Questions related to Heart Rate Variability
i want to extract/use ecg data from edf file , that is not supported by software for measurement of heart rate variability
- Heart rate variability (HRV) & Emotion recognition
- How to classify different emotions using Heart rate variability (HRV)?
- What is your recommendation for above-mentioned purpose?
- Which statistical tool/software(s) is (are) preferable for classifying emotions?
Thanks in advance,
I'd like to measure HRV from a group of athletes with polar H10 monitors. Is there any solution to do it via PC/MAC without mobile apps?
PS: The only thing I want to record is R-R interval values - I use Kubios to analyze HRV data.
Thanks for help.
Hello, I am looking for a good (affordable with scientific evidence) device to measure heart rate variability (HRV) by Electrocardiograph (ECG) or Photoplethysmography (PPG), and I will use it to compare a new smartphone-based HRV measuring App. May I have some recommendations?
Specifically, how does the App calculate heart rate (beats per minute (bpm))? Is heart rate calculated from an average number of beats over an interval (if so what is the duration of this interval). Or is heart rate calculated from the R-R (inter-beat) interval immediately preceding the beat. The latter does not seem to be correct as heart rate values from the App are not equivalent to R-R values from the App (that said, R-R values do not have a time-stamp so it is also unclear to me when these values are taken).
App details: Heart Rate Variability Logger - app details (marcoaltini.com)
Any advice would be greatly appreciated,
Hello. I am developing a project during which I would like to track HRV (as my dependent variable) over 18 weeks. I am thinking, based upon the existing literature, that I should be able to do this in recordings of five minutes each, twice a week (at the same time of day each time) over the course of the 18 weeks so that I can analyze overall trend in HRV during that time. I am hoping someone who has experience working with HRV can let me know if this makes sense or if I need to adjust my recording periods. This is a little outside my usual research area, so I want to be sure I am implementing appropriately.
Thank you for any thoughts you can offer!!!
We are preparing to run an experiment measuring heart rate variability and cardiac impedance using pre-gelled electrodes. We will be running both males and females and are concerned about good dermal contact. I have not seen this issue addressed in the methods sections of the research articles that I have read.
There seems to be a lot of controversy about the validity of HRV as a measure of vagal tone. Specifically, Marmerstein, McCallum, & Durand (2021) published a paper suggesting the lack of correlation between HRV and vagal tone. Are there better, non-invasive ways to clearly and accurately measure vagal tone? So much of the literature over the past few decades focuses entirely on HRV in some way or another. Is this still an accurate way to measure vagal tone?
We are doing a project on how to screen mdd patients based on heart rate variability and EEG and the data required is for this purpose.
I am preparing a grant and would like to collect 24-hour HRV at multiple time points. I'm looking for affordable, validated devices that would be ideal for my study- and importantly, they cannot have GPS capabilities. I cannot use any of the devices I am familiar with, and I am not having much luck with identifying other possibilities. Any suggestions would be much appreciated!
The physiological interpretation of the nonlinear results are difficult. Some Studies have shown that reduction of IBI (RR) signal complexity (Thuraisingham 2006;Papaioannou et al. 2006) may be a feature of cardiac pathology. On the other hand, for respiration signal Caldirola et al. (2004) found that greater respiratory entropy could be a factor in vulnerability to panic attacks. Whereas other studies have found that 0.1Hz breathing as the most dynamic state which is characterized by a specific complexity pattern and is potentially beneficial for cardiopulmonary rehabilitation and conditioning(Matić et al. 2020 ). So, its confusing how the reduction in complexity via slow rhythmic breathing is actually potentially beneficial where as it is also a a feature of cardiac pathology? Can anyone solve this dilemma?
I am first year doctoral student in Counselor Education and I'm interested in studying the mind/body connection to Covid-19 through the use of Heart Rate Variability. Thank you!
We are Master Students in Decision Science that just did a study to explore the relationship between heart rate variability (HRV) and procrastination (moderated by emotion regulated- ERQ), in a within-subject design.
