Measurement of Respiratory Rate using Wearable Devices and Applications to COVID-19 Detection

Abstract We show that heart rate enabled wearable devices can be used to measure respiratory rate. Respiration modulates the heart rate creating excess power in the heart rate variability at a frequency equal to the respiratory rate, a phenomenon known as respiratory sinus arrhythmia. We isolate this component from the power spectral density of the heart beat interval time series, and show that the respiratory rate thus estimated is in good agreement with a validation dataset acquired from sleep studies (root mean squared error = 0.648 min−1, mean absolute percentage error = 3%). Using the same respiratory rate algorithm, we investigate population level characteristics by computing the respiratory rate from 10,000 individuals over a 14 day period, with equal number of males and females ranging in age from 20 - 69 years. 90% of respiratory rate values for healthy adults fall within the range 11.8 min−119.2 min−1with a mean value of 15.4 min−1. Respiratory rate is shown to increase with nocturnal heart rate. It also varies with BMI, reaching a minimum at 25 kg/m2, and increasing for lower and higher BMI. The respiratory rate decreases slightly with age and is higher in females compared to males for age < 50 years, with no difference between females and males thereafter. The 90% range for the coefficient of variation in a 14 day period for females (males) varies from 2.3%−9.2% (2.3%−9.5%) for ages 20−24 yr, to 2.5%−16.8% (2.7%−21.7%) for ages 65−69 yr. We show that respiratory rate is often elevated in subjects diagnosed with COVID-19. In a 7 day window centered on the date when symptoms present (or the test date for asymptomatic cases), we find that 33% (18%) of symptomatic (asymptomatic) individuals had at least one measurement of respiratory rate 3 min−1higher than the regular rate..

Medienart:

Preprint

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

bioRxiv.org - (2022) vom: 27. Dez. Zur Gesamtaufnahme - year:2022

Sprache:

Englisch

Beteiligte Personen:

Natarajan, Aravind [VerfasserIn]
Su, Hao-Wei [VerfasserIn]
Heneghan, Conor [VerfasserIn]
Blunt, Leanna [VerfasserIn]
O’Connor, Corey [VerfasserIn]
Niehaus, Logan [VerfasserIn]

Links:

Volltext [lizenzpflichtig]
Volltext [kostenfrei]

Themen:

570
Biology

doi:

10.1101/2021.05.15.21257200

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI020570929