Heart Rate Variability

Heart rate variability (HRV) is a tool that represents the balance between the sympathetic and parasympathetic (Vagus) branches of the autonomic nervous system.  Sympathetic and parasympathetic nerves carry efferent (motor) signals to the heart and afferent signals to the brain for reflex functions.  Parasympathetic nerves slow heart rate through the release of acetylcholine.  Sympathetic nerves accelerate heart rate and force of contraction through the release of epinephrine and norepinephrine from nerve terminals and the adrenal glands.  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.  Another interesting demonstration of parasympathetic stimulation is that you can significantly slow your heart rate by rubbing the carotid arteries or applying pressure to the eyes.  During exercise, the sympathetic nervous system prevails and the heart rate is increased accordingly. 

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) 
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 and hardwired options.  Data from DSI technologies can be analyzed using the Ponemah or Dataquest A.R.T. software.

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.
 
 
Figure 1: Flow chart summarizing individual steps used when recording and processing the ECG signal in order to obtain data for HRV analysis. (Task for of the European Society of Cardiology the North American Society of Pacing Electrophysiology, 1996)

 Time Domain Analysis
Time-domain analysis is most commonly used in clinical applications of HRV.  It is probably the simplest method of analysis and it is less sensitive to noise and signal artifacts than the frequency-domain methods.  Time domain analysis use instantaneous heart rate or inter-beat-intervals.

Time Domain Measures

  • Mean NN Interval
  • Mean Heart Rate
  • Difference between longest and shortest NN interval
  • SDNN: Standard deviation of NN of normal-to-normal intervals (a representation of overall HRV)
  • SDANN: Standard deviation of NN of shorter segments averaged over entire sampling interval (an estimate of long term components of HRV)
  • SD/RR: Coefficient of the variance of HRV
  • rMSSD: Square root of the mean squared difference of successive NN intervals (correlates to high frequency components)
Frequency Domain Analysis
ECG and blood pressure signals contain identifiable frequencies that contain physiologic information.  Frequency domain techniques are performed on the inter-beat-interval signal, a plot of the R-R intervals (ms) versus time or beat number. It is very important with frequency domain techniques that the data points be equidistant.  Therefore, the inter-beat-interval data must be interpolated.

There are typically three main frequency components of HRV. Ranges for each of the frequency components vary based on species being studied.
  • Very Low Frequency (VLF)
  • Low Frequency (LF)
  • High Frequency (HF)
Parameters derived from frequency components
  • Total Power (TP)
  • VLF, LF, HF
  • Normalized LF and HF (removes VLF component)
  • LF/HF ratio
DSI offers two different software platforms, Ponemah and Dataquest A.R.T., which provide HRV anlaysis tools.  The table below summarizes the tools available in each platform.

 

Parameter

Ponemah

Dataquest A.R.T.

 Time Domain

 Mean NN interval

x

x

 Mean Heart Rate

x

x

 SDNN

x

x

 SDANN

x*

 SD/RR

x*

x

 

 Frequency Domain

 VLF

x

x

 LF

x

x

 HF

x

x

 Total Power

x

x

  *Only Available in Ponemah Replay Mode

Implantable Telemetry

DSI’s PhysioTelTM, PhysioTelTM HD and PhysioTelTM Digital 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.

 Telemetry Systems include

Small Animal Telemetry System
 
Large Animal Telemetry System
 

 Jacketed External Telemetry (JET)

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.

ECG is collected via the placement of electrodes on the exterior of the animal which are connected to the JET Device.
 

Blood pressure is collected via the placement of a Minimally Invasive Blood Pressure (MIBP) implant in an artery of the animal.  This implant then transmits to a nearby antenna in the animal’s jacket, which is connected to the JET Device.

 JET Systems include:

 JET system

Hardwired Instrumentation

Short durations of data are collected from chemically or physically restrained animals which are connected to external devices capable of monitoring ECG and recording directly into an acquisition and analysis computer system.  DSI offers two hardwired ECG options, the Multi-lead ECG Pod and Isolated/Defibrillation Protected ECG and General Purpose Probes.

 

 

Multi-Lead ECG Pod Systems include:

Isolated/Defibrillation Protected ECG and General Purpose Probes Systems include:

 


Baudrie, V., Laude, D., & Elghozi, J.-L. (2006). Optimal frequency ranges for extracting information on cardiovascular autonomic control from the blood pressure and pulse interval spectograms in mice. American Journal of Physiology - Regulatory, Integrative and Comparitive Physiology, R904-R912.

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.


Task for of the European Society of Cardiology the North American Society of Pacing Electrophysiology. (1996). Heart Rate Variability: Standards of Measurement, Physiological Intepretation, and Clinical Use. Circulation, 1043-1065.


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