Detection of signs of Parkinson's disease using dynamical features via an indirect pointing device

Ushirobira, Rosane; Efimov, Denis; Casiez, Géry; Fernandez, Laure; Olsson, Fredrik; Medvedev, Alexander

Detection of signs of Parkinson's disease using dynamical features via an indirect pointing device

detalle del documento

IDENTIFICACIÓN

oai:HAL:hal-02887913v1

Tema

Quantification of physiological pa... [SPI.AUTO]Engineering Sciences [ph...

Autor

Ushirobira, Rosane Efimov, Denis Casiez, Géry Fernandez, Laure Olsson, Fredrik Medvedev, Alexander

Langue

Editor

HAL CCSD

Categoría

CNRS - Centre national de la recherche scientifique

Año

2020

fecha de cotización

7/10/2023

Palabras clave

parkinson detection

Métrico

Resumen

International audience; In this paper, we study the problem of detecting early signs of Parkinson's disease during an indirect human-computer interaction via a computer mouse activated by a user.

The experimental setup provides a signal determined by the screen pointer position.

An appropriate choice of segments in the cursor position raw data provides a filtered signal from which a number of quantifiable criteria can be obtained.

These dynamical features are derived based on control theory methods.

Thanks to these indicators, a subsequent analysis allows the detection of users with tremor.

Real-life data from patients with Parkinson's and healthy controls are used to illustrate our detection method.

Ushirobira, Rosane,Efimov, Denis,Casiez, Géry,Fernandez, Laure,Olsson, Fredrik,Medvedev, Alexander, 2020, Detection of signs of Parkinson's disease using dynamical features via an indirect pointing device, HAL CCSD