scholarly journals Effects of Different Types of Verbal Activities on Heart Rate Variability

Engineering ◽  
2013 ◽  
Vol 05 (10) ◽  
pp. 310-313
Author(s):  
Ping Shi ◽  
Youfang Fang ◽  
Hongliu Yu
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Different Types

scholarly journals Comparative Characteristics of Sensorimotor Reactions of Highly Qualified Athletes with Different Types of Heart Rate Regulation

2021 ◽  
Vol 6 (5) ◽  
pp. 456-464
Author(s):  
A. P. Romanchuk ◽  
◽  
O. V. Guzii ◽  
A. V. Maglyovanyi ◽  
◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Type I ◽  
Sensorimotor Function ◽  
Type Ii ◽  
Highly Qualified ◽  
Rate Regulation ◽  
Type Iv ◽  
Heart Rate Regulation ◽  
Different Types

The purpose of the study was a comparative analysis of sensorimotor reactions in highly trained athletes with different types of heart rate regulation. Materials and methods. 202 highly trained male athletes aged 22.6±2.8 years, who are engaged in acyclic sports – martial arts (karate, taekwondo, kickboxing, boxing, freestyle wrestling, Greco-Roman wrestling, judo, sambo) and games (water polo, soccer) were examined. The experience in sports was 10.3±3.1 years. All studies were conducted in the pre-competition period in the morning. Based on the study of heart rate variability in athletes, the type of heart rate regulation was determined. The basis for determining the types of regulation is the classification of heart rate variability indicators, taking into account their inclusion in certain limits. Heart rate variability indicators that reflect the dual-circuit model of heart rate regulation and are used for diagnosis include: total heart rate variability – total power (ms2), very low frequency (ms2), and stress-index (e.u.), which reflect the various chains of regulatory effects on heart rate. According to certain data types, 4 groups were formed. 1 group (type I) consisted of 42 athletes, 2 (type II) – 28 athletes, 3 (type III) – 88 athletes, 4 (type IV) – 44 athletes. The study of sensorimotor function was performed using the device KMM-3. Results and discussion. It is shown that the most balanced sensorimotor reactions are in athletes with type III regulation of heart rate. The most strain sensorimotor reactions are observed in type II regulation of heart rate, which is reflected in the pronounced central asymmetry of movement control with acceleration to the left against the background of deteriorating accuracy of right (due to flexors) and left (due to extensors) limbs, and the right-hand predominance. Sensorimotor reactions are quite strain in type IV of heart rate regulation, which is characterized by slow reactions at the synaptic and peripheral levels. In type I of heart rate regulation, the disorders observed at the central level of regulation relate to the asymmetry of short-term motor memory processes, which are significantly reduced in the left hemisphere. Conclusion. The study shows that the differences in the regulatory support of heart rate in highly qualified athletes are accompanied by characteristic differences in sensorimotor function. The latter can be useful for the diagnosis and further correction of conditions associated with the development of overexertion and overtraining

ON CHAOS DETECTION METHODS

1996 ◽  
Vol 06 (03) ◽  
pp. 529-543 ◽  
Author(s):  
KARIN VIBE ◽  
JEAN-MARC VESIN
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Scientific Community ◽  
Detection Methods ◽  
Nonlinear Prediction ◽  
Attractor Dimension ◽  
Chaos Detection ◽  
Different Types ◽  
Data Length

Reliable chaos detection in real-world time series is attracting increasing attention in the scientific community. This work shows that it is possible to use chaos analysis methods such as attractor dimension estimation, Lyapunov exponents estimation and nonlinear prediction, under the condition that the limitations and drawbacks of the algorithms used are kept in mind. Three existing algorithms for chaos characterization are analyzed in terms of classification performances and robustness with respect to noise and data length. It is shown that all three help detect chaos and even classify different types of signals, but that their results are not devoid of ambiguity. An illustrative example is given, in which the algorithms presented are applied to heart rate variability signals, and directions of research are proposed for the design of a straightforward and simple chaos detection methodology.

