Heart Rate Variability in Diabetes Patients

2006 ◽  
Vol 34 (3) ◽  
pp. 291-296 ◽  
Author(s):  
H Kudat ◽  
V Akkaya ◽  
AB Sozen ◽  
S Salman ◽  
S Demirel ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
Frequency Domain ◽  
Autonomic Neuropathy ◽  
Time Domain ◽  
Cardiovascular Autonomic Neuropathy ◽  
Chronic Complications ◽  
Frequency Power ◽  
Diabetes Patients

Diabetes mellitus can cause cardiovascular autonomic neuropathy and is associated with increased cardiovascular deaths. We investigated cardiovascular autonomic neuropathy in diabetics and healthy controls by analysis of heart rate variability. Thirty-one diabetics and 30 age- and sex-matched controls were included. In the time domain we measured the mean R-R interval (NN), the standard deviation of the R-R interval index (SDNN), the standard deviation of the 5-min R - R interval mean (SDANN), the root mean square of successive R - R interval differences (RMSSD) and the percentage of beats with a consecutive R - R interval difference > 50 ms (pNN50). In the frequency domain we measured high-frequency power (HF), low-frequency power (LF) and the LF/HF ratio. Diabetes patients had lower values for time-domain and frequency-domain parameters than controls. Most heart rate variability parameters were lower in diabetes patients with chronic complications than in those without chronic complications.

Trends in Heart Rate and Heart Rate Variability during Pregnancy and Three Months Postpartum: Continuous Monitoring in a Free-Living Context (Preprint)

2021 ◽  
Author(s):  
Fatemeh Sarhaddi ◽  
Iman Azimi ◽  
Anna Axelin ◽  
Hannakaisa Niela-Vilen ◽  
Pasi Liljeberg ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Pregnant Women ◽  
Time Domain ◽  
Second Trimester ◽  
Third Trimester ◽  
Non Invasive ◽  
The Third ◽  
Invasive Method ◽  
Frequency Power

BACKGROUND Heart rate variability (HRV) is a non-invasive method reflecting autonomic nervous system (ANS) regulations. Altered HRV is associated with adverse mental or physical health complications. ANS also has a central role in physiological adaption during pregnancy causing normal changes in HRV. OBJECTIVE Assessing trends in heart rate (HR) and HRV parameters as a non-invasive method for remote maternal health monitoring during pregnancy and three months postpartum. METHODS Fifty-eight pregnant women were monitored using an Internet-of-Things (IoT)-based remote monitoring system during pregnancy and 3-months postpartum. Pregnant women were asked to continuously wear Gear sport smartwatch to monitor their HR and HRV. In addition, a cross-platform mobile application was utilized for collecting pregnancy-related information. The trends of HR and HRV parameters were extracted using reliable data. We also analyzed the trends of normalized HRV parameters based on HR to remove the effect of HR changes on HRV trends. Finally, we exploited hierarchical linear mixed models to analyze the trends of HR, HRV, and normalized HRV parameters. RESULTS HR increased significantly during the second trimester (P<.001) and decreased significantly during the third trimester (P<.01). Time-domain HRV parameters, average normal interbeat intervals (AVNN), standard deviation of normal interbeat intervals (SDNN), root mean square of the successive difference of normal interbeat intervals (RMSSD), normalized SDNN (nSDNN), and normalized RMSSD (nRMSSD) decreased significantly during the second trimester (P<.001) then increased significantly during the third trimester (P<.01). Some of the frequency domain parameters, low-frequency power (LF), high-frequency power (HF), and normalized HF (nHF) decreased significantly during the second trimester (P<.01), and HF increased significantly during the third trimester (P<.01). In the postpartum period, nRMSSD decreased (P<.05), and the LF to HF ratio (LF/HF) increased significantly (P<.01). CONCLUSIONS Our study showed that HR increased and HRV parameters decreased as the pregnancy proceeded, and the values returned to normal after the delivery. Moreover, our results show that HR started to decrease while time-domain HRV parameters and HF started to increase during the third trimester. Our results also demonstrate the possibility of continuous HRV monitoring in everyday life settings.

scholarly journals Sex Differences in Time-Domain and Frequency-Domain Heart Rate Variability Measures of Fatigued Drivers

2020 ◽  
Vol 17 (22) ◽  
pp. 8499
Author(s):  
Chao Zeng ◽  
Wenjun Wang ◽  
Chaoyang Chen ◽  
Chaofei Zhang ◽  
Bo Cheng
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sex Differences ◽  
Frequency Domain ◽  
Time Domain ◽  
Mental States ◽  
Male And Female ◽  
Frequency Domain Methods ◽  
The Difference ◽  
Electrocardiogram Ecg

The effects of fatigue on a driver’s autonomic nervous system (ANS) were investigated through heart rate variability (HRV) measures considering the difference of sex. Electrocardiogram (ECG) data from 18 drivers were recorded during a simulator-based driving experiment. Thirteen short-term HRV measures were extracted through time-domain and frequency-domain methods. First, differences in HRV measures related to mental state (alert or fatigued) were analyzed in all subjects. Then, sex-specific changes between alert and fatigued states were investigated. Finally, sex differences between alert and fatigued states were compared. For all subjects, ten measures showed significant differences (Mann-Whitney U test, p < 0.01) between different mental states. In male and female drivers, eight and four measures, respectively, showed significant differences between different mental states. Six measures showed significant differences between males and females in an alert state, while ten measures showed significant sex differences in a fatigued state. In conclusion, fatigue impacts drivers’ ANS activity, and this impact differs by sex; more differences exist between male and female drivers’ ANS activity in a fatigued state than in an alert state.