The participants measured their morning baseline HRV and filled out the academic procrastination questionnaire in the evening for 7 days.
We are unsure how to analyze the data and which tests to report.
Thank you in advance for your help.
I am currently trying to analyze pre-recorded exercise data, recorded using polar H10 monitor on polar beat, and transferred to polar flow. To analyze on Kubios. Currently, I am able to extract a csv. file, however, I do not think there it contains any R-R information and does not work in Kubios.
Does anyone know how to extract raw unfiltered R-R data that is pre-recorded on a polar H10 that can be analyzed using Kubios? or any other third-party program?
Slow breathing, usually at frequency of 0.1 Hz, is a method of relaxation and supposed to increase parasympathetic activity. Heart rate variability is used as a marker for autonomic response to such intervention. In the frequency domain of HRV analysis, the HF power is considered as a marker of vagal modulation of cardiac activity, the LF power for sympathetic influence with parasympathetic component, and LF:HF ratio as sympatho-vagal balance, though with controversy.
There is a concern about how to interpret frequency domain of the HRV analysis if respiration frequency is variable (not controlled). For example, as showed in the attached file, while time domain analysis of HRV indicates increased vagal activity in response to slow breathing (increase in SDNN, RMSSD, NN50, and pNN50), the frequency domain is complex; LF (and LFnu) and the LF:HF ratio are higher in slow breathing compared with normal breathing and also compared with breathing at frequency of 0.2 Hz. Also, HF is not significantly different between slow breathing and breathing with frequency of 0.2 Hz while HFnu is lower in slow breathing.
How frequency domain of HRV must be interpreted when the intervention itself is changing the frequency of respiration? Is the time domain a better analysis of autonomic response in such case?
I am doing a project about calculating human stress level using Electrodormal activity. For that purpose I am trying to use simple methods like, equation to map EDA values to stress without using machine learning approach. I have seen some researches have used a formula known as Bavesky Stress Index to calculate Stress value using Heart Rate Variability values. I would like to know if there a some kind of equation/method to calculate stress using EDA
Vagal activity has been shown to reduce inflammatory activity (
Vagal activity, as seen from respiratory modulation of heart rate, is strong in childhood and dimishes with aging
Is there any observation, that vagal activity might protect against too strong immune reaction as suspected in pneumonia?
Would it make sense to strengthen vagal activity as a preventive measure in the population before the big wave of infection arrives?
Hello. I want to measure HRV before activity, during activity and after activity. Each measurement will take 5 minutes. I have limited budget and i m searching for a portable device. And it must be reliable for scientific research. I've found some alternatives like shimmer ear clip, polar watches, polar chest strap and some finger and you may offer me different devices. What is the best option for me?
In my study I have exposed the volunteers to 4 separate 45 second stressors that are a mixture of modalities (audio/visual) and task types (emotion-evoking/cognitive) with 3 minute baselines in between. A continuous ECG is trace is taken throughout the experiment, from the gross heart rate I hope to work out heart rate variability. My aim is to test the validity of heart rate variability as an objective stress assessment method for psychophysiological stress. My question is at what point on the ECG trace for each volunteer would I analyse the gross heart rate to work out Heart Rate variability for each of the four stressors i.e. pre-stressor, post-stressor and why ?
One month data. According to WHO the recommended dose of physical activity (PA) is 8000 steps per day. Are these true levels of PA or a reflexion of job burnout? And how this PA is related to Heart Rate Variability (HRV)? Is it useful to set limits of PA?
I am a PhD student with a psychology background. My supervisor and I are thinking to investigate how HRV changes while phobic participants exposed to a phobic image over time. We are quite new to HRV research. I wonder if anyone can recommend some readings on HRV research methodology and analysis for complete beginner?
Currently I am working on a project about measuring stress using EDA. I have seen a formula known as Baevsky Stress Index to calculate stress using Heart Rate Variability. Does anyone know some kind of formula to calculate stress using EDA value?
Below is the project title:
This project will investigate how psychological stress and mental workload impact physiology. Using Heart Rate Variability in comparison to an array of ‘gold standard’ physiological measures to investigate how task interaction impacts on psychophysiological stress.
Physiometric analysis methods -
•Core Body Temperature
Which of one of the physiological measures stated above would be best to use to measure acute stress during a driving simulation and why ?
I am searching for a toolbox that can analyze changes in different physiological states using simultaneously recorded signals with trigger markers including EEG, Heart rate variations, galvanic skin response, and respiration rate.
Hi colleagues. I'm seeing alot of papers published saying "low HRV" "high HRV" but one thing I noticed is that the indice of measurment (say SDNN, RMSSD or HF) are parasympathetic measures.
Is it correct to use this indices and report as low or high HRV after all? Isn't just low or high parasympathetic predominance? Is it possible to presume a low or high balance between sympathetic and parasympathetic on those cases without having control of sympathetic variation?
I am using the pulse sensor, a low cost device for PPG detection in the index finger
Although I am quite still, the detected signals are heavily corrupted with low-frequency and high-frequency noise . Which simple and robust signal processing technique do you recommend for
solving this case? If it works in real time, much better.
I need the clean PPG on order to measure accurately the heart rate (HR) and the heart rate variability (HRV).
Thank you all!
From reading the literature on Heart Rate Variability (HRV) use and interpretation, we might be at the stage where we could add the sensors for HRV in healthcare units where unconscious patients are cared for. Thoughts?
By this question i want to know that how control system "classical or modern" can be used in the analysis of heart variability in any method of analysis linear or nonlinear, mathematical model preferred.
Hello, I am in the starting blocks to write my bachelor thesis. The thesis is supposed to be an empirical study, concerning heart rate variability and well-being and if HRV it might be a reliable measurement for (subjective) well-being. What I want with this discussion is to get input from you, what do you know about the two topics?
Thanks for your help!
In an experimental study we tested various breathing exercises and monitored respiratory flow, beat-to-beat blood pressure, and heart rate. We developed MATLAB script for baroreflex analysis based on the sequence method and the result was interesting.
Now, we want to compare breathing exercises regarding the magnitude and phase of transfer between respiration -> blood pressure, respiration -> heart rate, and blood pressure -> heart rate using transfer function analysis.
I appreciate if someone with experience in such analysis can help us with a MATLAB script.
We are currently using a Polar H7 and H10 chest sensor in combination with a V800 watch to register heart rate variability (HRV). Through Polar Flow, we are able to export RR data from the V800, at a sampling rate of 1 Hz.
We aim to export raw data at a sampling rate of 1000 Hz.
Does anyone know how you can adjust the sampling rate of the Polar devices to be more precise?
In the export file, there is only information at a frequency of 1 Hz, so we assume that other programs to perform more in depth analysis, will not produce more precise results if we are not exporting precise data?
Thank you very much.
I would like to measure HRV in mice. Is it doable with following setup: ECG with sampling rate of 1000Hz and in lightly anesthetized mouse 2% isoflurane? If yes, what are your experiences with analysis software? Thanks.
We have used the equivital SEM-EQ-02-SEM-007 in our lab to record ECG in order to calculate heart rate variabilty. So far we have had massive artifact problems (mainly caused by movement) which we never got rid of completely. What is more, these artifacts occur eventhough our participants do not really move a lot, because they are sedentary throughout all of our experiments.
I would like to know wether this is a common problem with Equivital products or if this is just a malfunction of some sort in our equipment.
Is it enough to analyze heart rate variability（including Time domain and Frequency Domain）in short-term measurements (2.5 min) ？
Because I want to do a research on how the microclimate in different space of urban square that influence the physiology in summer. But it is too hot outdoor so I need to reduce the measurement time to the least that would not let subjects be exhausted.
Slow breathing increases fluctuation of blood pressure over the breathing cycle which is followed by the larger amplitude of respiratory-sinus arrhythmia. One main mechanism is the baroreflex. In our study on slow breathing we found that although blood pressure variability stays more or less the same over 3 minutes of slow breathing, RSA decreases over time.
