Documentdetail
ID kaart
oai:HAL:hal-02887913v1
Onderwerp
Quantification of physiological pa... [SPI.AUTO]Engineering Sciences [ph...Auteur
Ushirobira, Rosane Efimov, Denis Casiez, Géry Fernandez, Laure Olsson, Fredrik Medvedev, AlexanderLangue
enEditor
HAL CCSD
Categorie
CNRS - Centre national de la recherche scientifique
Jaar
2020
vermelding datum
07-10-2023
Trefwoorden
parkinson detectionBeschrijving
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
Choice Between Partial Trajectories: Disentangling Goals from Beliefs
agents models aligned based bootstrapped learning reward function model return choice choices partial
Adverse and serious adverse events incidence of pharmacological interventions for managing chronic and episodic migraine in adults: a systematic review
aes medications bta incidence migraine drugs disorders