Differences in heart rate variability between Asian and Caucasian children living in the same Canadian community

2006 ◽  
Vol 31 (3) ◽  
pp. 277-282 ◽  
Author(s):  
Katharine E Reed ◽  
Darren E.R Warburton ◽  
Crystal L Whitney ◽  
Heather A McKay
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Aerobic Fitness ◽  
Time Domain ◽  
High Frequency ◽  
Analysis Of Covariance ◽  
Fitness Testing ◽  
High Frequency Power ◽  
Asian Children ◽  
Frequency Power

Heart rate variability (HRV) is an umbrella term for a variety of measures that assess autonomic influence on the heart. Reduced beat-to-beat variability is found in individuals with a variety of cardiac abnormalities. A reduced HRV positively correlates with obesity, poor aerobic fitness, and increasing age. Racial (black-white) differences are apparent in adults and adolescents. We aimed to evaluate (i) Asian-Caucasian differences in HRV and (ii) differences in HRV between girls and boys. Sixty-two children (30 male (15 Caucasian, 15 Asian) and 32 female (15 Caucasian, 17 Asians)) with a mean age of 10.3 ± 0.6 y underwent 5 min resting HRV recording, fitness testing (Leger's 20 m shuttle), and self-assessed maturity. Outcome HRV measures were a ratio of low to high frequency power (LF:HF), standard deviation of R-R intervals (SDRR) and root mean square of successive R-R intervals (RMSSD). Data were compared between groups using analysis of covariance (ANCOVA). There were no race or sex differences for time domain variables, mean R-R, body mass index, or blood pressure. Compared with Caucasian children, Asian children displayed a higher adjusted (fitness, R-R interval) LF:HF ratio (72.9 ± 59.4 vs. 120.6 ± 85.3, p < 0.05). Girls demonstrated a higher adjusted LF:HF power than boys (117.2 ± 85.1 vs. 76.6 ± 62.4, p = < 0.05). In conclusion, Asian and Caucasian children display different frequency domain components of heart rate variability.Key words: autonomic nervous system, sympathetic, vagal, race, aerobic fitness, sex.

scholarly journals Longitudinal Changes and Recovery in Heart Rate Variability of Young Healthy Subjects When Exposure to a Hypobaric Hypoxic Environment

2022 ◽  
Vol 12 ◽  
Author(s):  
Chenbin Ma ◽  
Haoran Xu ◽  
Muyang Yan ◽  
Jie Huang ◽  
Wei Yan ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Time Domain ◽  
Healthy Subjects ◽  
Multiscale Entropy ◽  
Healthy Population ◽  
Poincaré Plot ◽  
Longitudinal Changes ◽  
Hypoxic Environment

Background: The autonomic nervous system (ANS) is crucial for acclimatization. Investigating the responses of acute exposure to a hypoxic environment may provide some knowledge of the cardiopulmonary system’s adjustment mechanism.Objective: The present study investigates the longitudinal changes and recovery in heart rate variability (HRV) in a young healthy population when exposed to a simulated plateau environment.Methods: The study followed a strict experimental paradigm in which physiological signals were collected from 33 healthy college students (26 ± 2 years, 171 cm ± 7 cm, 64 ± 11 kg) using a medical-grade wearable device. The subjects were asked to sit in normoxic (approximately 101 kPa) and hypoxic (4,000 m above sea level, about 62 kPa) environments. The whole experimental process was divided into four stable resting measurement segments in chronological order to analyze the longitudinal changes of physical stress and recovery phases. Seventy-six time-domain, frequency-domain, and non-linear indicators characterizing rhythm variability were analyzed in the four groups.Results: Compared to normobaric normoxia, participants in hypobaric hypoxia had significantly lower HRV time-domain metrics, such as RMSSD, MeanNN, and MedianNN (p &lt; 0.01), substantially higher frequency domain metrics such as LF/HF ratio (p &lt; 0.05), significantly lower Poincaré plot parameters such as SD1/SD2 ratio and other Poincaré plot parameters are reduced considerably (p &lt; 0.01), and Refined Composite Multi-Scale Entropy (RCMSE) curves are reduced significantly (p &lt; 0.01).Conclusion: The present study shows that elevated heart rates, sympathetic activation, and reduced overall complexity were observed in healthy subjects exposed to a hypobaric and hypoxic environment. Moreover, the results indicated that Multiscale Entropy (MSE) analysis of RR interval series could characterize the degree of minor physiological changes. This novel index of HRV can better explain changes in the human ANS.

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