scholarly journals DETRENDED FLUCTUATION ANALYSES OF SHORT-TERM HEART RATE VARIABILITY IN SURGICAL INTENSIVE CARE UNITS

2006 ◽  
Vol 18 (02) ◽  
pp. 67-72 ◽  
Author(s):  
RONG-GUAN YEH ◽  
JIANN-SHING SHIEH ◽  
YIN-YI HAN ◽  
YU-JUNG WANG ◽  
SHIH-CHUN TSENG
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Intensive Care ◽  
White Noise ◽  
Short Term ◽  
Surgical Intensive Care ◽  
Ecg Signals ◽  
Different Types ◽  
Group A ◽  
Detrended Fluctuation

We examine the dynamics of complex physiologic fluctuations using methods developed very recently in statistical physics. The method based on detrended fluctuation analysis (DFA) has been used to investigate the profile of different types of physiologic states under long term (i.e., 24 hr) analysis of heart rate variability (HRV). In this paper, this method to investigate the output of central physiologic control system under short term (i.e., 1 hr) of HRV in surgical intensive care units (SICU). Electrocardiograph (ECG) signals lasting around 1 hr were collected from ten college student volunteers as group A. Ten computes-generates white noise signals as group B also provided ECG signals lasting around 1 hr. Finally, seventeen patients representing 37 cases undergoing different types of neurosurgery were studied as group C. From this group, 25 cases were selected from 15 patients with brain injury and 12 cases were selected from 2 patients with septicemia. Group A and B were used as high and low limits of baseline for comparison with pathologic states in the SICU. The a values of DFA of groups A, B, and C were 0.958 ± 0.034, 0.521 ± 0.010, and 0.815 ± 0.183, respectively. It was found that the α value of patients in the SICU was significantly lower (P < 0.05) than that of healthy volunteers and significantly higher (P < 0.05) than white noise signals. Hence, it can be concluded that α values based on the DFA statistical concept can clearly distinguish pathologic states in SICU patients from the healthy group and from white noise signals.

scholarly journals Heart rate variability in laparoscopic hysterectomy depending on different types of anesthesia

2021 ◽  
Vol 3 ◽  
pp. 37-40
Author(s):  
S. Zaychenko ◽  
R. Tkachenko
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Laparoscopic Hysterectomy ◽  
Control Group ◽  
Autonomic Nervous ◽  
Stress Protection ◽  
Different Types

The objective: was to evaluate the effectiveness of various anesthesia options for laparoscopic hysterectomy, including low-opioid (LOA) and opioid-free anesthesia (OFA) by studying the dynamics of heart rate variability (HRV) indicators.Materials and methods. 102 patients were randomly assigned to 3 groups: 37 patients who received standard opioid anesthesia (control group), 33 women who received the LOA group, and 32 patients who received OFA.Results. Laparoscopic hysterectomy is accompanied by tension of the autonomic nervous system, especially its sympathetic link, which is manifested by an increase in the index of vago-sympathetic interaction at the traumatic stage of the operation. These changes were most significant in patients who received standard and opioid-free anesthesia, which indirectly indicates insufficient stress protection of these types of intraoperative anesthesia.Conclusions. The use of low-opioid anesthesia is accompanied by a greater stabilization of HRV indices, which indicates its sufficient autonomic protection during laparoscopic hysterectomy than standard and opioid-free anesthesia.

