Is Ultra-Short-Term Heart Rate Variability Valid in Non-static Conditions?
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ABSTRACT:
SUBMITTER: Kim JW
PROVIDER: S-EPMC8042416 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Heart rate variability (HRV) is a cardiac autonomic marker with predictive value in cardiac patients. Ultra-short HRV (usHRV) can be measured at scale using standard and wearable ECGs, but its association with cardiovascular events in the general population is undetermined. We aimed to validate usHRV measured using ≤ 15-s ECGs (using RMSSD, SDSD and PHF indices) and investigate its association with atrial fibrillation, major adverse cardiac events, stroke and mortality in individuals without cardiovascular disease. In the National Survey for Health and Development (n = 1337 participants), agreement between 15-s and 6-min HRV, assessed with correlation analysis and Bland-Altman plots, was very good for RMSSD and SDSD and good for PHF. In the UK Biobank (n = 51,628 participants, 64% male, median age 58), after a median follow-up of 11.5 (11.4-11.7) years, incidence of outcomes ranged between 1.7% and 4.3%. Non-linear Cox regression analysis showed that reduced usHRV from 15-, 10- and 5-s ECGs was associated with all outcomes. Individuals with low usHRV (< 20th percentile) had hazard ratios for outcomes between 1.16 and 1.29, p < 0.05, with respect to the reference group. In conclusion, usHRV from ≤ 15-s ECGs correlates with standard short-term HRV and predicts increased risk of cardiovascular events in a large population-representative cohort.
| S-EPMC10624663 | biostudies-literature
Project description:BACKGROUND:Smartphone apps for heart rate variability (HRV) measurement have been extensively developed in the last decade. However, ultra-short-term HRV recordings taken by wearable devices have not been examined. OBJECTIVE:The aims of this study were the following: (1) to compare the validity and reliability of ultra-short-term and short-term HRV time-domain and frequency-domain variables in a novel smartphone app, Pulse Express Pro (PEP), and (2) to determine the agreement of HRV assessments between an electrocardiogram (ECG) and PEP. METHODS:In total, 60 healthy adults were recruited to participate in this study (mean age 22.3 years [SD 3.0 years], mean height 168.4 cm [SD 8.0 cm], mean body weight 64.2 kg [SD 11.5 kg]). A 5-minute resting HRV measurement was recorded via ECG and PEP in a sitting position. Standard deviation of normal R-R interval (SDNN), root mean square of successive R-R interval (RMSSD), proportion of NN50 divided by the total number of RR intervals (pNN50), normalized very-low-frequency power (nVLF), normalized low-frequency power (nLF), and normalized high-frequency power (nHF) were analyzed within 9 time segments of HRV recordings: 0-1 minute, 1-2 minutes, 2-3 minutes, 3-4 minutes, 4-5 minutes, 0-2 minutes, 0-3 minutes, 0-4 minutes, and 0-5 minutes (standard). Standardized differences (ES), intraclass correlation coefficients (ICC), and the Spearman product-moment correlation were used to compare the validity and reliability of each time segment to the standard measurement (0-5 minutes). Limits of agreement were assessed by using Bland-Altman plot analysis. RESULTS:Compared to standard measures in both ECG and PEP, pNN50, SDNN, and RMSSD variables showed trivial ES (<0.2) and very large to nearly perfect ICC and Spearman correlation coefficient values in all time segments (>0.8). The nVLF, nLF, and nHF demonstrated a variation of ES (from trivial to small effects, 0.01-0.40), ICC (from moderate to nearly perfect, 0.39-0.96), and Spearman correlation coefficient values (from moderate to nearly perfect, 0.40-0.96). Furthermore, the Bland-Altman plots showed relatively narrow values of mean difference between the ECG and PEP after consecutive 1-minute recordings for SDNN, RMSSD, and pNN50. Acceptable limits of agreement were found after consecutive 3-minute recordings for nLF and nHF. CONCLUSIONS:Using the PEP app to facilitate a 1-minute ultra-short-term recording is suggested for time-domain HRV indices (SDNN, RMSSD, and pNN50) to interpret autonomic functions during stabilization. When using frequency-domain HRV indices (nLF and nHF) via the PEP app, a recording of at least 3 minutes is needed for accurate measurement.
