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

2021 ◽  
Author(s):  
Aravind Natarajan ◽  
Hao-Wei Su ◽  
Conor Heneghan ◽  
Leanna Blunt ◽  
Corey O'Connor ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Mean Squared Error ◽  
Population Level ◽  
Wearable Devices ◽  
Mean Value ◽  
Heart Beat ◽  
Validation Dataset ◽  
Percentage Error ◽  
Sinus Arrhythmia

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 per minute, 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 per minute to 19.2 per minute with a mean value of 15.4 per minute. Respiratory rate is shown to increase with nocturnal heart rate. It also varies with BMI, reaching a minimum at 25 kg/m^2, 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 coecient 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 per minute higher than the regular rate.

scholarly journals Measurement of respiratory rate using wearable devices and applications to COVID-19 detection

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Aravind Natarajan ◽  
Hao-Wei Su ◽  
Conor Heneghan ◽  
Leanna Blunt ◽  
Corey O’Connor ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Wearable Devices ◽  
Mean Value ◽  
Heart Beat ◽  
Validation Dataset ◽  
Percentage Error ◽  
Sinus Arrhythmia

AbstractWe 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 error = 0.46 min−1, mean absolute percentage error = 3%). We use this respiratory rate algorithm to illuminate two potential applications (a) understanding the distribution of nocturnal respiratory rate as a function of age and sex, and (b) examining changes in longitudinal nocturnal respiratory rate due to a respiratory infection such as COVID-19. 90% of respiratory rate values for healthy adults fall within the range 11.8−19.2 min−1 with 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 from D−1 to D+5 (where D0 is the date when symptoms first present, for symptomatic individuals, and the test date for asymptomatic cases), we find that 36.4% (23.7%) of symptomatic (asymptomatic) individuals had at least one measurement of respiratory rate 3 min−1 higher than the regular rate.

scholarly journals The effect of adenotonsillectomy for childhood sleep apnoea on cardiorespiratory control

2016 ◽  
Vol 2 (2) ◽  
pp. 00003-2016 ◽  
Author(s):  
Mathias Baumert ◽  
Yvonne Pamula ◽  
James Martin ◽  
Declan Kennedy ◽  
Anand Ganesan ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Obstructive Sleep Apnoea ◽  
Respiratory Sinus Arrhythmia ◽  
Sleep Apnoea ◽  
Obstructive Sleep Apnoea Syndrome ◽  
Sinus Arrhythmia ◽  
Cardiorespiratory Control ◽  
Post Surgery ◽  
Obstructive Sleep

The efficacy of adenotonsillectomy for relieving obstructive sleep apnoea symptoms in children has been firmly established, but its precise effects on cardiorespiratory control are poorly understood.In 375 children enrolled in the Childhood Adenotonsillectomy Trial, randomised to undergo either adenotonsillectomy (n=194) or a strategy of watching waiting (n=181), respiratory rate, respiratory sinus arrhythmia and heart rate were analysed during quiet, non-apnoeic and non-hypopnoeic breathing throughout sleep at baseline and at 7 months using overnight polysomnography.Children who underwent early adenotonsillectomy demonstrated an increase in respiratory rate post-surgery while the watchful waiting group showed no change. Heart rate and respiratory sinus arrhythmia were comparable between both arms. On assessing cardiorespiratory variables with regard to normalisation of clinical polysomnography findings during follow-up, heart rate was reduced in children who had resolution of obstructive sleep apnoea syndrome, while no differences in their respiratory rate or respiratory sinus arrhythmia were observed.Adenotonsillectomy for obstructive sleep apnoea increases baseline respiratory rate during sleep. Normalisation of apnoea–hypopnoea index, spontaneously orviasurgery, lowers heart rate. Considering the small average effect size, the clinical significance is uncertain.

scholarly journals Measurement of Heart Rate Using the Polar OH1 and Fitbit Charge 3 Wearable Devices in Healthy Adults During Light, Moderate, Vigorous, and Sprint-Based Exercise: Validation Study (Preprint)

