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And how you can avoid them!

Heart Rate Variability (HRV) is a crucial metric for understanding the physiological stress and the autonomic nervous system (ANS) responses, particularly the parasympathetic system. For researchers, getting HRV measurements right is vital to ensure high-quality and reliable data. However, several common mistakes compromise the accuracy of HRV analysis. Let’s look at these common pitfalls and how to avoid them!

1. Using Consumer Devices
It’s tempting to opt for consumer-grade devices, especially when working with tight budgets. But these devices often don’t meet the standards required for accurate HRV measurement inresearch. They’re typically designed for everyday users rather than professionals, and they don’t provide access to raw data—making it difficult to ensure data accuracy.

How to Avoid This Mistake: Stick with reputable, research-grade brands that specialize in providing raw data and meet the standards for scientific research. If you can’t access raw data or need to log into a portal to view results, you're likely dealing with a consumer-grade device. These devices aren’t suitable for high-quality, publishable research.

2. Using PPG in Ambulatory Measurements
Photoplethysmography (PPG) sensors can be useful for short-term, stationary measurements in a controlled environment. However, when it comes to real-world, ambulatory measurements, PPG can be prone to inaccuracies. It struggles to provide precise beat detection, which is essential for accurate HRV calculations. Movement artefacts and noise are common in real-world conditions.

How to Avoid This Mistake: For more accurate HRV data, use an Electrocardiogram (ECG), which has a clear reference point (the R peak in the ECG signal) for detecting heartbeats. This method is far more reliable, especially in dynamic settings where a participant might be moving. Even research-grade PPG devices can struggle with accuracy in real-life situations, so ECG is generally a safer choice.

3. Using Devices That Only Record IBI or Have a Low Sampling Frequency
Not all ECG devices are equal! Some only record Inter-Beat Intervals (IBI), meaning you won’t have access to the raw signal data to check for artefacts. Additionally, devices that sample at low frequencies (under 1000Hz) compromise the accuracy and precision of HRV measurements.

How to Avoid This Mistake: Ensure that the ECG device you’re using has a sampling frequency over 1000Hz and captures more than just IBIs. This way, you’ll have access to high-resolution data that allows you to view artefacts and ensure the integrity of your HRV measurements. Low-quality data can lead to skewed results, which undermines the value of your research.

4. Not Having Access to Raw Data
Raw data is essential for ensuring accurate HRV measurements. Without it, you cannot identify artefacts, noise, or anomalies in your data that could distort your findings. Without access to the raw ECG signal, you’re flying blind when it comes to interpreting HRV.

How to Avoid This Mistake: Always ensure that your measurement devices provide access to raw data. If the device doesn’t allow you to view or download the raw signals, it’s not suitable for use in research. This step is crucial for identifying issues in the data that could impact the overall analysis and interpretation.

5. Using ECG in Isolation
Even with a high-quality ECG that records raw data at a high sampling rate, using it in isolation can lead to incomplete interpretations. HRV data, by itself, doesn’t provide the full context of what’s happening with the participant. Understanding how environmental or physical factors (such as movement, temperature, or barometric pressure) influence the data is essential for an accurate analysis.

How to Avoid This Mistake: Incorporate additional signals like accelerometer, gyrometric, barometric, and temperature data alongside the ECG. These contextual data points help researchers understand the circumstances under which the HRV measurements occurred, giving more insight into how the participant's body responded to different situations. Context is crucial for accurate interpretation of HRV results.

Click here to read more about the best ways to capture accurate HRV data