Heart rate variability modifications in response to different types of exercise training in athletes

2021 ◽  
Vol 61 (10) ◽  
Author(s):  
Marco A. PERRONE ◽  
Maurizio VOLTERRANI ◽  
Vincenzo MANZI ◽  
Fabio BARCHIESI ◽  
Ferdinando IELLAMO
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Exercise Training ◽  
Different Types

scholarly journals State of vegetative neurous system and nonspecitic adaptation mechanisms in multiple sclerosis patients

2003 ◽  
Vol XXXV (1-2) ◽  
pp. 22-25
Author(s):  
O. V. Evdokimova ◽  
A. S. Starikov ◽  
M. M. Lapkin ◽  
V. A. Zhdanov
Keyword(s):  
Multiple Sclerosis ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Course Of Disease ◽  
Adaptation Mechanisms ◽  
Adaptive Mechanisms ◽  
Different Types ◽  
Sympathetic Nervous ◽  
Multiple Sclerosis Patients

80 multiple sclerosis patients underwent mathematic analysis of heart rate variability. It has been determined that multiple sclerosis patients are characterized by increase of the activity of the sympathetic nervous system, nonspecific adaptive mechanisms and by decrease of the adaptive organism reserves correlated with the severity of the diseases. It has been revealed that there is connection between the above parameters and different types of the course of disease.

scholarly journals Neonatal heart rate variability: a contemporary scoping review of analysis methods and clinical applications

BMJ Open ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. e055209
Author(s):  
Samantha Latremouille ◽  
Justin Lam ◽  
Wissam Shalish ◽  
Guilherme Sant'Anna
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Frequency Band ◽  
Time Domain ◽  
Clinical Applications ◽  
Pathological Conditions ◽  
Neonatal Heart ◽  
Different Types ◽  
Study Characteristics

BackgroundNeonatal heart rate variability (HRV) is widely used as a research tool. However, HRV calculation methods are highly variable making it difficult for comparisons between studies.ObjectivesTo describe the different types of investigations where neonatal HRV was used, study characteristics, and types of analyses performed.Eligibility criteriaHuman neonates ≤1 month of corrected age.Sources of evidenceA protocol and search strategy of the literature was developed in collaboration with the McGill University Health Center’s librarians and articles were obtained from searches in the Biosis, Cochrane, Embase, Medline and Web of Science databases published between 1 January 2000 and 1 July 2020.Charting methodsA single reviewer screened for eligibility and data were extracted from the included articles. Information collected included the study characteristics and population, type of HRV analysis used (time domain, frequency domain, non-linear, heart rate characteristics (HRC) parameters) and clinical applications (physiological and pathological conditions, responses to various stimuli and outcome prediction).ResultsOf the 286 articles included, 171 (60%) were small single centre studies (sample size <50) performed on term infants (n=136). There were 138 different types of investigations reported: physiological investigations (n=162), responses to various stimuli (n=136), pathological conditions (n=109) and outcome predictor (n=30). Frequency domain analyses were used in 210 articles (73%), followed by time domain (n=139), non-linear methods (n=74) or HRC analyses (n=25). Additionally, over 60 different measures of HRV were reported; in the frequency domain analyses alone there were 29 different ranges used for the low frequency band and 46 for the high frequency band.ConclusionsNeonatal HRV has been used in diverse types of investigations with significant lack of consistency in analysis methods applied. Specific guidelines for HRV analyses in neonates are needed to allow for comparisons between studies.

Influence of seasons on heart rate variability during cognitive activity in students with different types of daily activity

2021 ◽  
Author(s):  
S.I. Pavlenko ◽  
O.A. Vedyasova
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cognitive Load ◽  
Cognitive Activity ◽  
Winter Season ◽  
Summer Season ◽  
Winter Period ◽  
Summer Period ◽  
Different Types ◽  
School Day

It is shown that changes of heart rate variability (HRV) in students with morning, afternoon and evening chronotypes under cognitive load are characterized by seasonal dependence. A more pronounced seasonal modulation of HRV is characteristic of "pigeons", whose background values of HRV parameters and responses to load during the school day are greater in the autumn-winter period than in the spring-summer period. In" larks", HRV changes in the conditions of cognitive activity dominate in the spring-summer season, and in "owls" – in the autumn-winter season, but the observed reactions are weaker than in "pigeons". The observed differences in HRV may be caused by seasonal features of mechanisms of the heart adaptation in different chronotypes. Keywords: heart rate variability, seasons of the year, chronotypes, cognitive load.

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