| S-EPMC7428904 | biostudies-literature
Project description:The aim of this study was to examine ultra-short-term and short-term heart rate variability (HRV) in under-20 (U-20) national futsal players during pre-tournament training camps and an official tournament. Fourteen male U-20 national futsal players (age = 18.07 ± 0.73 yrs; height = 169.57 ± 8.40 cm; body weight = 64.51 ± 12.19 kg; body fat = 12.42% ± 3.18%) were recruited to participate in this study. Early morning 10 min resting HRV, Borg CR-10 scale session rating of perceived exertion (sRPE), and general wellness questionnaire were used to evaluate autonomic function, training load, and recovery status, respectively. Log-transformed root mean square of successive normal-to-normal interval differences (LnRMSSD) was used to compare the first 30 s, first 1 min, first 2 min, first 3 min, and first 4 min with standard 5 min LnRMSSD. Mean (LnRMSSDmean) and coefficient of variation (LnRMSSDcv) of LnRMSSD were used to compare the different time segments of HRV analysis. The result of LnRMSSDmean showed nearly perfect reliability and relatively small bias in all comparisons. In contrast, LnRMSSDcv showed nearly perfect reliability and relatively small bias from 2-4 min time segments in all study periods. In conclusion, for accuracy of HRV measures, 30 s or 1 min ultra-short-term record of LnRMSSDmean and short-term record of LnRMSSDcv of at least 2 min during the training camps are recommended in U-20 national futsal players.
| S-EPMC7037747 | biostudies-literature
Project description:Objectives:Remote photoplethysmography (rPPG) is a promising non-contact measurement technique for assessing numerous physiological parameters: pulse rate, pulse rate variability (PRV), respiratory rate, pulse wave velocity, blood saturation, blood pressure, etc. To justify its use in ultra-short-term (UST) PRV analysis, which is of great benefit for several healthcare applications, the agreement between rPPG- and PPG-derived UST-PRV metrics was studied. Approach:Three time-domain metrics-standard deviation of normal-to-normal (NN) intervals (SDNN), root mean square of successive NN interval differences (RMSSD), and the percentage of adjacent NN intervals that differ from each other by more than 50 ms (pNN50)-were extracted from 56 video recordings in a publicly available data set. The selected metrics were calculated on the basis of three groups of 10 s recordings and their average, two groups of 30 s recordings and their average, and a group of 60 s recordings taken from the full-length recordings and then compared with metrics derived from the corresponding reference (PPG) pulse waveform signals by using correlation and effect size parameters, and Bland-Altman plots. Main results:The results show there is stronger agreement as the recording length increases for SDNN and RMSSD, yet there is no significant change for pNN50. The agreement parameters reach r = 0.841 (p < 0.001), r = 0.529 (p < 0.001), and r = 0.657 (p < 0.001), estimated median bias -1.52, -2.28 ms and -1.95% and a small effect size for SDNN, RMSSD, and pNN50 derived from the 60 s recordings, respectively. Significance:Remote photoplethysmography-derived UST-PRV metrics manage to capture UST-PRV metrics derived from reference (PPG) recordings well. This feature is highly desirable in numerous applications for the assessment of one's health and well-being. In future research, the validity of rPPG-derived UST-PRV metrics compared to the gold standard electrocardiography recordings is to be assessed.
| S-EPMC6953345 | biostudies-literature
Project description:This study aimed to examine the agreement and acceptance of ultra-short-term heart rate (HR) variability (HRVUST) measures during post-exercise recovery in college football players. Twenty-five male college football players (age: 19.80 ± 1.08 years) from the first division of national university championship voluntarily participated in the study. The participants completed both a repeated sprint ability test (RSA) and a Yo-Yo intermittent recovery test level 1 (YYIR1) in a randomized order and separated by 7 days. Electrocardiographic signals (ECG) were recorded in a supine position 10 min before and 30 min after the exercise protocols. The HR and HRV data were analyzed in the time segments of baseline 5~10 min (Baseline), post-exercise 0~5 min (Post 1), post-exercise 5~10 min (Post 2), and post-exercise 25~30 min (Post 3). The natural logarithm of the standard deviation of normal-to-normal intervals (LnSDNN), root mean square of successive normal-to-normal interval differences (LnRMSSD), and LnSDNN:LnRMSSD ratio was compared in the 1st min HRVUST and 5-min criterion (HRVcriterion) of each time segment. The correlation of time-domain HRV variables to 5-min natural logarithm of low frequency power (LnLF) and high frequency power (LnHF), and LF:HF ratio were calculated. The results showed that the HRVUST of LnSDNN, LnRMSSD, and LnSDNN:LnRMSSD ratio showed trivial to small effect sizes (ES) (-0.00~0.49), very large and nearly perfect interclass correlation coefficients (ICC) (0.74~0.95), and relatively small values of bias (RSA: 0.01~-0.12; YYIR1: -0.01~-0.16) to the HRVcriterion in both exercise protocols. In addition, the HRVUST of LnLF, LnHF, and LnLF:LnHF showed trivial to small ES (-0.04~-0.54), small to large ICC (-0.02~0.68), and relatively small values of bias (RSA: -0.02~0.65; YYIR1: 0.03~-0.23) to the HRVcriterion in both exercise protocols. Lastly, the 1-min LnSDNN:LnRMSSD ratio was significantly correlated to the 5-min LnLF:LnHF ratio with moderate~high level (r = 0.43~0.72; p < 0.05) during 30-min post-exercise recovery. The post-exercise 1-min HRV assessment in LnSDNN, LnRMSSD, and LnSDNN:LnRMSSD ratio was acceptable and accurate in the RSA and YYIR1 tests, compared to the 5-min time segment of measurement. The moderate to high correlation coefficient of the HRVUST LnSDNN:LnRMSSD ratio to the HRVcriterion LnLF:LnHF ratio indicated the capacity to facilitate the post-exercise shortening duration of HRV measurement after maximal anaerobic or aerobic shuttle running. Using ultra-short-term record of LnSDNN:LnRMSSD ratio as a surrogate for standard measure of LnLF:LnHF ratio after short-term bouts of maximal intensity field-based shuttle running is warranted.
