no code implementations • 5 Feb 2023 • Gennaro Raimo, Michele Buonanno, Massimiliano Conson, Gennaro Cordasco, Marcos Faundez-Zanuy, Stefano Marrone, Fiammetta Marulli, Alessandro Vinciarelli, Anna Esposito
The aim of this study is to use a new tool, the online handwriting and drawing analysis, to discriminate between healthy individuals and depressed patients.
To this date, studies focusing on the prodromal diagnosis of Lewy body diseases (LBDs) based on quantitative analysis of graphomotor and handwriting difficulties are missing.
Therefore, in this study, we follow up on our previous research, and we aim to explore the utilization of various approaches of fractional order derivative (FD) in the analysis of PD dysgraphia.
This paper describes a hand geometry biometric identification system.
This Paper studies different committees of neural networks for biometric pattern recognition.
This paper proposes the use of a discrete cosine transform (DCT) instead of the eigenfaces method (Karhunen-Loeve Transform) for biometric identification based on frontal face images.
Advanced motion models (4 or 6 parameters) are needed for a good representation of the motion experimented by the different objects contained in a sequence of images.
When focusing an image, depth of field, aperture and distance from the camera to the object, must be taking into account, both, in visible and in infrared spectrum.
This work defines a procedure for collecting naturally induced emotional facial expressions through the vision of movie excerpts with high emotional contents and reports experimental data ascertaining the effects of emotions on memory word recognition tasks.
Practical determination of physical recovery after intense exercise is a challenging topic that must include mechanical aspects as well as cognitive ones because most of physical sport activities, as well as professional activities (including brain computer interface-operated systems), require good shape in both of them.
In this paper, we present a pressure characterization and normalization procedure for online handwritten acquisition.
There was almost perfect agreement between the Polar V800 compared to a force platform for the SJ and CMJ tests (Mean ICCs = 0. 95; no systematic bias +- random errors in SJ mean: -0. 38 +- 2. 10 cm, p > 0. 05).
Experimental results with MCYT provide a 99. 76% identification rate and 2. 46% EER (skilled forgeries and individual threshold).
Most of medical developments require the ability to identify samples that are anomalous with respect to a target group or control group, in the sense they could belong to a new, previously unseen class or are not class data.
Up to 90% of patients with Parkinson's disease (PD) suffer from hypokinetic dysathria (HD) which is also manifested in the field of phonation.
no code implementations • 18 Mar 2022 • Karmele López-de-Ipiña, Alberto Bergareche, Patricia De La Riva, Jordi Sole-Casals, Marcos Faundez-Zanuy, Jose Felix Marti-Masso, Mikel Iturrate, Blanca Beitia, Pilar Calvo, Enric Sesa-Nogueras, Josep Roure, Itziar Gurrutxaga, Joseba Garcia-Melero
Biomedical systems are regulated by interacting mechanisms that operate across multiple spatial and temporal scales and produce biosignals with linear and non-linear information inside.
We show that pressure and in-air movement also possess information that is relevant for the diagnosis of Parkinson's Disease (PD) from handwriting.
no code implementations • 18 Mar 2022 • Jan Mucha, Zoltan Galaz, Jiri Mekyska, Tomas Kiska, Vojtech Zvoncak, Zdenek Smekal, Ilona Eliasova, Martina Mrackova, Milena Kostalova, Irena Rektorova, Marcos Faundez-Zanuy, Jesus B. Alonso-Hernandez
In this work, we analysed the power of conventional speech features quantifying imprecise articulation, dysprosody, speech dysfluency and speech quality deterioration extracted from a specialized poem recitation task to discriminate dysarthric and healthy speech.
Although in this case results are not conclusive, an outstanding average of 74% of well classified writers is obtained when information from pen-up strokes is combined with information from pen-down ones.
