Heart Rate Variability - Knowing More about HRV Analysis and Fatigue in Transport Studies

2013 ◽  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Transport Studies ◽  
Hrv Analysis

scholarly journals Field Monitoring the Effects of Overnight Shift Work on Specialist Tactical Police Training with Heart Rate Variability Analysis

2021 ◽  
Vol 13 (14) ◽  
pp. 7895
Author(s):  
Colin Tomes ◽  
Ben Schram ◽  
Robin Orr
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Shift Work ◽  
Emergency Response ◽  
Police Training ◽  
Heart Rate Variability Analysis ◽  
Response Team ◽  
Hrv Analysis ◽  
And Performance ◽  
Personnel Allocation

Police work exposes officers to high levels of stress. Special emergency response team (SERT) service exposes personnel to additional demands. Specifically, the circadian cycles of SERT operators are subject to disruption, resulting in decreased capacity to compensate in response to changing demands. Adaptive regulation loss can be measured through heart rate variability (HRV) analysis. While HRV Trends with health and performance indicators, few studies have assessed the effect of overnight shift work on HRV in specialist police. Therefore, this study aimed to determine the effects overnight shift work on HRV in specialist police. HRV was analysed in 11 SERT officers and a significant (p = 0.037) difference was found in pRR50 levels across the training day (percentage of R-R intervals varying by >50 ms) between those who were off-duty and those who were on duty the night prior. HRV may be a valuable metric for quantifying load holistically and can be incorporated into health and fitness monitoring and personnel allocation decision making.

Detecting Pedestrian Situation Awareness in Real-Time: Algorithm Development Using Heart Rate Variability and Phone Position

2018 ◽  
Vol 62 (1) ◽  
pp. 1579-1583
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Yi Wang ◽  
Si Yang
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Real Time ◽  
Situation Awareness ◽  
Mental State ◽  
Time Algorithm ◽  
Support Vector ◽  
Vehicle Design ◽  
Automated Vehicle ◽  
Hrv Analysis

To help automated vehicles learn surrounding environments via V2X communications, it is important to detect and transfer pedestrian situation awareness to the related vehicles. Based on the characteristics of pedestrians, a real-time algorithm was developed to detect pedestrian situation awareness. In the study, the heart rate variability (HRV) and phone position were used to understand the mental state and distractions of pedestrians. The HRV analysis was used to detect the fatigue and alert state of the pedestrian, and the phone position was used to define the phone distractions of the pedestrian. A Support Vector Machine algorithm was used to classify the pedestrian’s mental state. The results indicated a good performance with 86% prediction accuracy. The developed algorithm shows high applicability to detect the pedestrian’s situation awareness in real-time, which would further extend our understanding on V2X employment and automated vehicle design.

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

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 Noninvasive method for electrocardiogram recording in conscious rats: feasibility for heart rate variability analysis

2010 ◽  
Vol 82 (2) ◽  
pp. 431-437 ◽  
Author(s):  
Pedro P. Pereira-Junior ◽  
Moacir Marocolo ◽  
Fabricio P. Rodrigues ◽  
Emiliano Medei ◽  
José H.M. Nascimento
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Conscious State ◽  
Heart Rate Variability Analysis ◽  
Platinum Electrodes ◽  
Noninvasive Method ◽  
Conscious Rats ◽  
Custom Made ◽  
Surface Ecg ◽  
Hrv Analysis

Heart rate variability (HRV) analysis consists in a well-established tool for the assessment of cardiac autonomic control, both in humans and in animal models. Conventional methods for HRV analysis in rats rely on conscious state electrocardiogram (ECG) recording based on prior invasive surgical procedures for electrodes/transmitters implants. The aim of the present study was to test a noninvasive and inexpensive method for ECG recording in conscious rats, assessing its feasibility for HRV analysis. A custom-made elastic cotton jacket was developed to fit the rat's mean thoracic circumference, with two pieces of platinum electrodes attached on its inner surface, allowing ECG to be recorded noninvasively in conscious, restrained rats (n=6). Time- and frequency-domain HRV analyses were conducted, under basal and autonomic blockade conditions. High-quality ECG signals were obtained, being feasible for HRV analysis. As expected, mean RR interval was significantly decreased in the presence of atropine (p <0.05) and increased in the presence of propranolol (p<0.001). Also, reinforcing the reliability of the method, low- and high-frequency HRV spectral powers were significantly decreased in the presence of propranolol (p <0.05) and atropine (p< 0.001), respectively. In summary, the present work describes a novel, inexpensive and noninvasive method for surface ECG recording in conscious rats.

scholarly journals Autonomic Cardiac Activity in Patients with Smoking and Alcohol Addiction by Heart Rate Variability Analysis

2016 ◽  
Vol 39 (6) ◽  
pp. 147 ◽  
Author(s):  
Ramazan Yuksel ◽  
Rabia Nazik Yuksel ◽  
Tijen Sengezer ◽  
Senol Dane
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cardiac Rhythm ◽  
Cardiac Activity ◽  
Alcohol Addiction ◽  
Heart Rate Variability Analysis ◽  
Variability Analysis ◽  
Dsm Iv ◽  
Hrv Analysis ◽  
Almost All

Purpose: Smoking and alcohol addictions are common and worldwide. In the present study, we aimed to investigate the effects of these addictions on cardiac rhythm using heart rate variability (HRV) analysis. Methods: Addicts (n=42 men: 22 cigarette; 20 cigarette and alcohol) and age-matched controls (n=34 men) were included in the study. All patients fulfill the criteria for dependence according to DSM-IV-TR. Electrocardiography (ECG) recordings were obtained for a total of 30 minutes. Fagerstrom Nicotine Addiction Test (FNAT) and CAGE questionnaire (Cut down, Annoy, Guilt, Eye opener) was applied to all patients. Results: Almost all HRV parameters were significantly decreased in cigarette and cigarette and alcohol addicts compared with controls (p

Development and validation of an integrated portable heart rate variability (HRV) analysis system – STREME

2020 ◽  
Vol 143 ◽  
pp. 109887
Author(s):  
S. Arvind ◽  
K. Maheshkumar ◽  
S. Vaishali ◽  
S. Lavanya ◽  
R. Padmavathi
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Hrv Analysis ◽  
Analysis System ◽  
Development And Validation

scholarly journals Promising effects of xanthine oxidase inhibition by allopurinol on autonomic heart regulation estimated by heart rate variability (HRV) analysis in rats exposed to hypoxia and hyperoxia

PLoS ONE ◽  
2018 ◽  
Vol 13 (2) ◽  
pp. e0192781 ◽  
Author(s):  
Stanisław Zajączkowski ◽  
Wiesław Ziółkowski ◽  
Piotr Badtke ◽  
Miłosz A. Zajączkowski ◽  
Damian J. Flis ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Xanthine Oxidase ◽  
Oxidase Inhibition ◽  
Hrv Analysis ◽  
Xanthine Oxidase Inhibition
Sign in / Sign up

Export Citation Format

Share Document