HRV - INGENIOUSLY SIMPLE!
More than software - a strong relationship with the patient.
There are many ways to treat autonomic imbalance, as the effectiveness of therapy can be checked and controlled at any time with ANS Analysis.
The therapeutic goal in regulatory disorder should be the restoration of vegetative / autonomic balance.
Some examples of therapies to improve autonomic regulation (including recommendations from users of the ANS Analysis)
- Coenzyme Q10
- Craniosacral therapy
- Autogenic training
- Neural therapy
- Progressive muscle relaxation
- Mindfulness Training
- Autogenic Training – Yoga Meditation etc.
Terms & Methodology of ANS Analysis
Heart rate variability terms - HRV
There are several terms for autonomic nervous system analysis that clarify the underlying methodology:
- Heart rhythm variability HRV
- Heart rate variability HRV
- Heart rate variability HRV
- Heart Rate Variability HRV
…are different names for the measurement and evaluation of R-R intervals (time intervals from heartbeat to heartbeat) either by a chest strap (wireless) or ECG electrodes (wired).
Methodology of the ANS Analysis
The basis of the measurement is the recording of a technically flawless electrocardiogram in which the intervals between the individual R-waves can be recorded and processed cleanly and without interference. There are so-called short-term measurements of 5-10 minutes and long-term measurements recorded over 24 hours. The scientific standards for HRV measurement and evaluation were precisely defined by a commission of experts in 1996 and are now the basis for HRV analysis being included as a basic diagnostic in the evidence-based national health care guidelines.
The sequence of intervals can be analyzed by various mathematical-statistical methods. A distinction is made here:
- Time domain parameter (time-domain)
- Frequency-based parameters (frequency-domain)
- non-linear parameters e.g. DFA – alpha1
In the following, we will focus on the measurement parameters that are relevant in practice, the time-domain paramaters and the non-linear parameters.
The frequency-based parameters are mainly used in studies, but have little relevance for practice.
Short-term or long-term HRV measurement?
With the analysis of the autonomic nervous system, one wants to record the activity of the autonomic nervous system and recognize how stress stresses the body.
You can tell within 15 minutes whether the parasympathetic nervous system is able to take up its function in a resting situation or whether the function is restricted.
But what if the patient is agitated or has had a stressful day?
The autonomic nervous system is a regulatory system that controls and regulates all our organs and organ systems depending on the situation at hand.
If the patient has had a stressful day or is highly agitated, this will result in increased sympathetic activity and decreased parasympathetic activity.
In practice, this means that I cannot make an exact statement as to whether the parasympathetic nervous system can still work sufficiently and how many reserves are still available with just a single measurement.
In the case of conspicuous measurement results with increased sympathetic and decreased parasympathetic nervous system, a second measurement should therefore follow directly with a predefined cycle breathing (integrated in the ANS Analysis Professional).
The tact breathing leads to the stimulation of the parasympathetic nervous system and thus clarifies its reserves.
The image above shows a striking measurement with increased sympathetic (red) and decreased parasympathetic (blue) with a marked improvement in autonomic regulation under tact breathing. More information about breath timing here.
Thus, within 15 minutes you can make a statement about the vegetative regulation and recognize whether it is short-term stress, example above, or whether the stress has already manifested itself, see examples below.
Definition & History
ANS Analysis measures the autonomic nervous system via heart rate variability (HRV).
The ANS Analysis shows simply, quickly and scientifically recognized worldwide how our autonomic nervous system (ANS) regulates and functions. The ANS with its two main nerves sympathetic and parasympathetic, also called vagus, is a higher-level control center in the body, which controls and regulates subordinate processes and all vital functions such as blood pressure, respiration, heart rate, immune, hormonal and digestive systems, energy supply, etc.
The logic of the ANS Analysis
Introduction ANS Analysis
The heart becomes the focus of the ANS Analysis. Since it is directly controlled by sympathetic and parasympathetic nervous systems through the conduction system, it serves as the organ of success in ANS Analysis to measure the autonomic nervous system.