Can this be due to habituation of the baroreflex?
I use Brainvision analyzer to analyze ERP data, and lately I've started to collect ECG in parallel to the EEG recording, in order to see the correlation between some ERP components and HR related measures (Specifically - the heart rate deceleration seems like a good candidate, as it is event related, but I'm also thinking about using HRV in an event-related style, if it's possible). I have some experience with using Analyzer for ERP analyses, and I was wondering whether anyone has any advise on how to use Analyzer to detect R-R intervals, and to analyze related measures.
Thanks a lot,
This is for an intervention study with older adults with MCI and cardiovascular risk factors for dementia.
Hi guys, recently some of my data are presenting the following error message ""Invalid RR interval values (RR zero or negative!). File cannot be opened" error" . I'm collecting HR and HRV through Polar RS 800 CX and analyzing with Kubios HRV. Does anyone faced some similar problem or know how to fix it? (This problem appears while opening the data txt files with Kubios)
Thanks for your attention all! Greetings from Brazil.
I have to compare very short episodes for 4 experimental conditions. They have not the same duration (30, 40, 100 seconds).
I wonder which index in time and frequency domain I may use to make these comparisons and if possible, to have some references of studies doing these manipulations.
I am looking to purchase a portable device that has the capability to measure heart rate variability along with brain stem evoked potentials. The device output should be compatible with commonly available HRV analysis softwares (e.g Kubios).
is there any recommendation of window width and overlapping rate in frequency analysis (LF and HF, excluding VLF) using Welch's periodogram in short-term HRV measurements of 5 minutes duration? As I know, often a window width of 256s and overlapping of 50% is used, but mainly for long-term HRV analysis (24h). I know that a bigger window lead to a higher frequency resolution. But a window size of over 80% data length (like 256s windows) seems to me a little inappropriate. In an example of "Kubios HRV software user guide" there is a window width of 150s and 50% overlapping used for analysing 5min measurements.
Thank you in advance!
I would like to measure Heart Rate variability with the use of a watch in a research study. Can you tell me what watch I can use.
Premise 1: Neurogenic bradycardia and RSA are mediated by different branches of the vagus and need not respond in concert.
Premise 2: Neurogenic bradycardia associated with orienting is a phylogenetic vestigial relic of the reptilian brain and is mediated by the dorsal motor nucleus (DMNX).
Premise 3: Withdrawal of cardiac vagal tone through Nucleus Ambiguus (NA) mechanisms is a mammalian adaptation to select novelty in the environment while coping with the need to maintain metabolic output and continuous social communication.
(From Porges SW (2013) Polvagal Theory. NY: Norton)
The current evolutionary vagal evidence indicates that neither Premises 2 nor 3 are accurate. Also 1) there is a confluence of evidence regarding Premise 1 showing that the DMNX may only manifest vagal effects upon heart rate under conditions of severe physiological respiratory distress (and even this is not very well documented), 2) Porges provides merely very indirect findings to support his hypothesis (and his Figure 2.3 of the time course of putative DMNX-stimulated bradycardia in a single anesthetized rabbit shows much too rapid onset and offset for the heart rate drop to be a response of the unmyelinated DMNX vagal fibers [which should have a much more gradual onset and offset than shown because slow conduction time of these fibers prevent sudden changes]), and 3) no mention is made by Porges of earlier findings that indicate that the DMNX is not implicated in normal vagal control of heart rate.
Nevertheless, perhaps there are strands of direct evidence of which I am unaware? In any case, polvagal conjectures have become very popular in psychology, psychophysiology and therapy literature. It seems, therefore, high time to critically assess the value of Stephen Porges' ideas in this area.
Which is the most used parameter characterizing the HRV? If dk is the duration of the k-th R-R interval, the standard deviation of these dk values is a first possibility. Moreover, using dk, one can derive the corresponding Heart Rate value HRk = 60/dk (beats/min). The standard deviation of these HRk values could be another measure of HRV. Other propositions could also be considered. But which is the most used parameter?
