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Heart Rate Variability 





What is Heart Rate Variability?
Heart Rate Variability (HRV) is an index of autonomic function and a physiologic phenomenon of variation in the time interval between heartbeats. HRV is measured by the variation in the beat-to-beat interval.  Sympathetic and parasympathetic nerves carry efferent (motor) signals to the heart and afferent signals to the brain for reflex functions.  In a human heart without autonomic input, the resting rate would be about 100 beats per minute.  However, during resting conditions, parasympathetic influence is dominant and the heart rate is typically closer to 70 beats per minute. 


Why Measure Heart Rate Variability?
Heart rate and blood pressure spontaneously fluctuate even while resting or during steady-state conditions.  HRV allows observation of the specific frequencies resulting from the fluctuations and provides insight to autonomic function.  HRV is one method used to help diagnose cardiovascular disease (myocardial infarction, congestive heart failure, coronary artery disease, hypertension, and non-cardiovascular disease (stroke, diabetes, alcoholism, cancer, glaucoma, etc).  High HRV is an indication of healthy autonomic and cardiovascular response.  Low HRV may indicate that the sympathetic and parasympathetic nervous systems aren’t properly coordinating to provide an appropriate heart rate response.

Factors that can affect HRV

  • Reflexes (baroreceptors, chemoreceptors, cardiopulmonary receptors)
  • Respiration
  • Renin-angiotensin System
  • Physical or Mental Stress
  • Exercise
  • Cardiovascular (CV) and Non-CV Disease States
  • Age
  • Drugs (beta-blockers, atropine, glycosides, anesthetics, etc) 





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How is HRV Measured?
HRV Analysis requires a series of successive heart beat intervals.  HRV is typically derived from the R-R intervals of ECG signals or inter-beat-intervals from blood pressure signals.  DSI offers several technologies to record ECG or blood pressure signals, including implantable telemetry, external telemetry or hardwired options. 


Implantable Telemetry 


 

DSI implants are designed for monitoring and collecting data from conscious, freely moving animals.  Implants are offered in different sizes to support a variety of animal species including mice, rats, dogs and non-human primates. Several telemetry models are capable of monitoring ECG and blood pressure.

 


Hardwired Signals


  

Short durations of functional endpoints are collected non-invasively from chemically or physically restrained animals that are connected to external  devices capable of monitoring surface ECG or blood pressure and recording  directly into an acquisition and analysis computer system.

  


Jacketed External Telemetry
JET system

  

ECG and blood pressure signals are collected from conscious, freely moving animals wearing a jacket which contains and protects a small JET device capable of monitoring cardiovascular data and transmitting data to an acquisition and analysis computer system.

  

836 Heart Rate Variability articles citing DSI in Google Scholar


HRV Analysis Methods
Analysis methods for HRV data exist in the time-domain and frequency-domain. Each method of analysis is very different, but contains a wealth of information.  Note that the quality of the analysis results is highly dependent on the quality of the original data and performance in detecting cardiac cycles.  False detections or missed detections can have a profound effect on the results.  The following figure outlines the steps used when acquiring and processing data for HRV analysis derived from ECG signals. Heart Rate Variability data can be collected with the Ponemah Software Platform and analyzed easily with the Data Insights module. Ponemah is a complete physiologic data acquisition and analysis software platform used by physiologists, pharmacologists, and toxicologists to confidently collect, accurately analyze, and quickly summarize study data.
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HRV Analysis

  • Time Domain Analysis

  • Frequency Domain Analysis





Ponemah software, PNM


Heart Rate Variability Demo in Ponemah

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References

Axsom, J. E., Nanavati, A. P., Rutishauser, C. A., Bonin, J. E., Moen, J. M., & Lakatta, E. G. (2020). Acclimation to a thermoneutral environment abolishes age-associated alterations in heart rate and heart rate variability in conscious, unrestrained mice. GeroScience, 42(1), 217-232.

Herman, D. A., Wingen, L. M., Johnson, R. M., Keebaugh, A. J., Renusch, S. R., Hasen, I., ... & Kleinman, M. T. (2020). Seasonal effects of ambient PM2. 5 on the cardiovascular system of hyperlipidemic mice. Journal of the Air & Waste Management Association, 70(3), 307-323.

Huet, F., Fauconnier, J., Legall, M., Sicard, P., Lozza, C., Lacampagne, A., & Roubille, F. (2020). Low-dose colchicine prevents sympathetic denervation after myocardial ischemia-reperfusion: a new potential protective mechanism. Future Science OA, (0), FSO656.

Karey, E., Pan, S., Morris, A. N., Bruun, D. A., Lein, P. J., & Chen, C. Y. (2019). The Use of Percent Change in RR Interval for Data Exclusion in Analyzing 24-h Time Domain Heart Rate Variability in Rodents. Frontiers in physiology, 10, 693.

Rowan, W. H., Campen, M., Wichers, L., & Watkinson, W. (2007). Heart rate variability in rodents: uses and caveats in toxicological studies. Cardiovascular Toxicology, 28-51.

Thireau, J., Zhang, B., Poisson, D., & Babuty, D. (2008). Heart rate variability in mice: a theoretical and practical guide. Expermiental Physiology, 83-94.

Uceda, D. E., Zhu, X. Y., Woollard, J. R., Ferguson, C. M., Patras, I., Carlson, D. F., ... & Lerman, L. O. (2020). Accumulation of Pericardial Fat Is Associated With Alterations in Heart Rate Variability Patterns in Hypercholesterolemic Pigs. Circulation: Arrhythmia and Electrophysiology, 13(4), e007614.

Wallace, T., Schaeuble, D., Pace, S. A., Schackmuth, M. K., Hentges, S. T., Chicco, A. J., & Myers, B. (2021). Sexually divergent cortical control of affective-autonomic integration. Psychoneuroendocrinology, 129, 105238.