scholarly journals Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 137
Author(s):  
Olli-Pekka Nuuttila ◽  
Elisa Korhonen ◽  
Jari Laukkanen ◽  
Heikki Kyröläinen
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Laboratory Data ◽  
Rr Intervals ◽  
Recreational Athletes ◽  
Natural Logarithm ◽  
Intraclass Correlations ◽  
Measure Heart Rate ◽  
Cardiac Parasympathetic Activity ◽  
Rate Sensor

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11340 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (bias −0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (bias 0.20 ms, p < 0.001) and nocturnal recordings (bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.

Abstract 13500: Association Between Breast Cancer and Cardiac Autonomic Function as Measured by Heart Rate Variability in the Women’s Health Initiative

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Mary Branch ◽  
Christopher L Schaich ◽  
Daniel Beavers ◽  
Elsayed Z Soliman ◽  
Kerryn Reding ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Women's Health ◽  
Rr Intervals ◽  
Women's Health Initiative ◽  
Women’S Health Initiative ◽  
Health Initiative ◽  
Incident Breast Cancer ◽  
The Women’S Health Initiative

Background: Autonomic dysfunction (AD) as measured by heart rate variability (HRV) is associated with increased risk of cardiovascular disease (CVD) and breast cancer. No study has utilized a large prospective multi-center cohort of diverse women to assess differences in HRV associated with incident breast cancer. Objectives: To identify heart rate variability changes in women with breast cancer compared to controls in the Women’s Health Initiative (WHI). Methods: In a retrospective cohort study, we utilized 5,031 women in the WHI CT cohort who were breast cancer free at baseline and compared 1) those with incident breast cancer v. 2) those who were breast cancer free during the ECG follow-up period as controls. HRV was calculated utilizing 10-second ECG with two measures of two-domain HRV: standard deviation of all normal-to-normal RR intervals (SDNN) and the root mean square of successive differences in normal-to-normal RR intervals (rMSSD). HRV was measured from ECGs collected at baseline, years 3, 6, and 9 in the comparison groups. An adjusted mixed linear model was used to evaluate the differences in SDNN and rMSSD comparing women with incident breast cancer to controls. Cardiovascular risk factors utilized in the adjusted model were determined via questionnaire at baseline. Results: At baseline, women with incident breast cancer diagnosed by years 3, 6, or 9 were significantly older (median age 63 vs. 61, P<0.0001) and had a higher prevalence of hypertension (35% vs. 32%, P=0.02). SDNN at years 3 and 6 in women with breast cancer compared to controls was significantly lower (P=0.0002, P=0.03 respectively). As well, rMSSD was significantly lower at year 3 compared to controls (P<0.0001) ( Figure 1 ). Conclusions: HRV as a measure of AD is significantly lower in women with incident breast cancer compared to women without breast cancer. Reduction in HRV is associated with CVD outcomes in the literature. Our study suggests HRV may predict CVD in breast cancer patients.

scholarly journals Validation of the Software-Hardware Complex “Rytm” for Measurement of the RR Intervals and Heart Rate Variability Analysis During Exercise and Recovery Period

2021 ◽  
Vol 21 (1) ◽  
pp. 61-68
Author(s):  
Lyubomyr Vovkanych ◽  
Yuriy Boretsky ◽  
Viktor Sokolovsky ◽  
Dzvenyslava Berhtraum ◽  
Stanislav Kras
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Recovery Period ◽  
Intraclass Correlation ◽  
Step Test ◽  
Heart Rate Variability Analysis ◽  
Test Protocol ◽  
Rr Intervals ◽  
Significant Difference ◽  
Very High

The study purpose was estimation of the accuracy of RR time series measurements by SHC “Rytm” and validity of derived heart rate variability (HRV) indexes under physical loads and recovery period. Materials and methods. The participants were 20 healthy male adults aged 19.7 ± 0.23 years. Data was recorded simultaneously with CardioLab CE12, Polar RS800, and SHC “Rytm”. Test protocol included a 2 minute step test (20 steps per minute, platform height – 40 cm) with the next 3 minute recovery period. HRV indexes were calculated by Kubios HRV 2.1. Results. The RR data bias in the case of physical loads was -0.06 ms, it increased to 0.09-0.33 ms during the recovery period. The limits of agreement for RR data ranged from 3.7 ms to 22.8 ms, depending on the period of measurements and pair of compared devices. It is acceptable for the heart rate and HRV estimation. The intraclass correlation coefficients (0.62–1.00) and Spearman correlation coefficient (0.99) were high enough to suggest very high repeatability of the data. We found no significant difference (p > 0.05) and good correlation (r = 0.94-1.00) between the majority of HRV indexes, calculated from data of Polar RS800 and SHC “Rytm” in conditions of physical loads (except for LF/HF ratio) and in the recovery period. The only one index (RMSSD) was different (p < 0.05) in case of Polar RS800 and SHC “Rytm” data, obtained in the recovery period. The largest numbers of different HRV indexes have been found during the comparison of CardioLab CE12 and Polar RS800 – RMSSD, pNN50, and SD1. Correlation between HRV indexes (r = 0.81-1.00) was very high in all pairs of devices in all periods of measurements. Conclusions. The SHC “Rytm” appears to be acceptable for RR intervals registration and the HRV analysis during physical loads and recovery period.

