scholarly journals Estimation of Spectral Entropy of HRV Data and its Application to Depression and Thyroid Subjects to Predict Cardiac Risk

2018 ◽  
Vol 11 (3) ◽  
pp. 1643-1648
Author(s):  
C. H. Renu Madhavi
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Cardiac Dysfunction ◽  
Healthy Subjects ◽  
Cardiac Risk ◽  
Sampling Frequency ◽  
Spectral Entropy ◽  
The Status ◽  
Hrv Analysis

Heart Rate variability (HRV) analysis using nonlinear techniques is very much useful to estimate the status of Autonomic Nervous System (ANS) non invasively. In this paper ANS status is estimated using nonlinear Spectral Entropy (SE) technique for both Healthy, Depression and Thyroid subjects. HRV data of Thyroid , Depression and healthy subjects is derived from Power lab Instrument with sampling frequency of 500Hz.Three observations are made based on the estimated values of SE. First observation is that SE values of Thyroid and depression subjects is lower compared to Healthy subjects SE values. Second observation made is that among Thyroid and Depression subjects SE values are found to be the lowest for Thyroid subjects compared to Depression subjects. Third observation made is that the SE values of CHF and AF subjects is lower than Thyroid and depression subjects. From the three observations made lower values of SE indicates the existence of ANS dysfunction for AF,CHF, thyroid and depression subjects Further it indicates that these subjects are at higher risk of cardiac dysfunction as compared to CHF and AF subjects leading to mortality. From the results obtained it may be concluded that among the Thyroid and Depression subjects Thyroid subjects indicate higher ANS dysfunction indicating Thyroid subjects are at higher risk of cardiac dysfunction..These findings are in agreement with the medical findings available in the literature.

scholarly journals Quantitative assessment of autonomic nervous system responses induced by graded training workloads in healthy elderly, through indices obtained from heart rate variability analysis

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
R Fenici ◽  
M Picerni ◽  
D Brisinda
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Quantitative Assessment ◽  
Training Session ◽  
Time Varying ◽  
Autonomic Nervous ◽  
Healthy Elderly ◽  
Hrv Analysis

Abstract Background Quantitative assessment of individual body adaptability to physical training performed with the purposes of health maintenance is particularly necessary in the elderly age, to avoid the risk of overstrain induced by inappropriate exercises workload and physical stress. For that purpose, heart rate monitors and heart rate variability (HRV) analysis are nowadays commercially available. However, their reliability to guide individualized fitness training in elderly people needs to be tested, knowing that users might not have medical education. Objective To preliminary quantify autonomic nervous system (ANS) responses to graded physical effort and recovery in healthy elderly basing on the parasympathetic nervous system (PNSi), the sympathetic nervous system (SNSi) and the stress (STRi) indices, derived by short-term and time-varying HRV analysis. Methods ECG of a 75 healthy male subject was monitored, from April to November 2020, during three times/week training sessions with a professional bike–ergometer. Each session consisted of 10 minutes baseline rest, 5 minutes warm-up, 30 minutes work and 10 minutes recovery. According to age, the training workload was graded from low (65–75 watt/min), to moderate (75–85 watt/min), semi-intensive (85–95 watt/min) and intensive (95–110 watt/min). For this pilot study, ECG data of only 40 training sessions (10 sessions for each workload to evaluate reproducibility) were analyzed with Kubios Premium software (version 3.4.1), in the time (TD) and frequency (FD) domains, with nonlinear (NL) methods and with time-varying (TV) algorithms. Short-time HRV was calculated from 2-minutes intervals. The PNSi, SNSi and STRi induced by each workload were averaged and compared. Results Average values of PNSi, SNSi and STRi were significantly different (p<0.05) among training sessions carried out with different workloads (Table 1A) and among measurements obtained at rest, at every 5 minutes step of each 30 minutes training session, and at 1 and 5 minutes of recovery (Table 1B). Interestingly, the correlation between SNSi and STRi was strictly linear (R= 0,98), whereas that between PNSi and STRi was better fitted by a cubic function (R=0,82 with cubic vs 0.68 with linear function), when evaluated either as a function of the sessions' workloads (Figure 1A), or of four time-intervals of each training session (Figure 1B). PNSi and SNSi were inversely correlated, with cross-point at about 15 minutes of training and 75 watt/min workload. Conclusions The calculation of PNSi, SNSi and STRi from HRV analysis is an efficient method for quick and simplified quantitative assessment of dynamic ASN adaptation to effort-induced stress from HRV analysis. If confirmed, the method may be useful for safer and even remote monitoring of training/rehabilitation in elderly. However, more detailed evaluation of spectral and NL parameters may be necessary to interpret more complex patterns of abnormal cases. FUNDunding Acknowledgement Type of funding sources: None. Table 1 Figure 1

scholarly journals Autonomic nervous system response to remote ischemic conditioning: heart rate variability assessment