I have 300+ participants to analyze in Kubios for heart rate variability. Currently, the only option I know of, is to save each data file one by one, which is very time consuming. Is there a way to run a batch in Kubios, or MATLAB scripts to speed the process up?
In order to validate a Doppler radar used for Heartbeat Rate and Heart Rate Variability extraction, an ECG (electrocardiograph) is often used as reference. Which is the accuracy of an ECG? Can be the Doppler radar more accurate than the ECG? How the accuracy of an ECG could be determined?
I am about to start working with some aversive learning paradigms in humans and wanted to ask for some suggestions on measuring fear responses to threat/mild pain stimuli.
Specifically, I wonder if you could share some tricks and tips on how to improve quality and reliability of galvanic skin response (which, I know, is inherently noisy and can be tricky to collect in some subjects) or maybe recommend some good ways/techniques to complement it (e.g. by combining with heart rate variability, etc).
Many thanks in advance!
I am intending to explore the use of heart rate variability (HRV) for occupational settings. Real-time monitoring of physical and mental stress could be beneficial to for occupational safety and health. While going through literature, I have seen that HRV is sensitive to the sympathetic and parasympathetic activity of the autonomic system. But are there any HRV metrics available which could differentiate occupational physical stress and mental stress? Or measure them separately (mutually exclusive)?
I need comments of experts. Most of my publications in Russian. Not many people involved in the study of heart rate variability in the methodological level in Russia. Therefore, I almost did not have feedback on my results.
To formulate short, I discovered that:
1. In addition to the classic two phenomena of modulation of heart rate (respiratory sinus arrhythmia, low frequency waves associated with Mayer waves and thermoregulation) there is at least one more with a period of 3 cardiac intervals. I discovered this when I performed factor analysis of periodogram of heart rate tachogram and found out a wave of factor loadings with the peak on this period. A breaf publication in English is here https://arxiv.org/abs/1005.0776v2
2. Amplitude of heart rate modulations with the period of 3 cardiac intervals is associated with mental vigor and mental work capacity. I found positive correlations with a scale of psychological questionnaire and with results of computer game Tetris.
3. Amplitude of the 3 cardiac intervals heart rate modulations is associated with the frontal cortex activity. There is positive correlation with EEG defined level of cortex activity. This is published here http://link.springer.com/article/10.1007/s11055-013-9805-1
I have attached my presintations with extended information on this.
Please, answer me what do you think on these results?
I am not sure if this is possible or not. I am aware that greater than 100 ms is generally considered to be "good" hrv.
Any suggestion of linking heart rate variability (HRV -LF/HF) values to mental fatigue directly ?
There are two groups of patients with equal number of patients on betablockers. Will this effect the difference of heart rate variability in the two groups if both are equally on betablockers? I believe that the difference will not be effected although the absolute HRV will be effected.
Frequency domain parameters are not being tested and only time domain is being analysed.
If you can comment on this with some evidence linked please it will be very helpful.
Looking for someone to suggest the easiest way to get to frequency domain outputs of the HF band measured in 'Hz' rather than 'sec^2/Hz' (or - how to convert? - simple 'Hz' seems to be the more common way to report HF power in the literature).
Also, looking for a get around for the fact that time domain outputs (like RMSSD) seem to require a scripting license in AquKnowledge. Is there free software that can do the same? - or, perhaps better, free software that will give both time and frequency domain outputs in one quick analysis?
Failing that - suggestions for better analysis methods appreciated!
Aquknowledge 4.1 gives HRV frequency domain statistics in units of "sec^2/Hz":
e.g. "Power in the high frequency band: 0.000374971 sec^2/Hz"
However, the recommended way to report frequency domain stats seems to be "msec^2":
"The measurement of VLF, LF, and HF power components is usually made in absolute values of power (milliseconds squared)". see: http://circ.ahajournals.org/content/93/5/1043.full
Can someone walk me through what I should do here?
