Mood State Detection in Handwritten Tasks Using PCA–mFCBF and Automated Machine Learning

Mood State Detection in Handwritten Tasks Using PCA–mFCBF and Automated Machine Learning

In this research, we analyse data obtained from sensors when a user handwrites or draws on a tablet to detect whether the user is in a specific mood state. First, we calculated the features based on the temporal, kinematic, statistical, spectral and cepstral domains for the tablet pressure, the hori...

Full description

Bibliographic Details
Main Authors: Juan Arturo Nolazco-Flores, Marcos Faundez-Zanuy, Oliver Alejandro Velázquez-Flores, Carolina Del-Valle-Soto, Gennaro Cordasco, Anna Esposito
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Sensors
Subjects:
autoML
data augmentation
negative mood states recognition
feature extraction
SVM
Online Access:https://www.mdpi.com/1424-8220/22/4/1686

Internet

https://www.mdpi.com/1424-8220/22/4/1686

Similar Items