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Daniel Noronha Osório ◽  
Ricardo Viana-Soares ◽  
João Pedro Marto ◽  
Marcelo D. Mendonça ◽  
Hugo P. Silva ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Healthy Subjects ◽  
System Response ◽  
Remote Ischemic Conditioning ◽  
Ischemic Conditioning ◽  
Autonomic Nervous ◽  
Non Linear

Abstract Background Remote ischemic conditioning (RIC) is a procedure applied in a limb for triggering endogenous protective pathways in distant organs, namely brain or heart. The underlying mechanisms of RIC are still not fully understood, and it is hypothesized they are mediated either by humoral factors, immune cells and/or the autonomic nervous system. Herein, heart rate variability (HRV) was used to evaluate the electrophysiological processes occurring in the heart during RIC and, in turn to assess the role of autonomic nervous system. Methods Healthy subjects were submitted to RIC protocol and electrocardiography (ECG) was used to evaluate HRV, by assessing the variability of time intervals between two consecutive heart beats. This is a pilot study based on the analysis of 18 ECG from healthy subjects submitted to RIC. HRV was characterized in three domains (time, frequency and non-linear features) that can be correlated with the autonomic nervous system function. Results RIC procedure increased significantly the non-linear parameter SD2, which is associated with long term HRV. This effect was observed in all subjects and in the senior (> 60 years-old) subset analysis. SD2 increase suggests an activation of both parasympathetic and sympathetic nervous system, namely via fast vagal response (parasympathetic) and the slow sympathetic response to the baroreceptors stimulation. Conclusions RIC procedure modulates both parasympathetic and sympathetic autonomic nervous system. Furthermore, this modulation is more pronounced in the senior subset of subjects. Therefore, the autonomic nervous system regulation could be one of the mechanisms for RIC therapeutic effectiveness.

Heart Rate Variability Assessment and Its Application for Autonomic Function Evaluation in Patients with Hyperhidrosis

2020 ◽  
Vol 83 (3) ◽  
pp. 293-300
Author(s):  
Aracy Satoe Mautari Niwa ◽  
Michele Lima Gregório ◽  
Luiz Eduardo Villaça Leão ◽  
Moacir Fernandes de Godoy
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Point Of View ◽  
Function Evaluation ◽  
Recurrence Plots ◽  
Time Frequency ◽  
Hrv Analysis ◽  
Focal Hyperhidrosis ◽  
Systemic Component

Background: Pathophysiology mechanism of primary focal hyperhidrosis (PFHH) is controversial. Heart rate variability (HRV) could explain if there is a systemic component present. We aimed to investigate the functions of the autonomic nervous system in patients diagnosed with PFHH compared to controls using the analysis of HRV in the domains of time, frequency, and nonlinearity, as well as analysis of the recurrence plots (RPs). Methods: We selected 34 patients with PFHH (29.4 ± 10.2 years) and 34 controls (29.2 ± 9.6 years) for HRV analysis. Heart beats were recorded with Polar RS800CX monitor (20 min, at rest, in supine position), and RR intervals were analyzed with Kubios Premium HRV software. RPs were constructed with Visual Recurrence Analysis software. Statistical analysis included unpaired t test (p < 0.05). Results: Our results showed that HRV parameters in the 3 domains evaluated did not show any differences between the groups. The same was observed with RPs. Conclusions: The findings suggest that PFHH, from the pathophysiological point of view, may be caused by peripheral involvement of the sympathetic nervous system (glandular level or nerve terminals), as there was no difference between the groups studied. More specific studies should help elucidate this issue.

scholarly journals Heart Rate Variability Analysis in Patients with Allergic Rhinitis

2013 ◽  
Vol 2013 ◽  
pp. 1-4 ◽  
Author(s):  
Ming-Ying Lan ◽  
Guo-She Lee ◽  
An-Suey Shiao ◽  
Jen-Hung Ko ◽  
Chih-Hung Shu
Keyword(s):  
Heart Rate ◽  
Allergic Rhinitis ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Low Frequency ◽  
Sitting Position ◽  
Rr Intervals ◽  
Hrv Analysis ◽  
Low Frequency Power ◽  
Frequency Power