In this paper we present some experiments to automatically classify online handwritten text based on capital letters.
no code implementations • 10 Mar 2022 • Marcos Faundez-Zanuy, Antonio Satue-Villar, Jiri Mekyska, Viridiana Arreola, Pilar Sanz, Carles Paul, Luis Guirao, Mateu Serra, Laia Rofes, Pere Clavé, Enric Sesa-Nogueras, Josep Roure
Parkinson's disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0. 1-1 %, and an annual incidence between 1. 3-2. 0/10000 inhabitants.
The present work is based on the COST Action IC1206 for De-identification in multimedia content.
Dementia, and specially Alzheimer s disease (AD) and Mild Cognitive Impairment (MCI) are one of the most important diseases suffered by elderly population.
This paper contributes to this research line analyzing a selected set of online handwriting parameters provided by a healthy group of population aged from 18 to 70 years.
This paper deals the combination of nonlinear predictive models with classical LPCC parameterization for speaker recognition.
In this paper we compare several ADPCM schemes with nonlinear prediction based on neural nets with the classical ADPCM schemes based on several linear prediction schemes.
This paper presents a new database collected from a bilingual speakers set (49), in two different languages: Spanish and Catalan.
Recently several papers have been published on nonlinear prediction applied to speech coding.
A novel approach for speech segmentation is proposed, based on Multilevel Hybrid (mean/min) Filters (MHF) with the following features: An accurate transition location.
This paper presents an exhaustive study about the robustness of several parameterizations, in speaker verification and identification tasks.
In this paper we discuss the relevance of bandwidth extension for speaker identification tasks.
In this paper we present a new database acquired with three different sensors (visible, near infrared and thermal) under different illumination conditions.
Background- This paper summarizes the state-of-the-art and applications based on online handwritting signals with special emphasis on e-security and e-health fields.
For each fatigue level, the identification and verification performance of these methods is measured.
Background: An advantageous property of behavioural signals , e. g. handwriting, in contrast to morphological ones, such as iris, fingerprint, hand geometry, etc., is the possibility to ask a user for a very rich amount of different tasks.
We use this ranking process to identify the features which best reveal a targeted emotional state.
Recent advances in speech technologies have produced new tools that can be used to improve the performance and flexibility of speaker recognition While there are few degrees of freedom or alternative methods when using fingerprint or iris identification techniques, speech offers much more flexibility and different levels for performing recognition: the system can force the user to speak in a particular manner, different for each attempt to enter.
The performance of block matching methods has been measured in terms of the entropy in the error signal between the motion compensated and the original frames.
Methods In this paper, we will analyze a large set of databases (BIOSECURID, EMOTHAW, PaHaW, Oxygen-Therapy and SALT), which contain a total amount of 663 users and 17951 files.
This context corresponds to a real operation, where a new user tries to enroll an existing system and must be automatically guided by the system in order to detect the failure to enroll situations.
In this paper we present a method to identify people by means of thermal (TH) and visible (VIS) hand images acquired simultaneously with a TESTO 882-3 camera.
Although there has been a dramatically reduction on the prices of capturing devices and an increase on computing power in the last decade, it seems that biometric systems are still far from massive adoption for civilian applications.
In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system.
In this article, the authors discuss the problem of forensic authentication of digital audio recordings.
no code implementations • 2 Nov 2021 • Julian Fierrez, Javier Galbally, Javier Ortega-Garcia, Manuel R Freire, Fernando Alonso-Fernandez, Daniel Ramos, Doroteo Torre Toledano, Joaquin Gonzalez-Rodriguez, Juan A Siguenza, Javier Garrido-Salas, E Anguiano, Guillermo Gonzalez-de-Rivera, Ricardo Ribalda, Marcos Faundez-Zanuy, JA Ortega, Valentín Cardeñoso-Payo, A Viloria, Carlos E Vivaracho, Q Isaac Moro, Juan J Igarza, J Sanchez, Inmaculada Hernaez, Carlos Orrite-Urunuela, Francisco Martinez-Contreras, Juan José Gracia-Roche
A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol.