Towards an inclusive Parkinson´s screening system

Author

Geman, Oana ; Sanei, Saeid ; Chiuchisan, Iulian ; Graur, Adrian ; Prochazka, A. ; Vysata, O.

Author_Institution

Dept. of Health & Human Dev., “Stefan cel Mare” Univ. of Suceava, Suceava, Romania

fYear

2014

fDate

17-19 Oct. 2014

Firstpage

470

Lastpage

475

Abstract

In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson´s disease (the most important Neurodegenerative Disorder). Analysis of the information corresponding to a prescribed movement involving tremor, and the related changes in brain connectivity is novel and original. Analytically, developing a space-time nonlinear adaptive system which fuses brain and gait information algorithmically is proposed here for the first time. The overall dynamic system will be constrained by the clinical impressions of the patient symptoms embedded in a knowledge-based system. The entire complex constrained problem were solved to enable a powerful model for recognition and monitoring of Parkinson´s disease and establishing appropriate rules for its clinical following up.

Keywords

biomedical equipment; brain; data acquisition; data analysis; feature extraction; gait analysis; knowledge based systems; medical disorders; medical signal processing; neurophysiology; nonlinear dynamical systems; patient diagnosis; patient monitoring; sensor fusion; signal classification; space-time adaptive processing; Parkinson disease clinical following up rule; Parkinson disease diagnosis; Parkinson disease monitoring; Parkinson disease recognition; algorithmic fusion; brain connectivity change; brain dynamic information; clinical impression embedding; complex constrained problem; dynamic system constraint; gait dynamic information; inclusive Parkinson screening system; information analysis; information fusion; knowledge based system; neurodegenerative disorder; patient symptom; space-time nonlinear adaptive system; tremor movement; Adaptation models; Brain modeling; Chaos; Nonlinear dynamical systems; Parkinson´s disease; Signal processing algorithms; Gait; Intelligent Sensors; Knowledge-based System; Neurodegenerative Disorders; Nonlinear Dynamics; Tremor;

fLanguage

English

Publisher

ieee

Conference_Titel

System Theory, Control and Computing (ICSTCC), 2014 18th International Conference

Conference_Location

Sinaia

Type

conf

DOI

10.1109/ICSTCC.2014.6982461

Filename

6982461