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 Accuracy of Determining the Duration of Cardiointervals when Using the Hardware-Software Complex "Rhythm" in Conditions of Physical Activity

2020 ◽  
Vol 5 (6) ◽  
pp. 342-348
Author(s):  
L. S. Vovkanych ◽  
◽  
V. M. Sokolovskii ◽  
Y. R. Boretskii ◽  
D. I. Berhtraum ◽  
...  
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Wilcoxon Test ◽  
Step Test ◽  
Human Organism ◽  
Rr Intervals ◽  
Hardware Complex ◽  
Significant Difference ◽  
Good Agreement

The important task for modern physiology is remote monitoring of the functions of physiological systems of the human organism during the competitive and training activity. It is well known that analysis of heart rate variability is one of the effective methods to evaluate the physiological changes which occur in the response to physical loads. In order to perform the correct analysis of heart rate variability by newly designed devices, it is necessary to confirm the sufficient level of accuracy in the registration of RR intervals. The purpose of our research was to analyze the accuracy of RR time series measurements by software-hardware complex “Rytm” and validity of subsequently calculated heart rate variability indexes in conditions of exercise performance. Material and methods. The study involved 20 healthy male adults 20-21 years old. Recording of cardio intervals was performed simultaneously with «Polar RS800», and software-hardware complex “Rytm”. The subjects performed a step test in a rate of 20 steps per minute, platform height – 40 cm, duration – 2 minutes. Results and discussion. Heart rate variability indexes were calculated by Kubios HRV 2.1 software. The totally 4707 pairs of RR intervals were analyzed. The average bias between the RR interval, registered by software-hardware complex «Rytm» and «Polar RS800», was only 0.06 s. We revealed the narrow Bland–Altman limits of agreement (3.72 − -3.83 ms) and the highest value of the intraclass correlation coefficient (1.000) between the data of these two devices. The Bland–Altman plot confirmed good agreement between the devices in the measurements of RR intervals. At the same time, the significant difference (p = 0.002) of the two data sets was found according to paired Wilcoxon test. As the final goal of the registration of RR time series is calculation of individual heart rate variability indexes, we intended to test the presence of substantial differences in the heart rate variability indexes, derived from the data from two devices − «Polar RS800» and software-hardware complex «Rytm». We compared the results of time-domain (HR, STD RR, RMSSD, pNN50), frequency-domain (VLF, LF, HF, LF / HF) and nonlinear (RR tri index, SD1, SD2) analysis of heart rate variability. It was found that only for the LF/HF ratio a statistically significant difference was present. Conclusion. The results suggest the good agreement between most of the heart rate variability indexes based on data of software-hardware complex «Rytm» and well approved heart rate monitoring systems («Polar RS800»)

scholarly journals Investigation of Cardiovascular Endurance Levels of Sedentary High School Students

2018 ◽  
Vol 6 (5) ◽  
pp. 144
Author(s):  
Betül Akyol ◽  
Kayhan Söğüt
Keyword(s):  
High School ◽  
Heart Rate ◽  
High School Students ◽  
Oxygen Saturation ◽  
Recovery Period ◽  
Step Test ◽  
School Students ◽  
Walking Test ◽  
Cardiovascular Endurance ◽  
Significant Difference

The aim of our study is to examine the cardiovascular endurance systems of sedentary high school students. The 112 sedentary individual was taken to the 1600 meter walking test run, and the 120 sedentary individual Harward step test. While both individuals were participating in the same test, weight, height, oxygen saturation, and heart rate of participants were measured before starting the test. As soon as the test is finished (recovery period), oxygen saturation and heart rate variability of individuals are measured at 1, 3, 5 minutes. All measured variables were analyzed and compared. Analysis of the data was done according to the SPSS statistical program and the significance level was accepted as p <0.05. In the 1600-meter walking test, it was observed that there was a significant difference in mean heart rate between males and females p<0.05. There was a significant difference between the mean values of the time of completion of the 1600 m running test by males and females (p < 0.05). During the 1600-meter walking and Harward step test recovery period, there was no difference in the participants' parameters. There was no significant difference between oxygen saturations at beginning, recovery 1st, 3rd, and 5th minutes in both tests. Significant differences were found between heart rate and oxygen saturation values (beginning, recovery 1st, 3rd, and 5th minutes) in the intra-group comparisons of both groups. Participants' heart rates began to increase with exercise, but remained above the initial heart rate level during recovery. Participants' body mass indexes were observed to be within normal values. We think that can be increased cardio respiratory and cardiovascular fitness levels and can been created lifelong exercise habits by regular exercise programs are given to Sedentary high school students. Thus, we believe that the young population can be prevented from getting sick by providing healthier, social, active individuals.

Reproducibility of Heart Rate Variability Threshold in Untrained Individuals

2018 ◽  
Vol 40 (02) ◽  
pp. 95-99 ◽  
Author(s):  
Fabiula Novelli ◽  
Jaqueline de Araújo ◽  
Geovane Tolazzi ◽  
Gabriel Tricot ◽  
Gisela Arsa ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Exercise Test ◽  
Perceived Exertion ◽  
Intraclass Correlation ◽  
Physical Effort ◽  
Incremental Exercise Test ◽  
Significant Difference ◽  
High Intraclass Correlation Coefficient ◽  
Cardiac Modulation

AbstractThe aim of this study was to evaluate the reproducibility of the heart rate variability threshold (HRVT) by different HRV indexes and determination criteria. 68 untrained participants, 17 women (24.09±4.91 years old; 21.54±1.97 kg∙m−2) and 51 men (24.52±3.52 years old; 26.51±6.31 kg∙m−2), were evaluated on 2 different days (test and retest). The HRVT was determined during an incremental exercise test using 2 indexes (SD1 and RMSSD) and criteria (HRTV1, first intensity of physical effort with index<3 ms, and HRVT2, first intensity of physical effort, in which the index presents a difference<1 ms between 2 consecutive intensities). There was no significant difference (p<0.05) between the test and retest for any of the variables evaluated. All variables, except for the rate of perceived exertion at HRVT2, presented moderate to high intraclass correlation coefficient (HRVT1: 0.55–0.85 and HRVT2:0.58–0.69). All variables at HRVT1 and the heart rate at HRVT2 showed coefficient of variation ~ 10%. The HRVT, regardless of criteria and HRV index used, showed satisfactory reproducibility. Thus, these criteria can be used to assess clinically autonomic cardiac modulation and aerobic capacity, and to analyze the effect of different interventions.

Validity of a Smartphone Application and Chest Strap for Recording RR Intervals at Rest in Athletes

2020 ◽  
Vol 15 (6) ◽  
pp. 896-899
Author(s):  
Reabias de A. Pereira ◽  
José Luiz de B. Alves ◽  
João Henrique da C. Silva ◽  
Matheus da S. Costa ◽  
Alexandre S. Silva
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Time Domain ◽  
High Frequency ◽  
Low Frequency ◽  
Smartphone Application ◽  
Smartphone App ◽  
Heart Rate Variability Analysis ◽  
Rr Intervals

Objective: To evaluate the accuracy of the smartphone application (app) HRV Expert (CardioMood) and a chest strap (H10 Polar) for recording R-R intervals compared with electrocardiogram (ECG). Methods: A total of 31 male recreational runners (age 36.1 [6.3] y) volunteered for this study. R-R intervals were recorded simultaneously by the smartphone app and ECG for 5 minutes to analyze heart-rate variability in both the supine and sitting positions. Time-domain indexes (heart rate, mean R-R, SD of RR intervals, count of successive normal R-R intervals differing by more than 50 ms, percentage of successive normal R-R intervals differing by more than 50 ms, and root mean square of successive differences between normal R-R intervals), frequency-domain indexes (low frequency, normalized low frequency, high frequency, normalized high frequency, low-frequency to high-frequency ratio, and very low frequency), and nonlinear indexes (SD of instantaneous beat-to-beat variability and long-term SD of continuous R-R intervals) were compared by unpaired t test, Pearson correlation, simple linear regression, and Bland–Altman plot to evaluate the agreement between the devices. Results: High similarity with P value varying between .97 and 1.0 in both positions was found. The correlation coefficient of the heart-rate-variability indexes was perfect (r = 1.0; P = .00) for all variables. The constant error, standard error of estimation, and limits of agreement between ECG and the smartphone app were considered small. Conclusion: The smartphone app and chest strap provide excellent ECG compliance for all variables in the time domain, frequency domain, and nonlinear indexes, regardless of the assessed position. Therefore, the smartphone app replaces ECG for any heart-rate-variability analysis in runners.

scholarly journals Reliability of low electrocardiogram sampling frequencies for short-term heart rate variability analysis to estimate transient psychophysiological stress induced by car driving

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Brisinda ◽  
R Fenici
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Acute Stress ◽  
Intraclass Correlation ◽  
Heart Rate Variability Analysis ◽  
Wireless Devices ◽  
Time Intervals ◽  
Variability Analysis ◽  
Psychophysiological Stress ◽  
The Time Domain