2020 ◽  
Author(s):  
David Joseph Muggeridge ◽  
Kirsty Hickson ◽  
Aimie Victoria Davies ◽  
Oonagh M Giggins ◽  
Ian L Megson ◽  
...  
Keyword(s):  
Heart Rate ◽  
Wearable Devices ◽  
Bicycle Ergometer ◽  
Cycle Ergometer ◽  
Primary Objective ◽  
Healthy Adults ◽  
Mean Absolute Percentage Error ◽  
Percentage Error ◽  
Poor Correlation ◽  
Absolute Percentage Error

BACKGROUND Accurate, continuous heart rate measurements are important for health assessment, physical activity, and sporting performance, and the integration of heart rate measurements into wearable devices has extended its accessibility. Although the use of photoplethysmography technology is not new, the available data relating to the validity of measurement are limited, and the range of activities being performed is often restricted to one exercise domain and/or limited intensities. OBJECTIVE The primary objective of this study was to assess the validity of the Polar OH1 and Fitbit Charge 3 devices for measuring heart rate during rest, light, moderate, vigorous, and sprint-type exercise. METHODS A total of 20 healthy adults (9 female; height: mean 1.73 [SD 0.1] m; body mass: mean 71.6 [SD 11.0] kg; and age: mean 40 [SD 10] years) volunteered and provided written informed consent to participate in the study consisting of 2 trials. Trial 1 was split into 3 components: 15-minute sedentary activities, 10-minute cycling on a bicycle ergometer, and incremental exercise test to exhaustion on a motorized treadmill (18-42 minutes). Trial 2 was split into 2 components: 4 × 15-second maximal sprints on a cycle ergometer and 4 × 30- to 50-m sprints on a nonmotorized resistance treadmill. Data from the 3 devices were time-aligned, and the validity of Polar OH1 and Fitbit Charge 3 was assessed against Polar H10 (criterion device). Validity was evaluated using the Bland and Altman analysis, Pearson moment correlation coefficient, and mean absolute percentage error. RESULTS Overall, there was a very good correlation between the Polar OH1 and Polar H10 devices (<i>r</i>=0.95), with a mean bias of −1 beats·min<sup>-1</sup> and limits of agreement of −20 to 19 beats·min<sup>-1</sup>. The Fitbit Charge 3 device underestimated heart rate by 7 beats·min<sup>-1</sup> compared with Polar H10, with a limit of agreement of −46 to 33 beats·min<sup>-1</sup> and poor correlation (<i>r</i>=0.8). The mean absolute percentage error for both devices was deemed acceptable (&lt;5%). Polar OH1 performed well across each phase of trial 1; however, validity was worse for trial 2 activities. Fitbit Charge 3 performed well only during rest and nonsprint-based treadmill activities. CONCLUSIONS Compared with our criterion device, Polar OH1 was accurate at assessing heart rate, but the accuracy of Fitbit Charge 3 was generally poor. Polar OH1 performed worse during trial 2 compared with the activities in trial 1, and the validity of the Fitbit Charge 3 device was particularly poor during our cycling exercises. CLINICALTRIAL

scholarly journals Cardiorespiratory interactions in humans and animals: rhythms for life

2018 ◽  
Vol 315 (1) ◽  
pp. H6-H17 ◽  
Author(s):  
Maja Elstad ◽  
Erin L. O’Callaghan ◽  
Alex J. Smith ◽  
Alona Ben-Tal ◽  
Rohit Ramchandra
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Physiological Role ◽  
Prognostic Indicator ◽  
Heart Beat ◽  
Cardiorespiratory System ◽  
Sinus Arrhythmia ◽  
The Right ◽  
Work Done