scholarly journals The influence of type 2 diabetes mellitus on the frequency and complexity of ventricular arrhythmias and heart rate variability in patients after myocardial infarction

2016 ◽  
Vol 73 (11) ◽  
pp. 1050-1055
Author(s):  
Viktor Stoickov ◽  
Marina Deljanin-Ilic ◽  
Dijana Stojanovic ◽  
Stevan Ilic ◽  
Sandra Saric ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Myocardial Infarction ◽  
Type 2 Diabetes ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Type 2 Diabetes Mellitus ◽  
Ventricular Arrhythmias ◽  
Qt Dispersion ◽  
Rr Intervals

Background/Aim. After myocardial infarction arrhythmic cardiac deaths are significantly more frequent compared to non-arrhythmic ones. The aim of the study was to investigate the influence of type 2 diabetes mellitus (T2DM) on the frequency and complexity of ventricular arrhythmias after myocardial infarction. Methods. The study included 293 patients, mean age 59.5 ? 9.21 years, who were at least six months after acute myocardial infarction with the sinus rhythm, without atrioventricular blocks and branch blocks. In the clinical group 95 (32.42%) patients were with T2DM, while 198 (67.57%) patients were without diabetes. All of the patients were subjected to the following procedures: standard ECG according to which the corrected QT dispersion (QTdc) was calculated, exercise stress test, and 24-hour holter monitoring according to which, the four parameters of time domain of heart rate variability (HRV) were analyzed: standard deviation of all normal RR intervals during 24 hours (SDNN), standard deviation of the averages of normal RR intervals in all five-minute segments during 24 hours (SDANN), the square root of the mean of the sum of the squares of differences between adjacent normal (RMS-SD), and percentage of consequtive RR intervals which differed for more than 50 ms during 24 hours (NN > 50 ms). Results. In patients after myocardial infarction, patients with T2DM had significantly higher percentage of frequent and complex ventricular arrhythmias compared to the patients without diabetes (p < 0.001). The patients with T2DM had significantly higher percentage of residual ischemia (p < 0.001), and arterial hypertension (p < 0.001), compared to patients without diabetes. The patients with T2DM had significantly lower values of HRV parameters: SDNN (p < 0.001); SDANN (p < 0.001); RMS-SD (p < 0.001), and NN > 50 ms (p < 0.001), and significantly higher values of QTdc (p < 0.001) compared to the patients without diabetes. Conclusion. The study showed that type 2 diabetes mellitus has significant influence on ventricular arrhythmias, HRV parameters and QT dispersion in patients after myocardial infarction.

Season-Long Heart-Rate Variability Tracking Reveals Autonomic Imbalance in American College Football Players

2021 ◽  
pp. 1-10
Author(s):  
Andrew A. Flatt ◽  
Jeff R. Allen ◽  
Clay M. Keith ◽  
Matthew W. Martinez ◽  
Michael R. Esco
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
College Football ◽  
Time Of Day ◽  
Football Players ◽  
Resting Heart Rate ◽  
Autonomic Imbalance ◽  
Natural Logarithm ◽  
Competitive Season ◽  
Red Flag

Purpose: To track cardiac-autonomic functioning, indexed by heart-rate variability, in American college football players throughout a competitive period. Methods: Resting heart rate (RHR) and the natural logarithm root mean square of successive differences (LnRMSSD) were obtained throughout preseason and ∼3 times weekly leading up to the national championship among 8 linemen and 12 nonlinemen. Seated 1-minute recordings were performed via mobile device and standardized for time of day and proximity to training. Results: Relative to preseason, linemen exhibited suppressed LnRMSSD during camp-style preparation for the playoffs (P = .041, effect size [ES] = −1.01), the week of the national semifinal (P < .001, ES = −1.27), and the week of the national championship (P = .005, ES = −1.16). As a combined group, increases in RHR (P < .001) were observed at the same time points (nonlinemen ES = 0.48–0.59, linemen ES = 1.03–1.10). For all linemen, RHR trended upward (positive slopes, R2 = .02–.77) while LnRMSSD trended downward (negative slopes, R2 = .02–.62) throughout the season. Preseason to postseason changes in RHR (r = .50, P = .025) and LnRMSSD (r = −.68, P < .001) were associated with body mass. Conclusions: Heart-rate variability tracking revealed progressive autonomic imbalance in the lineman position group, with individual players showing suppressed values by midseason. Attenuated parasympathetic activation is a hallmark of impaired recovery and may contribute to cardiovascular maladaptations reported to occur in linemen following a competitive season. Thus, a descending pattern may serve as an easily identifiable red flag requiring attention from performance and medical staff.