| S-EPMC7312126 | biostudies-literature
Project description:In the recent years, short-term heart rate variability (HRV) describing complex variations of beat-to-beat interval series that are mainly controlled by the autonomic nervous system (ANS) has been increasingly analyzed to assess the ANS activity in different diseases and under various conditions. In contrast to long-term HRV analysis, short-term investigations (<30 min) provide a test result almost immediately. Thus, short-term HRV analysis is suitable for ambulatory care, patient monitoring and all those applications where the result is urgently needed. In a previous study, we could show significant variations of 5-min HRV indices according to age in almost all domains (linear and nonlinear) in 1906 healthy subjects from the KORA S4 cohort. Based on the same group of subjects, general gender-related influences on HRV indices are to be determined in this study. Short-term 5-min HRV indices from linear time and frequency domain and from nonlinear methods (compression entropy, detrended fluctuation analysis, traditional and segmented Poincaré plot analysis, irreversibility analysis, symbolic dynamics, correlation and mutual information analysis) were determined from 782 females and 1124 males. First, we examined the gender differences in two age clusters (25-49 years and 50-74 years). Secondly, we investigated the gender-specific development of HRV indices in five age decade categories, namely for ages 25-34, 35-44, 45-54, 55-64 and 65-74 years. In this study, significant modifications of the indices according to gender could be obtained, especially in the frequency domain and correlation analyses. Furthermore, there were significant modifications according to age in nearly all of the domains. The gender differences disappeared within the last two age decades and the age dependencies disappeared in the last decade. To summarize gender and age influences need to be considered when performing HRV studies even if these influences only partly differ.
| S-EPMC4378923 | biostudies-literature
Project description:Background and Objectives: Abnormal epileptic discharges in the brain can affect the central brain regions that regulate autonomic activity and produce cardiac symptoms, either at onset or during propagation of a seizure. These autonomic alterations are related to cardiorespiratory disturbances, such as sudden unexpected death in epilepsy. This study aims to investigate the differences in cardiac autonomic function between patients with temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE) using ultra-short-term heart rate variability (HRV) analysis around seizures. Materials and Methods: We analyzed electrocardiogram (ECG) data recorded during 309 seizures in 58 patients with epilepsy. Twelve patients with FLE and 46 patients with TLE were included in this study. We extracted the HRV parameters from the ECG signal before, during and after the ictal interval with ultra-short-term HRV analysis. We statistically compared the HRV parameters using an independent t-test in each interval to compare the differences between groups, and repeated measures analysis of variance was used to test the group differences in longitudinal changes in the HRV parameters. We performed the Tukey-Kramer multiple comparisons procedure as the post hoc test. Results: Among the HRV parameters, the mean interval between heartbeats (RRi), normalized low-frequency band power (LF) and LF/HF ratio were statistically different between the interval and epilepsy types in the t-test. Repeated measures ANOVA showed that the mean RRi and RMSSD were significantly different by epilepsy type, and the normalized LF and LF/HF ratio significantly interacted with the epilepsy type and interval. Conclusions: During the pre-ictal interval, TLE patients showed an elevation in sympathetic activity, while the FLE patients showed an apparent increase and decrease in sympathetic activity when entering and ending the ictal period, respectively. The TLE patients showed a maintained elevation of sympathetic and vagal activity in the pos-ictal interval. These differences in autonomic cardiac characteristics between FLE and TLE might be relevant to the ictal symptoms which eventually result in SUDEP.
