0106 - THE IMPACT OF HEART RATE VARIABILITY(HRV) ANALYSIS ON THE LENGTH OF STAY (LOS) IN A FRENCH NICU

2018 ◽  
Author(s):  
Thibault Blache
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Length Of Stay ◽  
Hrv Analysis ◽  
The Impact

scholarly journals Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3998
Author(s):  
Tam Pham ◽  
Zen Juen Lau ◽  
S. H. Annabel Chen ◽  
Dominique Makowski
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Analytical Approach ◽  
Sensor Technology ◽  
The Past ◽  
Research Areas ◽  
Significant Relationships ◽  
Hrv Analysis ◽  
Psychopathological Disorders ◽  
The Impact

The use of heart rate variability (HRV) in research has been greatly popularized over the past decades due to the ease and affordability of HRV collection, coupled with its clinical relevance and significant relationships with psychophysiological constructs and psychopathological disorders. Despite the wide use of electrocardiograms (ECG) in research and advancements in sensor technology, the analytical approach and steps applied to obtain HRV measures can be seen as complex. Thus, this poses a challenge to users who may not have the adequate background knowledge to obtain the HRV indices reliably. To maximize the impact of HRV-related research and its reproducibility, parallel advances in users’ understanding of the indices and the standardization of analysis pipelines in its utility will be crucial. This paper addresses this gap and aims to provide an overview of the most up-to-date and commonly used HRV indices, as well as common research areas in which these indices have proven to be very useful, particularly in psychology. In addition, we also provide a step-by-step guide on how to perform HRV analysis using an integrative neurophysiological toolkit, NeuroKit2.

scholarly journals Heart Rate Variability Analysis: How Much Artifact Can We Remove?

2020 ◽  
Vol 17 (9) ◽  
pp. 960-965
Author(s):  
David C. Sheridan ◽  
Ryan Dehart ◽  
Amber Lin ◽  
Michael Sabbaj ◽  
Steven D. Baker
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Heart Rate Variability Analysis ◽  
Time Interval ◽  
Clinically Significant Change ◽  
Hrv Analysis ◽  
Significant Change ◽  
Clinically Significant ◽  
The Impact

Objective Heart rate variability (HRV) evaluates small beat-to-beat time interval (BBI) differences produced by the heart and suggested as a marker of the autonomic nervous system. Artifact produced by movement with wrist worn devices can significantly impact the validity of HRV analysis. The objective of this study was to determine the impact of small errors in BBI selection on HRV analysis and produce a foundation for future research in mental health wearable technology.Methods This was a sub-analysis from a prospective observational clinical trial registered with clinicaltrials.gov (NCT03030924). A cohort of 10 subject’s HRV tracings from a wearable wrist monitor without any artifact were manipulated by the study team to represent the most common forms of artifact encountered.Results Root mean square of successive differences stayed below a clinically significant change when up to 5 beats were selected at the wrong time interval and up to 36% of BBIs was removed. Standard deviation of next normal intervals stayed below a clinically significant change when up to 3 beats were selected at the wrong time interval and up to 36% of BBIs were removed. High frequency HRV shows significant changes when more than 2 beats were selected at the wrong time interval and any BBIs were removed.Conclusion Time domain HRV metrics appear to be more robust to artifact compared to frequency domains. Investigators examining wearable technology for mental health should be aware of these values for future analysis of HRV studies to improve data quality.

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.

Mindfulness meditation, well-being, and heart rate variability: A preliminary investigation into the impact of intensive Vipassana meditation

2013 ◽  
Vol 89 (3) ◽  
pp. 305-313 ◽  
Author(s):  
Jonathan R. Krygier ◽  
James A.J. Heathers ◽  
Sara Shahrestani ◽  
Maree Abbott ◽  
James J. Gross ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Mindfulness Meditation ◽  
Preliminary Investigation ◽  
Well Being ◽  
Vipassana Meditation ◽  
The Impact

THE IMPACT OF STRESS ON HEART RATE VARIABILITY OF ON-CALL PHYSICIANS

CHEST Journal ◽  
2005 ◽  
Vol 128 (4) ◽  
pp. 277S
Author(s):  
Stavros E. Mountantonakis ◽  
Dimitrios A. Moutzouris ◽  
Craig McPherson
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
The Impact

