Kubios 2.2: A Scientifically Validated and User-Friendly Software for HRV Analysis
Kubios 2.2 HRV Calculation Software Setup Free
Heart rate variability (HRV) is a measure of the variation in time between consecutive heartbeats, which reflects the activity of the autonomic nervous system (ANS) that regulates many physiological functions such as heart rate, blood pressure, breathing, and digestion. HRV analysis is a non-invasive and easy-to-use tool for assessing cardiac autonomic function, stress, recovery, health, and performance.
Kubios 2.2 HRV Calculation Software Setup Free
Kubios 2.2 is a free software for HRV analysis that provides accurate and detailed results for short-term and long-term measurements. It supports data from various heart rate monitors, electrocardiogram (ECG) devices, and photoplethysmography (PPG) monitors. It includes an adaptive QRS detection algorithm and tools for artifact correction, trend removal, and analysis sample selection. It computes all the commonly used time-domain, frequency-domain, and non-linear HRV parameters, as well as the respiratory frequency, which is important for reliable interpretation of the results. It also allows users to export and save analysis results in PDF or CSV format.
In this article, we will show you how to download and install Kubios 2.2 on your computer, how to use it for HRV analysis, and how to compare it with other HRV software tools.
How to download and install Kubios 2.2
To download and install Kubios 2.2 on your computer, you need to follow these steps:
Visit the download page of Kubios website.
Select the installer for your operating system (Windows or macOS) and click on it.
Save the installer file on your computer.
Run the installer file and follow the instructions on the screen.
Order a free license key from the product page of Kubios website.
Enter your name, email address, country, affiliation, purpose of use, and agree to the license agreement.
Check your email inbox for a confirmation message from Kubios.
Click on the link in the email message to activate your license key.
Copy your license key from the email message.
Launch Kubios 2.2 on your computer.
Paste your license key into the activation window.
Click on Activate button.
Congratulations! You have successfully installed Kubios 2.2 on your computer.
To check the system requirements and compatibility of Kubios 2.2, you can refer to the user's guide or the support page of Kubios website.
How to use Kubios 2 .2 for HRV analysis
To use Kubios 2.2 for HRV analysis, you need to follow these steps:
Import data from your heart rate monitor, ECG device, or PPG monitor.
Preprocess and edit data for artifact correction and trend removal.
Select analysis samples and settings.
Compute and interpret HRV parameters in time-domain, frequency-domain, and non-linear methods.
Export and save analysis results in PDF or CSV format.
How to import data from different sources and formats
Kubios 2.2 supports data from various sources and formats, such as:
Polar heart rate monitors (.hrm, .gpx, .xml)
Suunto heart rate monitors (.sdf, .xml)
Garmin heart rate monitors (.fit, .tcx)
ECG devices (.mat, .txt, .csv, .edf)
PPG monitors (.mat, .txt, .csv)
To import data from your source device or file, you need to follow these steps:
Click on File menu and select Import Data.
Select your source device or file format from the list.
Browse your computer or device for the data file you want to import.
Click on Open button.
Wait for Kubios 2.2 to load and display your data in the main window.
How to preprocess and edit data for artifact correction and trend removal
Kubios 2.2 includes an adaptive QRS detection algorithm and tools for artifact correction and trend removal, which are essential for accurate and reliable HRV analysis. To preprocess and edit your data, you need to follow these steps:
Click on Edit menu and select QRS Detection Settings.
Select the appropriate QRS detection method for your data type (ECG or PPG).
Adjust the QRS detection threshold and sensitivity if needed.
Click on Apply button.
Check the QRS detection results in the main window. You should see red dots marking the QRS peaks of each heartbeat.
If you notice any missing or false QRS peaks, you can manually correct them by using the Add QRS Peak or Delete QRS Peak tools from the toolbar.
Click on Edit menu and select Artifact Correction.
Select the artifact correction method you want to use (Automatic or Manual).
If you choose Automatic, Kubios 2.2 will automatically detect and correct any artifacts in your data based on predefined criteria.
If you choose Manual, you can manually mark and correct any artifacts in your data by using the Mark Artifact or Correct Artifact tools from the toolbar.
Click on Edit menu and select Trend Removal.
Select the trend removal method you want to use (None, Linear Detrending, Smoothness Priors Detrending, or Wavelet Detrending).
If you choose None, Kubios 2.2 will not remove any trend from your data.
If you choose Linear Detrending, Kubios 2.2 will remove any linear trend from your data by fitting a straight line to it.
If you choose Smoothness Priors Detrending, Kubios 2.2 will remove any non-linear trend from your data by using a smoothness priors approach that preserves the high-frequency components of the signal.
If you choose Wavelet Detrending, Kubios 2.2 will remove any non-linear trend from your data by using a wavelet transform approach that decomposes the signal into different frequency bands and removes the low-frequency components.
Adjust the trend removal parameters if needed.
Click on Apply button.
Check the trend removal results in the main window. You should see a blue line showing the original data and a green line showing the detrended data.