Background. Very few studies investigate the role of the autonomic nervous system in allergic rhinitis. In this study, we evaluated the autonomic nervous system in allergic rhinitis patients using heart rate variability (HRV) analysis.Methods. Eleven patients with allergic rhinitis and 13 healthy controls, aged between 19 and 40 years old, were enrolled in the study. Diagnosis of allergic rhinitis was based on clinical history, symptoms, and positive Phadiatop test. Electrocardiographic recordings on the sitting and supine positions were obtained for HRV analysis.Results. In the supine position, there were no significant statistical differences in very-low-frequency power (VLF, ≤0.04 Hz), low-frequency power (LF, 0.04–0.15 Hz), high-frequency power (HF, 0.15–0.40 Hz), and the ratio of LF to HF (LF/HF) between the patient and control groups. The mean RR intervals significantly increased, while LF% and LF/HF significantly decreased in the patient group in the sitting position. Moreover, mean RR intervals, LF, and LF/HF, which were significantly different between the two positions in the control group, did not show a significant change with the posture change in the patient group.Conclusion. These suggest that patients with allergic rhinitis may have poor sympathetic modulation in the sitting position. Autonomic dysfunction may therefore play a role in the pathophysiology of allergic rhinitis.

scholarly journals Heart Rate Variability Analysis in Risk of Asthma Stratification

2017 ◽  
Vol 5 ◽  
Author(s):  
Javier Milagro ◽  
Eduardo Gil ◽  
Jesús Lázaro ◽  
Ville-Pekka Seppä ◽  
L. Pekka Malmberg ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Early Diagnosis ◽  
Heart Rate Variability Analysis ◽  
Long Term Effects ◽  
Variability Analysis ◽  
Hrv Analysis

Early diagnosis of asthma is crucial to avoid long-term effects such as permanent airway obstruction. Pathogenesis of asthma has been related with autonomic nervous system (ANS) dysfunction, concretely with abnormal parasympathetic activity. As heart rate variability (HRV) analysis does reflect ANS activity, it has been employed here in risk of asthma stratification.

scholarly journals Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Christoph Hoog Antink ◽  
Yen Mai ◽  
Mikko Peltokangas ◽  
Steffen Leonhardt ◽  
Niku Oksala ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cross Sectional Study ◽  
Medical Intervention ◽  
Heart Rate Monitoring ◽  
Cross Sectional ◽  
Endovascular Interventions ◽  
The Status ◽  
Hrv Analysis ◽  
High Frequency Content

AbstractOptical heart rate monitoring (OHR) with reflective wrist photoplethysmography is a technique mainly used in the wellness application domain for monitoring heart rate levels during exercise. In the absence of motion, OHR technique is also able to estimate individual beat-to-beat intervals relatively well and can therefore also be used, for example, in monitoring of cardiac arrhythmias, stress, or sleep quality through heart rate variability (HRV) analysis. HRV analysis has also potential in monitoring the recovery of patients, e.g. after a medical intervention. However, in order to detect subtle changes, the calculated HRV parameters should be sufficiently accurate and very few studies exist that asses the accuracy of OHR derived HRV in non-healthy subjects. In this paper, we present a method to estimate beat-to-beat-intervals (BBIs) from reflective wrist PPG signal and evaluated the accuracy of the proposed method in estimating BBIs in a cross-sectional study with 29 hospitalized patients (mean age 70.6 years) in 24-h recordings performed after peripheral vascular surgery or endovascular interventions. Finally, we evaluate the accuracy of more than 30 commonly used HRV parameters and find that the accuracy of certain metrics, for example SDNN and triangular index, shown in the literature to be associated with the deterioration of the status of the patients during recovery from surgical intervention, could be adequate for patient monitoring. On the other hand, the parameters more affected by the high-frequency content of the HRV and especially the LF/HF-ratio should be used with caution.

Heart Rate Variability (HRV) Analysis: A Methodology for Organizational Neuroscience

2016 ◽  
Vol 22 (1) ◽  
pp. 354-393 ◽  
Author(s):  
Sebastiano Massaro ◽  
Leandro Pecchia
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Ecological Validity ◽  
Heart Rhythm ◽  
Neuroscience Research ◽  
Hrv Analysis ◽  
Methodological Considerations ◽  
The Brain ◽  
Human Nervous System

Recently, the application of neuroscience methods and findings to the study of organizational phenomena has gained significant interest and converged in the emerging field of organizational neuroscience. Yet, this body of research has principally focused on the brain, often overlooking fuller analysis of the activities of the human nervous system and associated methods available to assess them. In this article, we aim to narrow this gap by reviewing heart rate variability (HRV) analysis, which is that set of methods assessing beat-to-beat changes in the heart rhythm over time, used to draw inference on the outflow of the autonomic nervous system (ANS). In addition to anatomo-physiological and detailed methodological considerations, we discuss related theoretical, ethical, and practical implications. Overall, we argue that this methodology offers the opportunity not only to inform on a wealth of constructs relevant for management inquiries but also to advance the overarching organizational neuroscience research agenda and its ecological validity.

