A Preliminary Cooperative Genetic Fuzzy Proposal for Epilepsy Identification Using Wearable Devices View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

E. A. de la Cal , J. R. Villar , P. M. Vergara , J. Sedano , A. Herrero

ABSTRACT

The epilepsy is one of the neurological disorders that affects people of all socioeconomic groups and ages. An incorrect treatment or a lack in monitoring might produce cognitive damage and depression. In previous work we presented a preliminary method for learning a generalized model to identify epilepsy episodes using 3DACC wearable devices placed on the dominant wrist of the subject. The model was based on a Fuzzy Finite State Machines to detect the epilepsy episodes in 3DACC time series. The learning model applied was a classical Genetic Fuzzy Finite State Machine. The goal of the present work is to adapt the previous learning scheme to a Cooperative Coevolutionary Genetic Fuzzy Finite State Machine to improve the classification results. The obtained results show that a Cooperative proposal outperform moderately the results of the original proposal. More... »

PAGES

49-63

References to SciGraph publications

Book

TITLE

10th International Conference on Soft Computing Models in Industrial and Environmental Applications

ISBN

978-3-319-19718-0
978-3-319-19719-7

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-19719-7_5

DOI

http://dx.doi.org/10.1007/978-3-319-19719-7_5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1049684687


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