Article Dans Une Revue Progress in brain research Année : 2024

HRV and EEG correlates of well-being using ultra-short, portable, and low-cost measurements

Résumé

Wearable electroencephalography (EEG) and electrocardiography (ECG) devices may offer a non-invasive, user-friendly, and cost-effective approach for assessing well-being (WB) in real-world settings. However, challenges remain in dealing with signal artifacts (such as environmental noise and movements) and identifying robust biomarkers. We evaluated the feasibility of using portable hardware to identify potential EEG and heart-rate variability (HRV) correlates of WB. We collected simultaneous ultrashort (2-min) EEG and ECG data from 60 individuals in real-world settings using a wrist ECG electrode connected to a 4-channel wearable EEG headset. These data were processed, assessed for signal quality, and analyzed using the open-source EEGLAB BrainBeats plugin to extract several theory-driven metrics as potential correlates of WB. Namely, the individual alpha frequency (IAF), frontal and posterior alpha asymmetry, and signal entropy for EEG. SDNN, the low/high frequency (LF/HF) ratio, the Poincaré SD1/SD2 ratio, and signal entropy for HRV. We assessed potential associations between these features and the main WB dimensions (hedonic, eudaimonic, global, physical, and social) implementing a pairwise correlation approach, robust Spearman's correlations, and corrections for multiple comparisons. Only eight files showed poor signal quality and were excluded from the analysis. Eudaimonic (psychological) WB was positively correlated with SDNN and the LF/HF ratio. EEG posterior alpha asymmetry was positively correlated with Physical WB (i.e., sleep and pain levels). No relationships were found with the other metrics, or between EEG and HRV metrics. These physiological metrics enable a quick, objective assessment of well-being in real-world settings using scalable, user-friendly tools.

Fichier principal
Vignette du fichier
Wellbeing, HRV, and EEG v4 - revisions.pdf (352.75 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-04731564 , version 1 (23-10-2024)

Licence

Identifiants

Citer

Cédric Cannard, Arnaud Delorme, Helané Wahbeh. HRV and EEG correlates of well-being using ultra-short, portable, and low-cost measurements. Progress in brain research, 2024, The Neurophysiology of Silence (C): Creativity, Aesthetic Experience and Time, 287, pp.91-109. ⟨10.1016/bs.pbr.2024.04.004⟩. ⟨hal-04731564⟩
177 Consultations
634 Téléchargements

Altmetric

Partager

  • More