Key result
The combination of dispersion entropy, quadratic sample entropy, and amplitude-aware permutation entropy significantly improved the detection of negative stress from EEG signals.
Why the study?
Negative stress poses adverse health consequences, and the utility of applying dispersion entropy to electroencephalographic signals for distress detection had not been evaluated.
The combination of QSampEn, AAPE, and DispEn improves the detection of negative stress from EEG signals compared to existing indices.
May support objective mental stress assessment in CV care; leaves open validation before clinical or research adoption.
Negative stress, or distress, represents a serious problem in advanced societies given its adverse consequences for health. Many studies have focused on the detection of distress from physiological signals such as the electroencephalogram (EEG). To this respect, the combination of regularity-based quadratic sample entropy (QSampEn) and symbolic amplitude-aware permutation entropy (AAPE) has reported valuable outcomes in distress recognition. In the present work, the recently introduced symbolic metric called dispersion entropy (DispEn) is applied for the first time to the same problem. Statistically significant results reported by the single metric have demonstrated its capability for calm and distress detection. Furthermore, relevant differences have been found between the combination of QSampEn with either AAPE or DispEn, finding that the assessment of ordinal and dispersion patterns leads to distinct and complementary outcomes. Finally, the combination of the three entropy metrics has considerably overcome the results ever reported by other indices in similar studies.
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García-Martínez et al. (2021) studied Negative stress (distress). Dispersion entropy (DispEn) combined with QSampEn and AAPE vs. Single metrics and other indices was evaluated on Detection of calm and distress from EEG signals. The combination of dispersion entropy, quadratic sample entropy, and amplitude-aware permutation entropy significantly improved the detection of negative stress from EEG signals.
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