Brain State Recognition Using Fuzzy C-Means (FCM) Clustering with Near Infrared Spectroscopy (NIRS) View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2001-09-26

AUTHORS

Syoji Kobashi , Yutaka Hata , Yuri T. Kitamura , Toshiaki Hayakata , Toshio Yanagida

ABSTRACT

Near-infrared spectroscopy (NIRS) is a recently developed method, which can investigate the human brain function with noninvasive, high time resolution, and high portability. However, there are few discussions on post-processing of time series data taken by the NIRS because of the difficulty of understanding the obtained data and the complexity of the human higher-order brain function. This paper discusses on an analysis of such a time series. The analysis method is based on fuzzy c-means (FCM) clustering and wavelet transform, and it divides the time series of a measurement point into some clusters with respect to wavelet coefficients. To evaluate the performance of the method, it has been applied to four healthy volunteers, and three brain-dead patients. The results showed that the proposed method could segment the NIRS time series into some clusters that may represent brain states, and could estimate the number of clusters. More... »

PAGES

124-136

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-45493-4_17

DOI

http://dx.doi.org/10.1007/3-540-45493-4_17

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1030371113


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