How to select analysis samples and settings
Kubios 2.2 allows you to select different analysis samples and settings for your HRV analysis, such as:
The length of the analysis sample (from 1 minute to 24 hours).
The start and end time of the analysis sample.
The analysis method (Short-term or Long-term).
The resampling rate (from 1 Hz to 10 Hz).
The interpolation method (Linear or Cubic Spline).
The frequency band limits (Very low frequency, Low frequency, and High frequency).
The frequency-domain method (Fast Fourier Transform or Autoregressive Model).
The non-linear method (Poincaré Plot, Approximate Entropy, Sample Entropy, or Correlation Dimension).
To select analysis samples and settings, you need to follow these steps:
Click on Analysis menu and select Analysis Settings.
Select the length of the analysis sample from the drop-down list.
Select the start and end time of the analysis sample by using the slider or entering the values in the boxes.
Select the analysis method from the drop-down list.
Select the resampling rate from the drop-down list.
Select the interpolation method from the drop-down list.
Select the frequency band limits by entering the values in the boxes or using the default values.
Select the frequency-domain method from the drop-down list.
Select the non-linear method from the drop-down list.
Click on Apply button.
How to compute and interpret HRV parameters in time-domain, frequency-domain, and non-linear methods
Kubios 2.2 computes all the commonly used HRV parameters in time-domain, frequency-domain, and non-linear methods, as well as the respiratory frequency, which is important for reliable interpretation of the results. To compute and interpret HRV parameters, you need to follow these steps:
Click on Analysis menu and select Compute HRV Parameters.
Wait for Kubios 2.2 to compute and display your HRV parameters in the main window.
Check the HRV parameters in different tabs: Time-Domain, Frequency-Domain, Non-Linear, and Respiratory Frequency.
Interpret your HRV parameters by comparing them with normative values or previous measurements, or by using guidelines from scientific literature or clinical practice.
Time-Domain HRV Parameters
Time-domain HRV parameters are statistical measures of the variation in time between consecutive heartbeats. They include:
ParameterDescriptionUnit
Mean RRThe average of all RR intervals in the analysis samplems
SDNNThe standard deviation of all RR intervals in the analysis samplems
RMSDDThe root mean square of successive differences between adjacent RR intervals in the analysis samplems
pNN50The proportion of successive differences between adjacent RR intervals that are greater than 50 ms in the analysis sample%
pNN20The proportion of successive differences between adjacent RR intervals that are greater than 20 ms in the analysis sample%
CVRRThe coefficient of variation of all RR intervals in the analysis sample (SDNN divided by Mean RR)%
CVRMSDDThe coefficient of variation of successive differences between adjacent RR intervals in the analysis sample (RMSDD divided by Mean RR)%
IQRNNThe interquartile range of all RR intervals in the analysis sample (the difference between the 75th and 25th percentiles)ms
MADRRThe median absolute deviation of all RR intervals in the analysis sample (the median of absolute differences between each RR interval and the median RR interval)ms
Time-domain HRV parameters reflect the overall variability of the heart rate, as well as the influence of the parasympathetic and sympathetic branches of the ANS. Generally, higher values indicate higher HRV and better cardiac autonomic function, while lower values indicate lower HRV and impaired cardiac autonomic function. However, the interpretation of time-domain HRV parameters depends on several factors, such as the length of the analysis sample, the physiological state of the subject, and the presence of any diseases or conditions that affect the heart rate.
Frequency-Domain HRV Parameters
Frequency-domain HRV parameters are spectral measures of the variation in frequency between consecutive heartbeats. They include:
ParameterDescriptionUnit
Total PowerThe total variance of all RR intervals in the analysis samplems
VLF PowerThe variance of RR intervals in the very low frequency band (0.003-0.04 Hz) in the analysis samplems
LF PowerThe variance of RR intervals in the low frequency band (0.04-0.15 Hz) in the analysis samplems
HF PowerThe variance of RR intervals in the high frequency band (0.15-0.4 Hz) in the analysis samplems
LF/HF RatioThe ratio of LF Power to HF Power in the analysis sample-
nLF PowerThe normalized LF Power in the analysis sample (LF Power divided by Total Power minus VLF Power)%
nHF PowerThe normalized HF Power in the analysis sample (HF Power divided by Total Power minus VLF Power)%
LF PeakThe frequency of the highest peak in the LF band in the analysis sampleHz
HF PeakThe frequency of the highest peak in the HF band in the analysis sampleHz
Frequency-domain HRV parameters reflect the oscillatory components of the heart rate, as well as the influence of different physiological mechanisms that modulate the heart rate. Generally, VLF Power reflects the long-term regulatory mechanisms, such as thermoregulation, hormonal activity, and circadian rhythms. LF Power reflects the short-term regulatory mechanisms, such as baroreflex activity, sympathetic activity, and blood pressure control. HF Power reflects the respiratory sinus arrhythmia, which is mediated by parasympathetic activity and respiration. LF/HF Ratio reflects the balance between sympathetic and parasympathetic activity. However, the interpretation of frequency-domain HRV parameters depends on several factors, such as the length and quality of the analysis sample, the frequency band limits, the frequency-domain method, and the physiological state of the subject.