| S-EPMC8304923 | biostudies-literature
Project description:PurposeSleep apnea syndrome (SAS) is a prevalent sleep disorder in which apnea and hypopnea occur frequently during sleep and result in increase of the risk of lifestyle-related disease development as well as daytime sleepiness. Although SAS is a common sleep disorder, most patients remain undiagnosed because the gold standard test polysomnography (PSG), is high-cost and unavailable in many hospitals. Thus, an SAS screening system that can be used easily at home is needed.MethodsApnea during sleep affects changes in the autonomic nervous function, which causes fluctuation of the heart rate. In this study, we propose a new SAS screening method that combines heart rate measurement and long short-term memory (LSTM) which is a type of recurrent neural network (RNN). We analyzed the data of intervals between adjacent R waves (R-R interval; RRI) on the electrocardiogram (ECG) records, and used an LSTM model whose inputs are the RRI data is trained to discriminate the respiratory condition during sleep.ResultsThe application of the proposed method to clinical data showed that it distinguished between patients with moderate-to-severe SAS with a sensitivity of 100% and specificity of 100%, results which are superior to any other existing SAS screening methods.ConclusionSince the RRI data can be easily measured by means of wearable heart rate sensors, our method may prove to be useful as an SAS screening system at home.
| S-EPMC8590683 | biostudies-literature
Project description:Application of ultra-short Heart Rate Variability (HRV) is desirable in order to increase the applicability of HRV features to wrist-worn wearable devices equipped with heart rate sensors that are nowadays becoming more and more popular in people's daily life. This study is focused in particular on the the two most used HRV parameters, i.e., the standard deviation of inter-beat intervals (SDNN) and the root Mean Squared error of successive inter-beat intervals differences (rMSSD). The huge problem of extracting these HRV parameters from wrist-worn devices is that their data are affected by the motion artifacts. For this reason, estimating the error caused by this huge quantity of missing values is fundamental to obtain reliable HRV parameters from these devices. To this aim, we simulate missing values induced by motion artifacts (from 0 to 70%) in an ultra-short time window (i.e., from 4 min to 30 s) by the random walk Gilbert burst model in 22 young healthy subjects. In addition, 30 s and 2 min ultra-short time windows are required to estimate rMSSD and SDNN, respectively. Moreover, due to the fact that ultra-short time window does not permit assessing very low frequencies, and the SDNN is highly affected by these frequencies, the bias for estimating SDNN continues to increase as the time window length decreases. On the contrary, a small error is detected in rMSSD up to 30 s due to the fact that it is highly affected by high frequencies which are possible to be evaluated even if the time window length decreases. Finally, the missing values have a small effect on rMSSD and SDNN estimation. As a matter of fact, the HRV parameter errors increase slightly as the percentage of missing values increase.
| S-EPMC7764161 | biostudies-literature
Project description:In healthy individuals, a reduction in cardiovascular output and a shift to parasympathetic/vagal dominant activity is observed across nocturnal sleep. This cardiac autonomic profile, often measured by heart rate variability (HRV), has been associated with significant benefits for the cardiovascular system. However, little is known about the autonomic profile during daytime sleep. Here, we investigated the autonomic profile and short-term reliability of HRV during daytime naps in 66 healthy young adults. Participants took an 80-120 min polysomnographically recorded nap at 1:30 pm. Beat-by-beat RR interval values (RR), high (HF) and low frequency (LF) power, total power (TP), HF normalized units (HF(nu)), and the LF/HF ratio were obtained for 5 min during presleep wakefulness and during nap sleep stages (N2, N3, REM). A subsample of 37 participants took two additional naps with 2 weeks between recordings. We observed lengthening of the RR, higher HF and HF(nu), and lower LF/HF during NREM, compared with REM and wake, and a marked reduction of LF and TP during N3. Intraclass correlation coefficients highlighted a short-term stability of RR and HF ranging across sleep stages between 0.52-0.76 and 0.52-0.80, respectively. Our results suggest that daytime napping in healthy young adults is associated with dynamic changes in the autonomic profile, similar to those seen during nocturnal sleep. Moreover, a reliable intraindividual measure of autonomic cardiac activity can be obtained by just a single daytime nap depending on specific parameters and recording purposes. Nap methodology may be a new and promising tool to explore sleep-dependent, autonomic fluctuations in healthy and at-risk populations.
| S-EPMC4801685 | biostudies-literature