The cardiorespiratory system exhibits oscillations from a range of sources. One of the most studied oscillations is heart rate variability, which is thought to be beneficial and can serve as an index of a healthy cardiovascular system. Heart rate variability is dampened in many diseases including depression, autoimmune diseases, hypertension, and heart failure. Thus, understanding the interactions that lead to heart rate variability, and its physiological role, could help with prevention, diagnosis, and treatment of cardiovascular diseases. In this review, we consider three types of cardiorespiratory interactions: respiratory sinus arrhythmia (variability in heart rate at the frequency of breathing), cardioventilatory coupling (synchronization between the heart beat and the onset of inspiration), and respiratory stroke volume synchronization (the constant phase difference between the right and the left stroke volumes over one respiratory cycle). While the exact physiological role of these oscillations continues to be debated, the redundancies in the mechanisms responsible for its generation and its strong evolutionary conservation point to the importance of cardiorespiratory interactions. The putative mechanisms driving cardiorespiratory oscillations as well as the physiological significance of these oscillations will be reviewed. We suggest that cardiorespiratory interactions have the capacity to both dampen the variability in systemic blood flow as well as improve the efficiency of work done by the heart while maintaining physiological levels of arterial CO2. Given that reduction in variability is a prognostic indicator of disease, we argue that restoration of this variability via pharmaceutical or device-based approaches may be beneficial in prolonging life.

scholarly journals Measurement of Heart Rate Using the Polar OH1 and Fitbit Charge 3 Wearable Devices in Healthy Adults During Light, Moderate, Vigorous, and Sprint-Based Exercise: Validation Study

10.2196/25313 ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. e25313
Author(s):  
David Joseph Muggeridge ◽  
Kirsty Hickson ◽  
Aimie Victoria Davies ◽  
Oonagh M Giggins ◽  
Ian L Megson ◽  
...  
Keyword(s):  
Heart Rate ◽  
Wearable Devices ◽  
Bicycle Ergometer ◽  
Cycle Ergometer ◽  
Primary Objective ◽  
Healthy Adults ◽  
Mean Absolute Percentage Error ◽  
Percentage Error ◽  
Poor Correlation ◽  
Absolute Percentage Error

Background Accurate, continuous heart rate measurements are important for health assessment, physical activity, and sporting performance, and the integration of heart rate measurements into wearable devices has extended its accessibility. Although the use of photoplethysmography technology is not new, the available data relating to the validity of measurement are limited, and the range of activities being performed is often restricted to one exercise domain and/or limited intensities. Objective The primary objective of this study was to assess the validity of the Polar OH1 and Fitbit Charge 3 devices for measuring heart rate during rest, light, moderate, vigorous, and sprint-type exercise. Methods A total of 20 healthy adults (9 female; height: mean 1.73 [SD 0.1] m; body mass: mean 71.6 [SD 11.0] kg; and age: mean 40 [SD 10] years) volunteered and provided written informed consent to participate in the study consisting of 2 trials. Trial 1 was split into 3 components: 15-minute sedentary activities, 10-minute cycling on a bicycle ergometer, and incremental exercise test to exhaustion on a motorized treadmill (18-42 minutes). Trial 2 was split into 2 components: 4 × 15-second maximal sprints on a cycle ergometer and 4 × 30- to 50-m sprints on a nonmotorized resistance treadmill. Data from the 3 devices were time-aligned, and the validity of Polar OH1 and Fitbit Charge 3 was assessed against Polar H10 (criterion device). Validity was evaluated using the Bland and Altman analysis, Pearson moment correlation coefficient, and mean absolute percentage error. Results Overall, there was a very good correlation between the Polar OH1 and Polar H10 devices (r=0.95), with a mean bias of −1 beats·min-1 and limits of agreement of −20 to 19 beats·min-1. The Fitbit Charge 3 device underestimated heart rate by 7 beats·min-1 compared with Polar H10, with a limit of agreement of −46 to 33 beats·min-1 and poor correlation (r=0.8). The mean absolute percentage error for both devices was deemed acceptable (<5%). Polar OH1 performed well across each phase of trial 1; however, validity was worse for trial 2 activities. Fitbit Charge 3 performed well only during rest and nonsprint-based treadmill activities. Conclusions Compared with our criterion device, Polar OH1 was accurate at assessing heart rate, but the accuracy of Fitbit Charge 3 was generally poor. Polar OH1 performed worse during trial 2 compared with the activities in trial 1, and the validity of the Fitbit Charge 3 device was particularly poor during our cycling exercises.