Non-Linear HRV Parameters
Non-linear HRV parameters are complex measures of the variation in pattern and structure between consecutive heartbeats. They include:
ParameterDescriptionUnit
Poincaré PlotA graphical representation of the relationship between successive RR intervals in a scatter plot, where each point represents a pair of adjacent RR intervals (RRi, RRi+1)-
SD1The standard deviation of points perpendicular to the line of identity in the Poincaré plot, which reflects the short-term variability of the heart ratems
SD2The standard deviation of points along the line of identity in the Poincaré plot, which reflects the long-term variability of the heart ratems
SD1/SD2 RatioThe ratio of SD1 to SD2 in the Poincaré plot, which reflects the balance between short-term and long-term variability of the heart rate-
Approximate Entropy (ApEn)A measure of the complexity and irregularity of RR intervals, which reflects how predictable or unpredictable the heart rate is-
Sample Entropy (SampEn)A measure of the complexity and irregularity of RR intervals, which reflects how self-similar or self-dissimilar the heart rate is-
Correlation Dimension (D2)A measure of the fractal dimension and chaos of RR intervals, which reflects how sensitive the heart rate is to initial conditions-
Non-linear HRV parameters reflect the nonlinear dynamics and chaotic behavior of the heart rate, as well as the influence of various physiological systems that interact with the heart rate. Generally, higher values indicate higher HRV and higher complexity and adaptability of the cardiac system, while lower values indicate lower HRV and lower complexity and adaptability of the cardiac system. However, the interpretation of non-linear HRV parameters depends on several factors, such as the length and quality of the analysis sample, the non-linear method, and the physiological state of the subject.
Respiratory Frequency
Respiratory frequency is a measure of the breathing rate of the subject, which is derived from the HRV signal by using a peak detection algorithm. It is expressed in breaths per minute (bpm) and it is important for reliable interpretation of the HRV results, especially for the HF Power and LF/HF Ratio parameters, which are influenced by respiration. To compute and interpret respiratory frequency, you need to follow these steps:
Click on Analysis menu and select Compute Respiratory Frequency.
Wait for Kubios 2.2 to compute and display your respiratory frequency in the main window.
Check your respiratory frequency in the Respiratory Frequency tab.
Interpret your respiratory frequency by comparing it with your actual breathing rate or with normative values for different physiological states.
How to compare Kubios 2.2 with other HRV software
Kubios 2.2 is one of the most widely used and validated software tools for HRV analysis, but it is not the only one. There are other software tools that offer similar or different features and functions for HRV analysis, such as:
HRV Analysis Software 1.1 by Biomedical Signal Analysis Group
HRVAS: Heart Rate Variability Analysis Software by Ramshur et al.
RHRV: Heart Rate Variability Analysis of ECG Data by Gómez et al.
HRT: Heart Rate Turbulence Analysis by Schmidt et al.
ARTiiFACT: A Tool for Heart Rate Artifact Processing and Heart Rate Variability Analysis by Kuntzelman et al.
To compare Kubios 2.2 with other HRV software tools, you need to consider several aspects, such as:
The data sources and formats supported by each software tool.
The data preprocessing and editing methods provided by each software tool.
The analysis samples and settings available in each software tool.
The HRV parameters computed by each software tool.
The accuracy and reliability of each software tool.
The user interface and usability of each software tool.
The documentation and support provided by each software tool.
Kubios 2.2 has several advantages over other HRV software tools, such as:
It supports data from various heart rate monitors, ECG devices, and PPG monitors in different formats.
It includes an adaptive QRS detection algorithm and tools for artifact correction, trend removal, and analysis sample selection.
It computes all the commonly used time-domain, frequency-domain, and non-linear HRV parameters, as well as the respiratory frequency.
It provides accurate and detailed results for short-term and long-term measurements.
It allows users to export and save analysis results in PDF or CSV format.
It has a user-friendly interface and easy-to-use functions.
It has a comprehensive user's guide and a responsive support team.
Kubios 2.2 also has some disadvantages over other HRV software tools, such as:
It requires a free license key for activation, which may take some time to receive by email.
It does not support data from some newer heart rate monitors or devices that use proprietary formats.
It does not provide any graphical representation of the frequency-domain or non-linear HRV parameters, except for the Poincaré plot.
It does not provide any statistical analysis or comparison of multiple HRV parameters or samples.
It does not provide any feedback or suggestions for improving the quality or interpretation of the HRV results.
Therefore, Kubios 2.2 is a useful and reliable software tool for HRV analysis, but it may not meet all the needs or preferences of different users or applications. It can be used as a benchmarking system for HRV studies, as it has been extensively validated and widely used by researchers and clinicians. However, it can also be complemented or compared with other HRV software tools that offer different features and functions for HRV analysis.
Conclusion
In this article, we have shown you how to download and install Kubios 2.2 on your computer, how to use it for HRV analysis, and how to compare it with other HRV software tools. We have also explained what is Kubios 2.2 and what is HRV analysis, and what are