Ultra-Short-Term HRV and EDA Features for Machine-Learning-Based Arousal Detection in Exergaming

HRV and EDA features collected for the experiments reported in the manuscript: "Influence of High Allostatic Load and Obesity on Ultra-Short-Term HRV and EDA Features for Machine-Learning-Based Arousal Detection in Exergaming". The dataset includes computed features per protocol segment and group information (PwO or HP). Further clinical information (e.g., sex, age, BMI) about patients are not provided due to privacy constraints, but can be requested from the data curators. Latest version includes detrended EDA features, to remove potential accumulation effects.

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