UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRDF06028


Registration ID:
223851

Page Number

138-144

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Title

DIAGNOSIS OF HYPERNYCHTHEMERAL SYNDROME USING MACHINE LEARNING

Abstract

Hypernychthemeral syndrome is a disorder that affects normal 24-hour synchronization of circadian rhythms.The Circadian Rhythm is an internal biological clock situated in the brain of all living organisms.Circadian rhythms can influence sleep-wake cycles, hormone release, body temperature, heartbeat rate and other important bodily functions. Circadian rhythms are important in determining human sleep patterns.This disease occurs in blind people but can occur in normal people as well.The diagnosis and monitoring of this disease is done using a sleep diary that has to be maintained by the patients themselves which is a tedious task.Our approach is to use different sensors to analyse the environment condition,Sleep pattern,temperature,heart rate process the data by using k-means clustering and then classify them using the random forest algorithm to get the accurate prediction of this disease.Based on the output the warning is displayed to the patients through a web application as an alarm.This also helps to provide further monitoring of the disease based on the medication given to the patients.

Key Words

Hypernychthemeral syndrome,circadian rhythm,k-means,Random forest..

Cite This Article

"DIAGNOSIS OF HYPERNYCHTHEMERAL SYNDROME USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.138-144, June 2019, Available :http://www.jetir.org/papers/JETIRDF06028.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"DIAGNOSIS OF HYPERNYCHTHEMERAL SYNDROME USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp138-144, June 2019, Available at : http://www.jetir.org/papers/JETIRDF06028.pdf

Publication Details

Published Paper ID: JETIRDF06028
Registration ID: 223851
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 138-144
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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