?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=A+power+spectrum+based+backpropagation+artificial+neural+network+model+for+classification+of+sleep-wake+stages+in+rats&rft.creator=Sinha%2C+Mr+Rakesh+Kumar&rft.creator=Agrawal%2C+Mr+Navin+Kumar&rft.creator=Ray%2C+Dr+Amit+Kumar&rft.subject=Online+Journal+of+Health+and+Allied+Sciences&rft.description=Three+layered+feed-forward+backpropagation+artificial+neural+network+architecture+is+designed+to+classify+sleep-wake+stages+in+rats.+Continuous+three+channel+polygraphic+signals+such+as+electroencephalogram%2C+electrooculogram+and+electromyogram+were+recorded+from+conscious+rats+for+eight+hours+during+day+time.+Signals+were+also+stored+in+computer+hard+disk+with+the+help+of+analog+to+digital+converter+and+its+compatible+data+acquisition+software.+The+power+spectra+(in+dB+scale)+of+the+digitized+signals+in+three+sleep-wake+stages+were+calculated.+Selected+power+spectrum+data+of+all+three+simultaneously+recorded+polygraphic+signals+were+used+for+training+the+network+and+to+classify+slow+wave+sleep%2C+rapid+eye+movement+sleep+and+awake+stages.+The+ANN+architecture+used+in+present+study+shows+a+very+good+agreement+with+manual+sleep+stage+scoring+with+an+average+of+94.83%25+for+all+the+1200+samples+tested+from+SWS%2C+REM+and+AWA+stages.+The+high+performance+observed+with+the+system+based+on+ANN+highlights+the+need+of+this+computational+tool+into+the+field+of+sleep+research.&rft.publisher=Kakkilaya+BS&rft.contributor=Kakkilaya+Bevinje%2C+Dr+Srinivas&rft.date=2003-04&rft.type=Journal+(On-line%2FUnpaginated)&rft.type=PeerReviewed&rft.format=application%2Fpdf&rft.identifier=http%3A%2F%2Fcogprints.org%2F3227%2F1%2F2003-1-1.pdf&rft.identifier=++Sinha%2C+Mr+Rakesh+Kumar+and+Agrawal%2C+Mr+Navin+Kumar+and+Ray%2C+Dr+Amit+Kumar++(2003)+A+power+spectrum+based+backpropagation+artificial+neural+network+model+for+classification+of+sleep-wake+stages+in+rats.++%5BJournal+(On-line%2FUnpaginated)%5D+++++&rft.relation=http%3A%2F%2Fcogprints.org%2F3227%2F