As internal and external stimuli are registered and processed by the sympathetic and parasympathetic nervous systems, sensible reactions (regulation) follow in order to prepare the organism as best as possible for the current needs (e.g. acute danger = provision of energy).
A disturbance of the ANS with overactive sympathetic and hypoactive parasympathetic nervous system will physiologically and inevitably lead to altered excitation of the heart. This changes the heart rate variability (distance from heartbeat to heartbeat) accordingly and is therefore measurable!
The Chinese physician Wang Shu-he documented this in his writings “Mai Ching”/”The Knowledge of Pulse Diagnosis” (today a “pulse classic”). He wrote down a sentence that is often quoted in modern times:
Further milestones of the ANS Analysis / HRV Analysis
- 1891-Muller shows smaller increase in HF to atropine in cardiac patients.
- 1927 – Winterberg and Wenkelbach describe respiratory sinus arrhythmia.
- 1965 – Hon and Lee describe changes in RR intervals in “fetal distress”.
- 1972 – Hinkel et al. Show increased risk of cardiac death with reduced respiratory sensory arrhythmia.
- 1978 – Wolf et al. describe relationship between HRV and infarct mortality
- 1981 – (Akselrod et al. 1981) “Spectral analysis of HRV is significant as a noninvasive, quantitative measure of the functionality of cardiovascular regulatory circuits.
- 1990 – HRV analysis finds its way into clinical cardiology and diabetology
- 2000 – HRV becomes part of the risk stratification for sudden cardiac death.
- 2007 – Commit GmbH is founded and develops the ANS Analysis
- 2010 – HRV analysis is included in the program for national care guidelines in the field of neuropathy in adult-onset diabetes.
- 2016 – The International Society for Autonomic Functional Diagnostics and Regulatory Medicine e.V., in short IGAF, is founded.
HRV measurement parameters
Time-based, non-linear and frequency-based parameters
Time-based HRV parameters
RR: Distance between two heartbeats (R-points in the QRS complex / ECG). The abbreviation RR can lead to misunderstandings in German, as it can also mean blood pressure.
NN: distance between two heartbeats (normal to normal)
SDNN: Standard deviation of all NN intervals, the SDNN gives an average of the variability and consists of shares from the sympathetic and parasympathetic nervous system. The SDNN can also be referred to as total variability or total power. For the patient, it can be called the total energy of the regulatory system.
SDANN: standard deviation of the mean of the NN intervals in all five-minute periods of the entire recording, (higher values indicate increased parasympathetic activity).
SDANN-i: standard deviation of the mean normal NN interval for all five-minute intervals in a 24-hour recording, (higher values indicate increased parasympathetic activity).
r-MSSD: square root of the root mean square of the sum of all differences between adjacent NN intervals (higher values indicate increased parasympathetic activity).
SI: Stress index, reflects sympathetic activity.
pNN50: percentage of intervals with at least 50 ms deviation from the preceding interval (higher values indicate increased parasympathetic activity).
SDSD: Standard deviation of differences between adjacent NN intervals.
NN50: number of pairs of adjacent NN intervals differing more than 50 ms from each other in the whole recording, (higher values indicate increased parasympathetic activity).
Non-linear HRV parameters
Alpha 1 or DFA 1: detrended fluctuation analysis.
The Alpha 1 value not only measures purely temporal changes in heart rate variability (HRV), but it measures the quality of regulation.
By examining the HRV signal for random and repetitive areas, it is thus possible to determine how the individual regulatory systems work together.
Optimally, the alpha 1 value would be 1.0. This states that in heart rate variability, 50% are random signals indicating rapid responsiveness and 50% of the signals consist of repetitive signals. This indicates a fundamental stability of the control systems.
Anything above 1.0 means more stability and is more likely to mean compensation processes in the individual control systems.
Anything less than 1.0 means a lot of randomness, and anything less than 0.8 indicates that the control systems are not working well together. This state can also be called chaos in the system.
An example of stability in the system is, for example, measurement under paced breathing. When a measurement is performed under a given breathing rate, a respiratory sinus arrhythmia occurs, which can be seen very nicely in the rhythmogram. The signal looks very uniform, which means there is more stability in the system. The control systems work very closely coupled to each other, there is the so-called coherence. Thus, under cycle breathing, the alpha 1 value inevitably increases. So this is not to be considered negatively but shows that the systems can enter into coherence.