Automated Real-Time Processing of Single Lead Electrocardiogram for Simultaneous Heart Rate and Respiratory Rate Monitoring

2017 ◽  
Vol 11 (2) ◽  
Author(s):  
Disha N. Dutta ◽  
Reshmi Das ◽  
Saurabh Pal
Keyword(s):  
Heart Rate ◽  
Data Acquisition ◽  
Respiratory Rate ◽  
Real Time ◽  
Single Subject ◽  
Sinus Arrhythmia ◽  
Real Time Processing ◽  
Time Processing ◽  
The Subject ◽  
Respiration Signal

In this article, the design and development of a real-time heart rate (HR) and respiratory rate (RR) monitoring device is reported. The proposed device is designed to impose minimum data acquisition hazards on the subject. In standard bedside monitors, HR and RR are derived from electrocardiogram (ECG) and respiration signals, respectively, and different electrodes are required for capturing the 12-lead ECG and respiration via a chest belt, which is cumbersome for patients and healthcare providers. Respiration signal has an impact on ECG due to anatomical proximity of the heart and lung, and ECG is modulated by respiration, a phenomenon known as respiratory sinus arrhythmia (RSA). In the proposed method, the ECG signal is acquired using clip electrodes at the wrists and the respiration signal is extracted from the ECG using an Arduino Uno microcontroller-based real-time processing of ECG. RR is then derived from ECG-derived respiration (EDR). The prototype is tested on healthy subjects and compared to measurements taken using a standard MP45 data acquisition device associated with a Biopac Student Lab (BSL). A mean percentage error of 5.54 ± 8.48% was observed under normal breathing conditions and an error of −3.41 ± 3.27% was observed for a single subject tested under a variety of breathing conditions, such as resting, stair-climbing, and paced breathing. The proposed algorithm can also be used in combination with standard ECG monitoring systems to measure HR and RR, without any data acquisition hazard to the subject.

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

Measures of RSA Suppression, Attentional Control, and Negative Affect Predict Self-Ratings of Executive Functions

2011 ◽  
Vol 25 (4) ◽  
pp. 164-173 ◽  
Author(s):  
Brian Healy ◽  
Aaron Treadwell ◽  
Mandy Reagan
Keyword(s):  
College Students ◽  
Heart Rate ◽  
Regression Analysis ◽  
Individual Differences ◽  
Negative Affect ◽  
Respiratory Sinus Arrhythmia ◽  
Attentional Control ◽  
Executive Processes ◽  
Sinus Arrhythmia ◽  
Low Levels

The current study was an attempt to determine the degree to which the suppression of respiratory sinus arrhythmia (RSA) and attentional control were influential in the ability to engage various executive processes under high and low levels of negative affect. Ninety-four college students completed the Stroop Test while heart rate was being recorded. Estimates of the suppression of RSA were calculated from each participant in response to this test. The participants then completed self-ratings of attentional control, negative affect, and executive functioning. Regression analysis indicated that individual differences in estimates of the suppression of RSA, and ratings of attentional control were associated with the ability to employ executive processes but only when self-ratings of negative affect were low. An increase in negative affect compromised the ability to employ these strategies in the majority of participants. The data also suggest that high attentional control in conjunction with attenuated estimates of RSA suppression may increase the ability to use executive processes as negative affect increases.

