Browsing Articles by Title

Now showing items 2-5 of 5

    • Emotional state recognition performance improvement on a handwriting and drawing task 

      Nolazco Flores, Juan Arturo; Faundez-Zanuy, Marcos; Velázquez-Flores, O. A.; Cordasco, Gennaro; Esposito, Anna (IEEE Access. 2021 Feb 23;(9):28496-28504, 2021-02-21)
      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 ...

    • Exploiting spectral and cepstral handwriting features on diagnosing parkinson’s disease 

      Nolazco Flores, Juan Arturo; Faundez-Zanuy, Marcos; de la Cueva, Victor; Mekyska, Jiri (IEEE Access. 2021 Oct 22;(9):141599-141610, 2021-10-22)
      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 ...

    • Mood state detection in handwritten tasks using PCA–mFCBF and automated machine learning 

      Nolazco Flores, Juan Arturo; Faundez-Zanuy, Marcos; Velázquez-Flores, O. A.; Del-Valle-Soto, Carolina; Cordasco, Gennaro; Esposito, Anna (Sensors. 2022 Feb 21;22(4):1686, 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 ...

    • On handwriting pressure normalization for interoperability of different acquisition stylus 

      Faundez-Zanuy, Marcos; Brotons-Rufes, Olga; Paul Recarens, Carles; Plamondon, Réjean (IEEE Access. 2021 Jan 21;9:18443-18453, 2021-01-21)
      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 ...