Inter- and intraindividual variability in daily resting heart rate and its associations with age, sex, sleep, BMI, and time of year: Retrospective, longitudinal cohort study of 92,457 adults

Quer, Giorgio; Gouda, Pishoy; Galarnyk, Michael; Topol, Eric J.; Steinhubl, Steven R.

doi:10.1371/journal.pone.0227709

Cited by 137 publications

(112 citation statements)

References 30 publications

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“…P values of a two-sided Fisher's exact test applied to COVID-19-positive and COVID-19-negative participants are also reported.relatively consistent RHR, for them, that fluctuates by a median of only 3 b.p.m. weekly6 . On the other hand, what would be considered a normal RHR for an individual can vary by as much as 70 b.p.m.…”

mentioning

confidence: 99%

Wearable sensor data and self-reported symptoms for COVID-19 detection

Quer

Radin

Gadaleta

et al. 2020

Nat Med

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393

368

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Traditional screening for COVID-19 typically includes survey questions about symptoms and travel history, as well as temperature measurements. Here, we explore whether personal sensor data collected over time may help identify subtle changes indicating an infection, such as in patients with COVID-19. We have developed a smartphone app that collects smartwatch and activity tracker data, as well as self-reported symptoms and diagnostic testing results, from individuals in the United States, and have assessed whether symptom and sensor data can differentiate COVID-19 positive versus negative cases in symptomatic individuals. We enrolled 30,529 participants between 25 March and 7 June 2020, of whom 3,811 reported symptoms. Of these symptomatic individuals, 54 reported testing positive and 279 negative for COVID-19. We found that a combination of symptom and sensor data resulted in an area under the curve (AUC) of 0.80 (interquartile range (IQR): 0.73-0.86) for discriminating between symptomatic individuals who were positive or negative for COVID-19, a performance that is significantly better (P < 0.01) than a model 1 that considers symptoms alone (AUC = 0.71; IQR: 0.63-0.79). Such continuous, passively captured data may be complementary to virus testing, which is generally a one-off or infrequent sampling assay. Owing to the current lack of fast and reliable testing, one of the greatest challenges for preventing transmission of SARS-CoV-2 is the ability to quickly identify, trace and isolate cases before they can further spread the infection to susceptible individuals. As regions across the United States start implementing measures to reopen businesses, schools and other activities, many rely on current screening practices for COVID-19, which typically include a combination of symptom and travel-related survey questions and temperature measurements. However, this method is likely to miss pre-symptomatic or asymptomatic cases, which make up ~40-45% of those infected with SARS-CoV-2, and who can still be infectious 1,2. An elevated temperature (>100 °F (>37.8 °C)) is not as common as frequently believed, being present in only 12% of individuals who tested positive for COVID-19 3 and just 31% of patients hospitalized with COVID-19 (at the time of admission) 4. Smartwatches and activity trackers, which are now worn by one in five Americans 5 , can improve our ability to objectively characterize each individual's unique baseline for resting heart rate 6 , sleep 7 and activity and can therefore be used to identify subtle changes in that user's data that may indicate that they are coming down with a viral illness. Previous research from our group has shown that this method, when aggregated at the population level, can significantly improve real-time predictions for influenza-like illness 8. Consequently, we created a prospective app-based research platform, called DETECT (Digital Engagement and Tracking for Early Control and Treatment), where individuals can share their sensor data, self-reported symptoms, diagnoses and ele...

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mentioning

confidence: 99%

Wearable sensor data and self-reported symptoms for COVID-19 detection

Quer

Radin

Gadaleta

et al. 2020

Nat Med

Self Cite

393

368

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“…The heartbeat and blood flow of G. holbrooki embryos could be readily visualised, with stable and regular HR for six hours post-removal from the ovarian sac, allowing robust and repeat recordings. Importantly, the range of embryonic HRs of G. holbrooki (42–153 bpm) were much closer to those of normal fetal (110 to 150 bpm) [ 48 ] and adult (60–100 bpm) [ 49 ] humans. In contrast, the HRs of the commonly used model species such as zebrafish (120–180 bpm) and mice (300–600 bpm) [ 37 ] are relatively much higher.…”

Section: Discussionmentioning

confidence: 72%

Embryonic Onset of Sexually Dimorphic Heart Rates in the Viviparous Fish, Gambusia holbrooki

2021

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In fish, little is known about sex-specific differences in physiology and performance of the heart and whether these differences manifest during development. Here for the first time, the sex-specific heart rates during embryogenesis of Gambusia holbrooki, from the onset of the heart rates (HRs) to just prior to parturition, was investigated using light cardiogram. The genetic sex of the embryos was post-verified using a sex-specific genetic marker. Results reveal that heart rates and resting time significantly increase (p < 0.05) with progressive embryonic development. Furthermore, both ventricular and atrial frequencies of female embryos were significantly higher (p < 0.05) than those of their male sibs at the corresponding developmental stages and remained so at all later developmental stages (p < 0.05). In concurrence, the heart rate and ventricular size of the adult females were also significantly (p < 0.05) higher and larger respectively than those of males. Collectively, the results suggest that the cardiac sex-dimorphism manifests as early as late-organogenesis and persists through adulthood in this species. These findings suggest that the cardiac measurements can be employed to non-invasively sex the developing embryos, well in advance of when their phenotypic sex is discernible. In addition, G. holbrooki could serve as a better model to study comparative vertebrate cardiovascular development as well as to investigate anthropogenic and climatic impacts on heart physiology of this species, that may be sex influenced.

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“…We include ten volunteers in our study in order to account for the natural differences between individuals and to ensure a level of robustness in our vital sign extraction methods [ 19 ]. The participants are monitored in varying lying positions while performing simple activities, emulating vital sign variations of real-life sleeping scenarios.…”

Section: Introductionmentioning

confidence: 99%

Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios

Antikainen

Kortelainen

Antropov

et al. 2020

Sensors

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Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of 3.6% (86% correlation) and 9.1% (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.

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Inter- and intraindividual variability in daily resting heart rate and its associations with age, sex, sleep, BMI, and time of year: Retrospective, longitudinal cohort study of 92,457 adults

Cited by 137 publications

References 30 publications

Wearable sensor data and self-reported symptoms for COVID-19 detection

Wearable sensor data and self-reported symptoms for COVID-19 detection

Embryonic Onset of Sexually Dimorphic Heart Rates in the Viviparous Fish, Gambusia holbrooki

Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios

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