The influence of osteopathic correction on the rate of various rhythms of the body

2019 ◽  
pp. 64-71 ◽  
Author(s):  
A. E. Chernikova ◽  
Yu. P. Potekhina
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Age Groups ◽  
Biomechanical Properties ◽  
Dispersion Analysis ◽  
The Body ◽  
Body Tissues ◽  
Age Related ◽  
Significant Difference ◽  
Before And After

Introduction. An osteopathic examination determines the rate, the amplitude and the strength of the main rhythms (cardiac, respiratory and cranial). However, there are relatively few studies in the available literature dedicated to the influence of osteopathic correction (OC) on the characteristics of these rhythms.Goal of research — to study the influence of OC on the rate characteristics of various rhythms of the human body.Materials and methods. 88 adult osteopathic patients aged from 18 to 81 years were examined, among them 30 men and 58 women. All patients received general osteopathic examination. The rate of the cranial rhythm (RCR), respiratory rate (RR) heart rate (HR), the mobility of the nervous processes (MNP) and the connective tissue mobility (CTM) were assessed before and after the OC session.Results. Since age varied greatly in the examined group, a correlation analysis of age-related changes of the assessed rhythms was carried out. Only the CTM correlated with age (r=–0,28; p<0,05) in a statistically significant way. The rank dispersion analysis of Kruskal–Wallis also showed statistically significant difference in this indicator in different age groups (p=0,043). With the increase of years, the CTM decreases gradually. After the OC, the CTM, increased in a statistically significant way (p<0,0001). The RCR varied from 5 to 12 cycles/min in the examined group, which corresponded to the norm. After the OC, the RCR has increased in a statistically significant way (p<0,0001), the MNP has also increased (p<0,0001). The initial heart rate in the subjects varied from 56 to 94 beats/min, and in 15 % it exceeded the norm. After the OC the heart rate corresponded to the norm in all patients. The heart rate and the respiratory rate significantly decreased after the OC (р<0,0001).Conclusion. The described biorhythm changes after the OC session may be indicative of the improvement of the nervous regulation, of the normalization of the autonomic balance, of the improvement of the biomechanical properties of body tissues and of the increase of their mobility. The assessed parameters can be measured quickly without any additional equipment and can be used in order to study the results of the OC.

PENGARUH TINDAKAN MOBILISASI DINI TERHADAP DENYUT JANTUNG DAN FREKUENSI PERNAPASAN PADA PASIEN KRITIS DI ICU RSUD SLEMAN YOGYAKARTA

2019 ◽  
Vol 5 (3) ◽  
pp. 213-223
Author(s):  
Muhamat Nofiyanto ◽  
Tetra Saktika Adhinugraha
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Early Mobilization ◽  
Critical Conditions ◽  
P Value ◽  
Cardiorespiratory Function ◽  
Arterial Blood ◽  
Post Test ◽  
Critical Patients ◽  
Security Standards

Background: Patients with critical conditions in the ICU depend on a variety of tools to support their lifes. Patients’ conditions and and their unstable hemodynamic are challenges for nurses to perform mobilization. Less mobilization in critical patients can cause a variety of physical problems, one of them is cardiorespiratory function disorder. Objective: to investigate differences in heart rate (HR) and respiratory rate (RR) before, during, and immediately after early mobilization. Methods: This study employed quasi experiment with one group pre and post test design. Twenty four respondents were selected based on the criteria HR <110 / min at rest, Mean Arterial Blood Pressure between 60 to 110 mmHg, and the fraction of inspired oxygen <0.6. Early mobilization was performed to the respondents, and followed by assessments on the changes of respiratory rate and heart rate before, during, and immediately after the mobilization. Analysis of differences in this study used ANNOVA. Results: Before the early mobilization, mean RR was 22.54 and mean HR was 78.58. Immediately after the mobilization,  mean RR was 23.21 and mean HR was 80.75. There was no differences in the value of RR and HR, before and immediately after the early mobilization with the p-value of 0.540 and 0.314, respectively. Conclusions: Early mobilization of critical patients is relatively safe. Nurses are expected to perform early mobilization for critical patients. However, it should be with regard to security standards and rigorous assessment of the patient's conditions. Keywords: Early mobilization, critical patients, ICU

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