SLEEP CLASSIFICATION IN INFANTS BASED ON ARTIFICIAL NEURAL NETWORKS

被引：18

作者：

PFURTSCHELLER, G ^{[1
]}

FLOTZINGER, D ^{[1
]}

MATUSCHIK, K ^{[1
]}

机构：

[1] GRAZ TECH UNIV,LUDWIG BOLTZMANN INST MED INFORMAT & NEUROINFORMAT,A-8010 GRAZ,AUSTRIA

来源：

BIOMEDIZINISCHE TECHNIK | 1992年 / 37卷 / 06期

关键词：

SLEEP CLASSIFICATION; NEURAL NETWORKS;

D O I：

10.1515/bmte.1992.37.6.122

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

The study reports on the possibility of classifying sleep stages in infants using an artificial neural network. The polygraphic data from 4 babies aged 6 weeks, 6 months and 1 year recorded over 8 hours were available for classification. From each baby 22 signals were recorded, digitized and stored on an optical disc. Subsets of these signals and additional calculated parameters were used to obtain data vectors, each of which represents an interval of 30 sec. For classification, two types of neural networks were used, a Multilayer Perceptron and a Learning Vector Quantizer. The teaching input for both networks was provided by a human expert. For the 6 sleep classes in babies aged 6 months, a 65% to 80% rate of correct classification (4 babies) was obtained for the testing data not previously seen.

引用

页码：122 / 130

页数：9