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abstract: A three-layered feed-forward back-propagation Artificial Neural Network was used to classify the seizure episodes in rats. Seizure patterns were induced by subjecting anesthetized rats to a Biological Oxygen Demand incubator at 45-47ºC for 30 to 60 minutes. Selected fast Fourier transform data of one second epochs of electroencephalogram were used to train and test the network for the classification of seizure and normal patterns. The results indicate that the present network with the architecture of 40-12-1 (input-hidden-output nodes) agrees with manual scoring of seizure and normal patterns with a high recognition rate of 98.6%.
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- http://www.ojhas.org/issue4/2002-4-1.htm
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creators_id:
- Sinha RK
creators_name:
- family: Sinha
given: Rakesh Kumar
honourific: Mr
lineage: ''
date: 2002-12
date_type: published
datestamp: 2003-10-17
department: ~
dir: disk0/00/00/32/26
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editors_id:
- Kakkilaya BS
editors_name:
- family: Kakkilaya
given: Srinivas
honourific: Dr
lineage: Bevinje
eprint_status: archive
eprintid: 3226
fileinfo: /style/images/fileicons/application_pdf.png;/3226/1/2002%2D4%2D1.pdf
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keywords: 'Artificial Neural Network, fast Fourier transform, electroencephalogram, Hyperthermic seizures'
lastmod: 2011-03-11 08:55:22
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number: 4
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publication: Online Journal of Health and Allied Sciences
publisher: Kakkilaya BS
refereed: TRUE
referencetext: |-
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reportno: ~
rev_number: 12
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status_changed: 2007-09-12 16:49:13
subjects:
- OJHAS
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title: Backpropagation Artificial Neural Network To Detect Hyperthermic Seizures In Rats
type: journale
userid: 4338
volume: 1