We recorded ECG (no control for breathing, but with simultaneous EDA recording), and after extracting RR tachograms, I noticed that one participant had what looked to me an unusual RR pattern (I've attached a picture). Whereas most people have very busy (dense and spikey) tachograms, this person had very large waves so that frequency analysis showed almost purely LF power.
Is this pattern unusual, and what does it mean? Is it breathing? Possibly relevant is that the peaks and troughs of the RR seem to roughly correspond to EDRs, does that make sense?
Dear colleagues, I would like to hear from you which sample of RR intervals would be more suitable for HRV analysis: fixed number of RRi or fixed time?
I usually work with fixed number, which has been well accepted, but sometimes reviewers criticize this approach.
In the experiment for my dissertation thesis, I want to measure kinematic, kinetic and physiological parameters (VO2max, heart-rate, breath-rate...) from treadmill running and synchronizing all three of these data streams would be really helpful for future processing.
For heart rate variability analysis I'm using a Polar rs800x; anybody know another heart rate monitor with R-R recording more modern that I can use?
We analyse the respiration trace from a respiratory belt in a study on emotions. We want to calculate the average respiratory rate across a given block (1 minute). An automated analysis with LabChart detects most respiratory cycles correctly. However, some peaks in the respiration trace seem to be abnormal / artifacts (e.g., very short or very shallow breaths). Do you know any guidlines that inform how to include only the meaningful data into the analysis and rule out breathing artifacts?
I need a device for measuring the HRV and the respirationrate from both thorax and abdomen. The test persons are playing piano, so it has to be not very disturbing. I already saw the belts from Polar but they only use ECG. Thank you for any idea!
I am currently exploring in how far it is possible to use (combinations of) sensors to measure (electro magnetic) signals (aka EM-Biofield) to collect objective data which can be interpreted to reflect subjective mental states.
I am experimenting with HRV derived from Polar H10 and Kubios, but get stuck with the interpretation of parameters, Spectra and Poincare plots - eventually there is a clever way to combine this with meaningful EEG or other parameters.
Eventually it could make sense to also use tone of voice (FFT) t complement the assessment - which of course is only possible in an active mode - whereas the HRV / EEG would also work passive.
Any other parameters that could be used ? Like Skin conductance, skin temperature?
We have hundreds of HRV datasets of medical staff. We want to create a predictive model of stress.
Is it important that HRV or IBI (Inter Beat Interval) data length should be equal for all datasets? I read, there are two types of HRV study i.e. long (24hour) and short (5min). My datasets are of variable length for example one contains 7132 IBI points, other one contains 5648 IBI points and so on.
I have calculated time domain measures such as SD, SE etc., Would this (variable dataset length) will significantly affect our results?
What should I do to minimize such issues?
I have a total of 100 datasets that contain data of Inter Beat Interval (R-R Interval), for which I have calculated mean and standard deviation. This resulted in a range of standard deviation, I don't know how should I divide this range in stress score classes such as mild, moderate and severe?
Do I need to use some other measures?
Attachment: Articles and media
It has been proposed that no single statistical measure can be used to assess the complexity of physiologic systems. Furthermore, it has been demonstrated that many entropy-based measures are "regularity" statistics, not direct indexes of physiologic "complexity". Finally, it has been stressed that increased/decreased irregularity does not imply increased/decreased physiologic complexity. However, it is common to keep finding interpretations such as, "a decreased/increased entropy value of beat-to-beat interval series (RR sequences) reflects a decreased/increased complexity of heart rate variability", and even more as "this reflects a decreased/increased complexity of the cardiovascular control". So, which entropy-based measures actually quantifies time series complexity? Moreover, is it appropriate to interpret that because of a decreased/increased complexity in heart rate variability there is a decreased/increased complexity of the cardiovascular control?
Thanks in advance,
I have been trying to extract data from XML files (originally exported from GE ECG device) for heart rate variability analysis. However, I have yet become successful in doing that. Is there anyone that can help me on this issue?