Transformer-Based Decomposition of Electrodermal Activity for Real-World Mental Health Applications

Transformer-Based Decomposition of Electrodermal Activity for Real-World Mental Health Applications

Decomposing Electrodermal Activity (EDA) into phasic (short-term, stimulus-linked responses) and tonic (longer-term baseline) components is essential for extracting meaningful emotional and physiological biomarkers. This study presents a comparative analysis of knowledge-driven, statistical, and dee...

Full description

Saved in:
Bibliographic Details
Main Authors: Charalampos Tsirmpas, Stasinos Konstantopoulos, Dimitris Andrikopoulos, Konstantina Kyriakouli, Panagiotis Fatouros
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Sensors
Subjects:
biosignal processing
phasic and tonic decomposition
time series detrending
electrodermal activity
wearable sensors
deep learning
Online Access:https://www.mdpi.com/1424-8220/25/14/4406
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/25/14/4406

Similar Items