Heart Rate Variability

The validation reports for this parameter is available on request:

HEART RATE VARIABILITY

Heart rate (HR) refers to the number of heartbeats per minute. Heart Rate Variability (HRV) is the variation in the time intervals between consecutive heartbeats (RR intervals – RRi). HRV is generated by the interactions between the heart and brain and autonomic nervous system processes. HRV helps the body adapt to environmental and psychological challenges, reflecting the regulation of autonomic balance, blood pressure, blood vessel diameter, gas exchange, gut, and heart functions.

A healthy heart does not beat at constant intervals but exhibits small variances between beats. This variability allows the heart to adapt rapidly to an uncertain and changing environment. Physical or emotional stress results in faster, more monotonic heartbeats, reducing HRV. Conversely, relaxation leads to slower, less regular heartbeats and higher HRV. Normal HRV is associated with a lower risk of developing depression and post-traumatic stress disorder. Additionally, decreased HRV has been identified as an independent predictor of cardiovascular and overall mortality. Thus, HRV is a noninvasive method for evaluating autonomic nervous system activity and physical and emotional status in various clinical situations.

Our HRV algorithm uses the photoplethysmography (PPG) signal recorded from facial skin tissue (remote PPG - rPPG). The algorithm identifies the heartbeat peaks, representing the contraction of heart ventricles (R peaks of the QRS complex of the ECG wave). RR intervals (RRi) are defined as the difference between successive R peaks, calculated as: RR(n) = R(n) − R(n−1), where n is the beat index number. The variability of RRi is known as Heart Rate Variability (HRV). Our HRV measurements are based on various parameters calculated from RRi values, such as SDNN (msec), which represents the standard deviation of RRi. Accuracy is determined according to the mean RRi.

This report describes the results of a validation experiment comparing our HRV measurements with those of an accurate reference device. The advantage of a non-intrusive, automatic, and accessible method for monitoring these vital signs is clear. Our algorithm uses the PPG signal recorded from facial skin tissue (remote PPG - rPPG). It extracts face video images, produces an rPPG signal, analyzes the data, and provides the end user with real-time vital signs measurements.