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Output details

13 - Electrical and Electronic Engineering, Metallurgy and Materials

University of York

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Output 16 of 85 in the submission

Article title

Characterising Neurological Time Series Data using Biologically-Motivated Networks of Coupled Discrete Maps

Type

D - Journal article

DOI

10.1016/j.biosystems.2013.03.009

Title of journal

Biosystems

Article number

Volume number

112

Issue number

First page of article

ISSN of journal

0303-2647

Year of publication

2013

URL

http://www.sciencedirect.com/science/article/pii/S0303264713000531

Number of additional authors

Additional information

This paper realises advances in the development of novel evolutionary algorithms for the diagnosis of Parkinson’s disease. Patient measurements undertaken at Leeds General Infirmary exceeded 90% accuracy - significantly higher than the 75% observed in routine clinical practice. This work provided the foundation on which a Royal Academy of Engineering Enterprise Fellowship was awarded to support commercialisation of the technology.

Interdisciplinary

Cross-referral requested

Research group

B - Intelligent Systems

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract