117 women and 83 men, were included in the study. It was determined that the correlation coefficients of the heart rate values measured by the vital signs monitor and smartphone were in a high statistical agreement. When the saturation values measured by the vital signs monitor, smartphone, and blood gas analyzer were compared, it was found that the intra-class correlation coefficients of the saturation values measured by the smartphone with reference to the blood gas analyzer and vital signs monitor were 0.957 and 0.949, respectively, indicating an excellent agreement. Smartphones have as high efficiency as reference devices in measuring heart rate and saturation in hypotensive patients. In this way, hypotensive patients who need medical help can also have the opportunity to measure their vital parameters with their smartphones, without the need for any other medical device, before applying to the hospital or emergency health system. This may contribute to the improvement of the quality of life of the patients and the early and accurate information of the health care providers about the patient's health parameters.

In mass casualty incidents, the demand for healthcare services far exceeds existing capacity, underscoring the importance of triage. This study supports drone-based triage by developing and validating algorithms for non-contact vital sign measurement from drone footage. Heart rate was measured by extracting average frame colour values from RGB videos and applying signal processing. Respiratory rate was obtained by analyzing temperature changes in the nasal region. Body temperature was analyzed based on the maximum temperature values in the forehead region’ thermal images. For oxygen saturation measurement, a deep learning model trained with features extracted from thermal images. Thirty-seven participants (mean age: 29.7 ± 8.45 years; 64.9% male) were simultaneously recorded using a drone-mounted camera and monitored with a standard bedside reference monitor, with seven recordings obtained outdoors and 30 indoors. The videos were analyzed by creating 15-second segments for respiratory rate and 13-second segments for the other parameters, with 1-second shifts. The accuracy rates of the oxygen saturation, body temperature, heart rate, and respiratory rate measurement algorithms were 98.65%, 98.59%, 97.70%, and 85.22%, respectively, for indoor recordings, and 99.60%, 98.48%, 96.85%, and 82.83% for outdoor recordings. The mean differences between the image processing–based and reference measurements for indoor recordings were 1.26% for oxygen saturation, 0.19 °C for body temperature, -0.37 breaths/min for respiratory rate, and −0.31 beats/min for heart rate; for outdoor recordings, the corresponding mean differences were 0.34%, 0.27 °C, −0.52 breaths/min, and −0.38 beats/min, respectively. The vital sign measurement algorithms demonstrated strong performance and can be successfully integrated into drone-based triage and other remote monitoring systems.