Current methods and new trends in signal processing and pattern recognition for the automatic assessment of motor impairments: the case of Parkinson's disease
Orozco-Arroyave JR, Vasquez Correa J, Nöth E (2020)
Publication Language: English
Publication Type: Book chapter / Article in edited volumes
Publication year: 2020
Publisher: IOP
Edited Volumes: Neurological Disorders and Imaging Physics, Volume 5 Applications in dyslexia, epilepsy and Parkinson's
Book Volume: 5
ISBN: 978-0-7503-2723-7
URI: https://iopscience.iop.org/chapter/978-0-7503-2723-7/bk978-0-7503-2723-7ch8.pdf
DOI: 10.1088/978-0-7503-2723-7ch8
Abstract
This chapter describes current methods and future trends in signal processing and pattern recognition techniques applied to the automatic analysis of motor impairments observed in patients with Parkinson's disease (PD). A revision of the state-of-the-art is presented considering methods and applications that include the analysis of speech, gait, and handwriting signals for the evaluation of PD. The suitability of existing methods and the potential use of novel approaches are also presented in the context of the automatic diagnosis and monitoring of the disease progression. Apart from the classical clinical scales used to assess the neurological state of PD patients, specific scales designed to evaluate the speech impairments of the patients are also reviewed. Additionally, the suitability of a modified version of the Frenchay Dysarthria Assessment scale (m-FDA) is evaluated. Besides the classical signal processing methods based on the analysis in the time and frequency domains, other methods that consider non-linear features and also deep neural networks are explored in several experiments.
Authors with CRIS profile
Juan Vasquez Correa
Professur für Informatik (Mustererkennung)
Elmar Nöth
Professur für Informatik (Mustererkennung)
Involved external institutions
Colombia (CO)How to cite
APA:
Orozco-Arroyave, J.R., Vasquez Correa, J., & Nöth, E. (2020). Current methods and new trends in signal processing and pattern recognition for the automatic assessment of motor impairments: the case of Parkinson's disease. In Ayman El-Baz and Jasjit S Suri (Eds.), Neurological Disorders and Imaging Physics, Volume 5 Applications in dyslexia, epilepsy and Parkinson's. IOP.
MLA:
Orozco-Arroyave, J. R., Juan Vasquez Correa, and Elmar Nöth. "Current methods and new trends in signal processing and pattern recognition for the automatic assessment of motor impairments: the case of Parkinson's disease." Neurological Disorders and Imaging Physics, Volume 5 Applications in dyslexia, epilepsy and Parkinson's. Ed. Ayman El-Baz and Jasjit S Suri, IOP, 2020.
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