Abstract P315: Increase in Stress May Contribute to Lower Heart Rate Variability in Healthy Young Subjects

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Amanda C Costa ◽  
Ana Gabriela C Silva ◽  
Cibele T Ribeiro ◽  
Guilherme A Fregonezi ◽  
Fernando A Dias
Keyword(s):  
Cardiovascular Disease ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Healthy Volunteers ◽  
Perceived Stress ◽  
Low Frequency ◽  
Statistical Correlation ◽  
Total Power ◽  
The Impact ◽  
Nonparametric Correlation

Background: Stress is one of the risk factors for cardiovascular disease and decreased heart rate variability is associated to increased mortality in some cardiac diseases. The aim of the study was to assess the impact of perceived stress on cardiac autonomic regulation in young healthy volunteers. Methods: 35 young healthy volunteers (19 to 29 years old, 6 men) from a Brazilian population were assessed for perceived stress by the translated and validated Perceived Stress Scale (PSS, 14 questions) and had the R-R intervals recorded at rest on supine position (POLAR RS800CX) and analyzed (5 minutes, Kubius HRV software) by Fast-Fourier Transform for quantification of Heart Rate Variability (HRV). Results: Average data (±SD) for age, heart rate, BMI, waist circumference and percentage of body fat (%BF) were: 21.3±2.7 years; 65.5±7.9 bpm; 22.3±1.9 Kg/m 2 ; 76.0±6.1 cm and 32.1±6.6%; respectively. The mean score for the PSS-14 was 23.5±7.2 and for the HRV parameter as follow: SSDN=54.8±21.2ms; rMSSD=55.9±32.2ms; low-frequency (LF)= 794.8±579.7ms 2 ; High-frequency (HF)= 1508.0±1783.0 ms 2 ; LF(n.u.)= 41.1±16.2; HF(n.u.)= 58.9±16.2; LF/HF=0.89±0.80 and Total power (TP)= 3151±2570ms 2 . Spearman nonparametric correlation was calculated and there was a significant correlation of PSS-14 scores and LF (ms 2 ) (r=−0.343; p= 0.044). Other HRV variables did not shown significant correlation but also had negative values for Spearman r (TP r=−0.265, p=0.124; HF r=−0.158; SSDN r=−0.207; rMSSD r=−0.243, p=0.160). LF/HF and LF(n.u.) did not correlate to PSS-14 having Spearman r very close to zero (LF/HF r=−0.007, p=0.969; LF(n.u.) r=−0.005, p=0.976). No correlation was found for HRV parameters and BMI and there was a trend for statistical correlation of %BF and LF (ms 2 ) (r=−0.309, p=0.071). Conclusions: These data demonstrate a possible association of perceived stress level and HRV at rest. Changes in LF can be a consequence of both sympathetic and parasympathetic activity, however, analyzing the other variables HF, TP, SSDN and rMSSD (all negative Spearman r) and due to the lack of changes in LF/HF ratio and LF(n.u.) we interpret that increased stress may be associated to decrease in overall heart rate variability. These changes were seen in healthy individuals and may point out an important mechanism in cardiovascular disease development.

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

scholarly journals The impact of sedentarism on heart rate variability (HRV) at rest and in response to mental stress in young women

2018 ◽  
Vol 6 (18) ◽  
pp. e13873 ◽  
Author(s):  
José Robertto Zaffalon Júnior ◽  
Ariane Oliveira Viana ◽  
Gileno Edu Lameira de Melo ◽  
Kátia De Angelis
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Young Women ◽  
Mental Stress ◽  
The Impact

The Impact of the Components of Metabolic Syndrome on Heart Rate Variability: Using the NCEP-ATP III and IDF Definitions

2008 ◽  
Vol 31 (5) ◽  
pp. 584-591 ◽  
Author(s):  
KYOUNG-BOK MIN ◽  
JIN-YOUNG MIN ◽  
DOMYUNG PAEK ◽  
SUNG-IL CHO
Keyword(s):  
Metabolic Syndrome ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
The Impact
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