scholarly journals DISCRIMINATION BETWEEN HEALTHY AND SICK CARDIAC AUTONOMIC NERVOUS SYSTEM BY DETRENDED HEART RATE VARIABILITY ANALYSIS

Fractals ◽  
1999 ◽  
Vol 07 (01) ◽  
pp. 85-91 ◽  
Author(s):  
Y. ASHKENAZY ◽  
M. LEWKOWICZ ◽  
J. LEVITAN ◽  
S. HAVLIN ◽  
K. SAERMARK ◽  
...  
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Healthy Subjects ◽  
Heart Rate Variability Analysis ◽  
Fluctuation Analysis ◽  
Cardiac Autonomic Nervous System ◽  
Data Points ◽  
Short Time

Multiresolution Wavelet Transform and Detrended Fluctuation Analysis have recently been proven to be excellent methods in the analysis of Heart Rate Variability and in distinguishing between healthy subjects and patients with various dysfunctions of the cardiac nervous system. We argue that it is possible to obtain a distinction between healthy subjects/patients of at least similar quality by, first, detrending the time-series of RR-intervals by subtracting a running average based on a local window with a length of around 32 data points, then calculating the standard deviation of the detrended time-series. The results presented here indicate that the analysis can be based on very short time-series of RR-data (7–8 minutes), which is a considerable improvement relative to 24-hour Holter recordings.

scholarly journals The Influence of Acupressure at Extra 1 Acupuncture Point on the Spectral Entropy of the EEG and the LF/HF Ratio of Heart Rate Variability

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Young-Chang P. Arai ◽  
Takahiro Ushida ◽  
Takako Matsubara ◽  
Kazuhiro Shimo ◽  
Hiroshi Ito ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Bispectral Index ◽  
Acupuncture Point ◽  
Control Group ◽  
Spectral Entropy ◽  
Parasympathetic Nerve ◽  
Sham Point

Acupressure applied on the Extra 1 acupuncture point results in sedation, thereby reducing bispectral index (BIS) values. Mental status and hypnotic agents influence the autonomic nervous system. We hypothesized that acupressure at the Extra 1 point would induce sedation and change sympatho-parasympathetic nerve balance. We investigated the effect of acupressure at the Extra 1 point on the EEG spectral entropy values and heart rate variability (HRV). Forty-eight volunteers (24 males and 24 females) were randomly assigned to the control or Extra 1 group. The control group received acupressure at a sham point and the Extra 1 group received acupressure at the Extra 1 point. Acupressure was applied for 5 min. The record of the EEG spectral entropy values and HRV started 5 min before acupressure and stopped 5 min after acupressure. Acupressure significantly reduced the EEG spectral entropy values in both groups, but the values of the Extra 1 group were significantly smaller than those of the control group (P< .01). Acupressure significantly decreased the LF/HF ratio of HRV in both groups (P< .05). When divided upon gender, although acupressure tended to decrease the LF/HF ratio, the ratio significantly decreased during and after acupressure only in females of the Extra 1 group (P< .05). We concluded that acupressure on the Extra 1 point significantly reduced the EEG spectral entropy in both the genders, but affected the LF/HF ratio of HRV only in females.

scholarly journals Wearable Devices Suitable for Monitoring Twenty Four Hour Heart Rate Variability in Military Populations

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1061
Author(s):  
Katrina Hinde ◽  
Graham White ◽  
Nicola Armstrong
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Wearable Devices ◽  
Health Issues ◽  
Autonomic Nervous ◽  
Military Populations ◽  
Hrv Analysis ◽  
Field Setting

Heart rate variability (HRV) measurements provide information on the autonomic nervous system and the balance between parasympathetic and sympathetic activity. A high HRV can be advantageous, reflecting the ability of the autonomic nervous system to adapt, whereas a low HRV can be indicative of fatigue, overtraining or health issues. There has been a surge in wearable devices that claim to measure HRV. Some of these include spot measurements, whilst others only record during periods of rest and/or sleep. Few are capable of continuously measuring HRV (≥24 h). We undertook a narrative review of the literature with the aim to determine which currently available wearable devices are capable of measuring continuous, precise HRV measures. The review also aims to evaluate which devices would be suitable in a field setting specific to military populations. The Polar H10 appears to be the most accurate wearable device when compared to criterion measures and even appears to supersede traditional methods during exercise. However, currently, the H10 must be paired with a watch to enable the raw data to be extracted for HRV analysis if users need to avoid using an app (for security or data ownership reasons) which incurs additional cost.

Sign in / Sign up

Export Citation Format

Share Document