Noncontact Longitudinal Respiratory Rate Measurements in Healthy Adults Using Radar-Based Sleep Monitor (Somnofy): Validation Study

Abstract

Background Respiratory rate (RR) is arguably the most important vital sign to detect clinical deterioration. Change in RR can also, for example, be associated with the onset of different diseases, opioid overdoses, intense workouts, or mood. However, unlike for most other vital parameters, an easy and accurate measuring method is lacking. Objective This study aims to validate the radar-based sleep monitor, Somnofy, for measuring RRs and investigate whether events affecting RR can be detected from personalized baselines calculated from nightly averages. Methods First, RRs from Somnofy for 37 healthy adults during full nights of sleep were extensively validated against respiratory inductance plethysmography. Then, the night-to-night consistency of a proposed filtered average RR was analyzed for 6 healthy participants in a pilot study in which they used Somnofy at home for 3 months. Results Somnofy measured RR 84% of the time, with mean absolute error of 0.18 (SD 0.05) respirations per minute, and Bland-Altman 95% limits of agreement adjusted for repeated measurements ranged from –0.99 to 0.85. The accuracy and coverage were substantially higher in deep and light sleep than in rapid eye movement sleep and wake. The results were independent of age, sex, and BMI, but dependent on supine sleeping position for some radar orientations. For nightly filtered averages, the 95% limits of agreement ranged from −0.07 to −0.04 respirations per minute. In the longitudinal part of the study, the nightly average was consistent from night to night, and all substantial deviations coincided with self-reported illnesses. Conclusions RRs from Somnofy were more accurate than those from any other alternative method suitable for longitudinal measurements. Moreover, the nightly averages were consistent from night to night. Thus, several factors affecting RR should be detectable as anomalies from personalized baselines, enabling a range of applications. More studies are necessary to investigate its potential in children and older adults or in a clinical setting.

Reliable Contactless Monitoring of Heart Rate, Breathing Rate and Breathing Disturbance During Sleep in Aging: A Digital Health Technology Evaluation Study

“…In the evaluation conducted by Ranta et al, in a population of 34 participants with a median age of 32 years, the Emfit had an MAE of 1.34 bpm for heart rate and a MAE of 0.59 cpm for breathing rate [33]. In contrast, in the evaluation conducted by Toften et al, Somnofy had an MAE of 0.18 cpm in a population of 37 participants with a mean age of 32.6 years [32]. Although the vital signs estimates of WSA have been used in large scale studies, there is no existing evaluation of WSA estimated vital signs in the literature to the best of our knowledge [52, 53].…”

“…To realise the potential of contactless technologies for monitoring vital signs such as heart rate and breathing rate in the community, the accuracy and reliability of their measurements need to be evaluated in relevant populations. While the validity of the heart rate and breathing rate estimates collected from a few contactless technologies has been evaluated in younger populations, to the best of our knowledge, there are no vital signs evaluation studies in older adults (> 65 years) although these devices have been implemented in longitudinal studies [13,30,[32][33][34]. Here, we have evaluated the accuracy of heart rate and breathing rate measurements collected from three contactless technologies (a bedside radar and two undermattress devices) against polysomnography (PSG) electrocardiogram (ECG) derived heart rate and respiratory inductance plethysmography thorax (RIP thorax) derived breathing rate in a laboratory setting.…”

Agreement between Vital Signs Measured Using Mat-Type Noncontact Sensors and Those from Conventional Clinical Assessment

“…In recent years, noncontact sensor technology has been developed to address these issues and enable continuous monitoring of vital signs [ 12 , 13 , 14 ]. Noncontact sensors used for vital sign monitoring include cameras [ 15 ], radar [ 16 ], and thermography [ 17 ]. These sensors need to record the movement of the patient’s thorax and facial condition, and the less obstruction between the sensor and the body, the better.…”