Heart-rate variability (HRV) is an intrinsic characteristic of human physiology, being controlled by the coupled action of sympathetic and parasympathetic components of the autonomic nervous system.
This article shows you to conduct heart rate variability analysis using PLUX products.
Why do I need Filter Options?
During the HRV processing stage of the, a great set of parameters can be used to objectively evaluate HRV, most of them with a statistical nature. Due to this statistical nature, the presence of some heart rate “outliers” will affect the results dramatically and in an undesired way, like stated in some practical examples [1][2].
To avoid these types of problems, before extracting HRV parameters, the ECG signal and the resulting heart rate information needs to be filtered for removal of ectopic beats (unexpected or false-positive peak detection).
The OpenSignal (r)evolution HRV add-on contains a configurable section dedicated to the “ectopic beats removal” task (as shown in the following figure).
Getting Started: Required Products
Using biosignalsplux hardware:
- 1x biosignalsplux hub (4 or 8-channel)
- 1x biosignalsplux Electrocardiography (ECG) sensor
Using BITalino hardware:
- 1x BITalino Board or Plugged
- 1x BITalino Electrocardiography (ECG) sensor
Software:
Step 1: Open the OpenSignals HRV add-on
Open the OpenSignals Visualization Mode.
Open the add-on interface by clicking on the plug icon and select the HRV add-on from the selection of available add-ons at the top.
Step 2: HRV add-on & R-Peak Detection
OpenSignals (r)evolution software includes HRV processing functionalities using acquired ECG sensor data, with the evolution of R-Peak to R-Peak intervals (RR intervals) duration along with the acquisition (tachogram). To achieve this, press the PROCESS button of the HRV add-on.
This processes the ECG sensor data and generates the HRV add-on results, as shown below.
Step 3: Opening Filtering options
For this, open the FILTER OPTIONS of the HRV add-on by clicking on the downwards facing arrow button next to the FILTER OPTIONS field, as shown in the following screenshot.
A window of filtering options will open as shown in the screenshot below.
Step 4: Selecting Filtering Options
Generally, heart rate can vary between 40 and 200 beats per minute (BPM), which corresponds to RR intervals between 0.30s and 1.50s [3]. For this reason, it is is logical that to set the minimum expected RR interval length (MIN RR length) and the maximum expected RR interval length (MAX RR length) limits according to the expected heart rate values within this range.
Tip
If you are expecting heart rate values ranging within other specific limitations (e.g. 60 BPM and 120 BPM), set the minimum and maximum RR accordingly (0.50s and 1.00s)
With this in mind, for this example we will assume that we will expect heart rate values between these limitations before extracting HRV parameters and will all RR intervals outside the [MIN RR, MAX RR] range will be excluded. Set the MIN (s) to 0.30 and MAX (s) to 1.50 for this example.
In relation to the second “filtering level”, it consists of a moving average, taking into consideration the average RR interval inside a sliding window with a number “Number of RR before and after” of beats inside it. The central beat will be excluded if its duration is greater or smaller than a fraction (“% WINDOW AVG. ACCEPTANCE“) of the average value.
Reasonable starting values are 20 (“Number of RR before and after“) and 20% (“%Window Avg. Acceptance“), as proposed by Mietus from the Harvard Medical School (class available here). The 20 % value is typically accepted in clinical practice.
