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Table 2 Features derived from BVP signal and their explanations

From: Physiology-driven cybersickness detection in virtual reality: a machine learning and explainable AI approach

BVP feature

Feature description

HR

A straightforward measurement of heartbeats per minute.=

BVP PSD

PSD of BVP signal between 1 and 8 Hz

MAD

A measure of heart variability

IBI

The time interval between successive heartbeats, useful for assessing HRV.

SDNN

Quantifies overall variability in heart rate, reflecting ANS function.

SDSD

RMSSD

SDSD and RMSSD analyze the variability of successive heartbeat intervals, with RMSSD particularly sensitive to parasympathetic activity

pNN20

pNN50

Percentages of differences between adjacent R-R intervals,greater than 20 ms and 50 ms, respectively, indicators of rapid changes in heart rate.

SD1

Std of points perpendicular to the line of identity, indicating short-term HR variability.

SD2

Standard deviation along line of identity, reflecting long-term variability.

S

Quantifies scatter of points within plot, indicating overall heart rate variability.

SD1/SD2 ratio

Provides insights into balance between short-term and long-term heart rate variabilities, reflecting relative contributions of sympathetic and parasympathetic inputs to heart rate dynamics.

BR

Estimated breathing rate extracted from BVP signal