Abstract Background Heart rate variability analysis (HRVa) is increasingly used to evaluate stress-induced adaptation of the autonomic nervous system (ANS), basing on electrocardiogram (ECG) recorded with novel wearable wireless devices (WWD) for physiological monitoring. However, in order to transfer ECG data to mobile phones efficiently, WWD use low sampling frequency (SF), usually ∼100 Hz, thus much lower than the 0.5–1 kHz, previously suggested to optimize R–R intervals detection, precise enough for HRVa in the time-domain (TD), frequency-domain (FD) and with nonlinear (NL) methods. Moreover, the latter are sensitive to SF as a function of data length. Aim Aim of this study was to quantify the relative error (RE%) of HRVa, when calculated from ECG downsampled at 100 Hz, compared with that digitized at 1 kHz, considering different data lengths. Methods ECG of four healthy professional pilots was continuously recorded with a WWD (Vi-grade, Udine), at 1 kHz SF, while driving a professional simulator, inducing different degree of psychophysiological stress by changing suddenly the vehicle's behavior without advising the driver. TD, FD and NL HRV parameters were calculated (Kubios 3.0.2, Finland), from time intervals of 300, 120, 60 and 30 seconds, of ECG downsampled at 100 Hz SF from original recordings acquired at 1 kHz SF (assumed as goldstandard). The RE% and the intraclass correlation coefficient (ICC) were calculated. Results A good correlation (ICC ≥0.79–0.84) was found for the majority of HRV parameters, in both driving conditions, for all selected intervals lengths. The average RE% ranged between zero and 3%, increasing if the length of the interval selected for HRVa was lower than 60 second (Table 1). However higher RE was occasionally found. In Figure 1, an example of HRVa calculated from 2 minutes tachogram's segments, at 100 Hz (left) and at 1 kHz SF (right) is shown. Conclusions Compared to 1 kHz SF, downsampling ECG at 100 Hz doesn't affect significantly HRVa for data lengths between 5 and 1 minutes. However, for shorter time intervals the RE increases. This must be taken into account if HRVa is used to track transient short-lasting changes of ASN modulation induced by acute stress. Figure 1 Funding Acknowledgement Type of funding source: None

Reliability of Heart Rate Variability in Children: Influence of Sex and Body Position During Data Collection

2017 ◽  
Vol 29 (2) ◽  
pp. 228-236 ◽  
Author(s):  
Carla Cristiane Silva ◽  
Maurizio Bertollo ◽  
Felipe Fossati Reichert ◽  
Daniel Alexandre Boullosa ◽  
Fábio Yuzo Nakamura
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Supine Position ◽  
Repeated Measures ◽  
Body Position ◽  
Intraclass Correlation ◽  
Poincaré Plot ◽  
Rr Intervals ◽  
Type Method ◽  
Mean Square Difference

Purpose:To examine which body position and indices present better reliability of heart rate variability (HRV) measures in children and to compare the HRV analyzed in different body positions between sexes.Method:Twenty eutrophic prepubertal children of each sex participated in the study. The RR intervals were recorded using a portable heart rate monitor twice a day for 7 min in the supine, sitting, and standing positions. The reproducibility was analyzed using the intraclass correlation coefficient (ICC; two way mixed) and within-subject coefficient of variation (CV).Two-way ANOVA with repeated measures was used to compare the sexes.Results:High levels of reproducibility were indicated by higher ICC in the root-mean-square difference of successive normal RR intervals (RMSSD: 0.93 and 0.94) and Poincaré plot of the short-term RR interval variability (SD1: 0.92 and 0.94) parameters for boys and girls, respectively, in the supine position. The ICCs were lower in the sitting and standing positions for all HRV indices. In addition, the girls presented significantly higher values than the boys for SDNN and absolute high frequency (HF; p < .05) in the supine position.Conclusions:The supine position is the most reproducible for the HRV indices in both sexes, especially the vagal related indices.

scholarly journals Are smoking and passive smoking related with heart rate variability in male adolescents?

2015 ◽  
Vol 13 (1) ◽  
pp. 27-33 ◽  
Author(s):  
Renata Melo Gondim ◽  
Breno Quintella Farah ◽  
Carolina da Franca Bandeira Ferreira Santos ◽  
Raphael Mendes Ritti-Dias
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Passive Smoking ◽  
High Frequency ◽  
Heart Rate Monitor ◽  
Rr Intervals ◽  
Male Adolescents ◽  
Significant Difference ◽  
Frequency Domains ◽  
Time Standard

Objective To analyze the relation between smoking and passive smoking with heart rate variability parameters in male adolescents. Methods The sample consisted of 1,152 males, aged 14 and 19 years. Data related to smoking and passive smoking were collected using a questionnaire. RR intervals were obtained by a heart rate monitor, on supine position, for 10 minutes. After collecting the RR intervals, time (standard deviation of all RR intervals, root mean square of the squared differences between adjacent normal RR intervals and the percentage of adjacent intervals over 50ms) and frequency domains (low and high frequency and sympathovagal balance) parameters of heart rate variability were obtained. Results No significant differences between smoker and nonsmoker adolescents were observed in heart rate variability parameters (p>0.05). Similarly, heart rate variability parameters did not show significant difference between exposed and not exposed to passive smoking (p>0.05). Conclusion Cigarette smoking and passive smoking are not related to heart rate variability in adolescence.

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