Detrended Fluctuation Analysis of Heart Rate Variability in Noise Exposure

2014 ◽  
Vol 1044-1045 ◽  
pp. 1129-1134 ◽  
Author(s):  
Shih Tsung Chen ◽  
Li Ho Tseng ◽  
Yuan Po Lee ◽  
Hong Zhun Wu ◽  
Chia Yi Chou
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Detrended Fluctuation Analysis ◽  
Low Frequency ◽  
Fluctuation Analysis ◽  
Frequency Noise ◽  
Cardiovascular Activity ◽  
Low Frequency Noise ◽  
Rr Intervals ◽  
Detrended Fluctuation

During the past two decades, most studies have employed questionnaires to characterize the effects of noise on behavior and health. Developments in physiological techniques have provided a noninvasive method for recording cardiovascular autonomic activity by using an electrocardiogram (ECG). We investigated cardiovascular activity changes in exposure to exposure to low-frequency noise for various noise intensities by using detrended fluctuation analysis (DFA) of heart rate variability (HRV). We hypothesized that distinct noise intensities would affect cardiovascular activity, which would be reflected in the HRV and DFA parameters. A total of 17 healthy volunteers participated in this study. The test intensities of noises were no noise, 70-dBC, 80-dBC, and 90-dBC. Each noise was sustained for 5 minutes and the ECG was recorded simultaneously. The cardiovascular responses were evaluated using DFA of the beat-to-beat (RR) intervals obtained from ECG signals. The results showed that the mean RR intervals variability and mean blood pressure did not substantially change relative to the noises. However, the short-term scaling exponent (α1) of the DFA of the background noise (no noise) condition was lower than the 70-dBC, 80-dBC and 90-dBC noises (P< 0.05, repeated measures analysis of variance). The α1of 90-dBC noise was significantly higher than the α1of BN condition according to a Mann–Whitney U test (P< 0.01). We concluded that exposure to low-frequency noise significantly affects the temporal correlations of HRV, but it does not influence RR intervals variability.

Determination of minimal recording period to assess resting heart rate variability during pregnancy

2020 ◽  
Vol 45 (4) ◽  
pp. 431-436
Author(s):  
Danilo Fernandes da Silva ◽  
Shuhiba Mohammad ◽  
Kelly Ann Hutchinson ◽  
Kristi Bree Adamo
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Exercise Training ◽  
Pregnant Women ◽  
Resting Heart Rate ◽  
Time Segment ◽  
Natural Logarithm ◽  
Resting Heart Rate Variability ◽  
Measurement Period

Traditionally, resting heart rate variability (rHRV) is measured for 10 min using the last 5 min for analyses (e.g., criterion period). It is unknown whether the measurement period can be shortened in pregnant women as there are currently no established standards. We aimed to compare shorter time segments (e.g., from the 1st to 10th minutes) of the parasympathetic index natural logarithm transformation of root mean square of successive R–R differences (Ln rMSSD) with the criterion period in pregnant and nonpregnant women. Twelve pregnant (age: 30.8 ± 3.4 years; gestational age: 20.1 ± 5.0 weeks) and 15 nonpregnant women (age: 29.8 ± 4.0 years) were included. rHRV was measured using a portable heart rate monitor for 10 min while sitting. Ln rMSSD difference/agreement between shorter time segments and criterion period was analyzed. The result observed between the 4th–5th minutes was the shortest time segment not different from/highly agreed with the criterion period in pregnant women (difference [95% confidence interval (CI)]: −0.10 [−0.22 to 0.02]/bias ± 1.96 × SD: −0.06 [−0.38 to 0.25]). In nonpregnant women, the 2nd–3rd-minute segment was the shortest with similar results (difference [95% CI]: −0.04 [−0.15 to 0.07]/bias ± 1.96 × SD: −0.03 [−0.39 to 0.32]). The Ln rMSSD was found to be stable from the 5th–10th minutes and the 3rd–10th minutes in pregnant and nonpregnant women, respectively. A shortened rHRV assessment can increase its applicability in clinical/exercise-training settings. Novelty Ln rMSSD can be measured for 5 min in pregnant women, with the last 1-min segment analyzed. The last 1-min segment from 3 min can be used for rHRV measurement in nonpregnant women. The shortened rHRV assessment can facilitate its applicability in clinical/exercise-training settings.

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