Parkinson's disease diagnosis using modular systems
Paper i proceeding, 2013

In this paper, we present two modular systems for Parkinson's disease diagnosis. Also, we compare the frequency and chaotic behavior of rest tremor velocity in the index finger of some parkinsonian and healthy subjects. The proposed methods consist of two different modules, first, high-dimensional features are compressed by local linear and nonlinear principal component analysis (PCA) techniques and then, the features are classified by neural classifiers. The results indicate the efficiency of modular systems in Parkinson's disease diagnosis.


Mona Noori-Hosseini

Chalmers, Signaler och system, System- och reglerteknik, Automation

Behrooz Makki

Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

Proceedings - 2013 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2013