Now showing items 1-5 of 5
Mood state detection in handwritten tasks using PCA–mFCBF and automated machine learning
(MDPI, 2022 Feb 2)
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 ...
Emotional state recognition performance improvement on a handwriting and drawing task
In this work we combine time, spectral and cepstral features of the signal captured in a tablet to characterize depression, anxiety, and stress emotional state recognition on the EMOTHAW database. EMOTHAW ...
Analysis of fine motor skills in essential tremor: combining neuroimaging and handwriting biomarkers for early management
(Frontiers Media SA, 2021-06-08)
Essential tremor (ET) is a highly prevalent neurological disorder characterized by actioninduced tremors involving the hand, voice, head, and/or face. Importantly, hand tremor is present in nearly all ...
On handwriting pressure normalization for interoperability of different acquisition stylus
In this paper, we present a pressure characterization and normalization procedure for online handwritten acquisition. Normalization process has been tested in biometric recognition experiments (identification ...
Exploiting spectral and cepstral handwriting features on diagnosing Parkinson’s disease
Parkinson’s disease (PD) is the second most frequent neurodegenerative disease associated with several motor symptoms, including alterations in handwriting, also known as PD dysgraphia. Several computerized ...