Frequency-based HRV parameters
The pure RR intervals can be decomposed into their frequency components by the FFT (Fast Fourier Transform). Frequency components in the VLF, LF and HF ranges result from the signal. The total power is specified in TP (Total Power).
Evaluation of the measurement data
Rhythmogram, histogram and scatter plot
The basis of our VNS analysis is the detection of 520 R-R intervals (depending on the pulse between 5 – 10 minutes) by a chest strap with a measurement resolution of 1ms. The patient is measured in the sitting position. It should have come to rest 10 minutes before, similar to the blood pressure measurement.
The transmission of data from the chest strap to the receiver is digital via radio. The subsequent graphical display and calculation of the main ANS parameters is performed fully automatically by the software.
The VNS analysis has been optimized for daily use in practice so that the physician, alternative practitioner or therapist can quickly and easily evaluate and interpret the measurement data.
In the rhythmogram, each individual time interval from heartbeat to heartbeat is recorded in milliseconds (RR interval) and connected with a line. A total of 520 RR intervals are recorded on the X-axis.
On the Y-axis the duration of the respective heartbeat is displayed.
The more different the individual RR intervals are during the measurement, the more variability can be seen in the ryhthmogram.
This variability is a sign of adaptability. It shows that the autonomic nervous system is able to adjust to internal and external stimuli. Here, the variable heartbeat is used to test whether the autonomic nervous system manages to change the heartbeat depending on the situation.
At rest, this is once the breathing (when inhaling, the heart beats faster, when exhaling, the heart beats slower). This respiratory-dependent variability is referred to as respiratory sinus arrhythmia. This is generated to a large extent by the autonomic nervous system, especially the parasympathetic nervous system.
In addition to breathing, there are other influencing factors in the resting state to which the autonomic nervous system adjusts the body, e.g. the digestive system works, we think about things, we raise our arm to scratch ourselves, we hear sounds. The autonomic nervous system has to adjust the body to all these situations.
The measurement is performed in the idle state. In this resting state, the rhythmogram should show a large variability, since variability is greatest at rest.
Why the variability is greatest at rest is well explained by a simple example:
Our heart does not give full throttle at rest in order to be efficient, but it will only beat as fast as it is necessary at the moment (e.g. a little faster when breathing in, or when you briefly raise your arm to scratch yourself). Afterwards, the heart will immediately start beating slower again to conserve energies.
In the second rhythmogram you see almost no variability, it resembles a straight line. This means the heart gives full throttle to be efficient. In the autonomic nervous system, the sympathetic nervous system is predominantly at work and the parasympathetic nervous system is on the sidelines.
GOOD HEART RATE VARIABILITY
POOR HEART RATE VARIABILITY
The histogram is another form of representation of the recorded heart rate variability.
In the histogram, the measured RR intervals are divided into fixed time ranges, e.g. 900 ms – 950 ms, etc. The percentage frequency of the values in a time range is visible in the height of the bar. The more bars there are in the width, the more variable the heart beats, the better the autonomic nervous system can regulate.
On the other hand, if you have only one or two bars, it means that the measured RR intervals are almost identical. Accordingly, the heart gives full throttle to be efficient. It does not adapt to the individual.
The distribution should resemble a Gaussian distribution curve. Other distributions allow conclusions to be drawn about possible arrhythmias.
GOOD HEART RATE VARIABILITY
POOR HEART RATE VARIABILITY
A point in the coordinate system results from two adjacent RR intervals. The first value is plotted on the X axis and the second on the Y axis. Thus, these two values result in a point in the scatter plot.
The larger the scattering cloud, the more variable the heart beats, the better the autonomic nervous system can regulate.
A highly condensed cloud means that the heart always beats evenly and can no longer adjust individually. It gives full throttle.
Optimally, the scattering cloud resembles an ellipse. Other forms of the cloud allow conclusions to be drawn about possible rhythm disturbances.