CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Knowledge based System for the Diagnosis of Sleep Disorders

by Vijay Kumar Garg, R.k. Bansal
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 110 - Number 1
Year of Publication: 2015
Authors: Vijay Kumar Garg, R.k. Bansal
10.5120/19284-0702

Vijay Kumar Garg, R.k. Bansal . Knowledge based System for the Diagnosis of Sleep Disorders. International Journal of Computer Applications. 110, 1 ( January 2015), 47-51. DOI=10.5120/19284-0702

@article{ 10.5120/19284-0702,
author = { Vijay Kumar Garg, R.k. Bansal },
title = { Knowledge based System for the Diagnosis of Sleep Disorders },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 110 },
number = { 1 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 47-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume110/number1/19284-0702/ },
doi = { 10.5120/19284-0702 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:45:16.763195+05:30
%A Vijay Kumar Garg
%A R.k. Bansal
%T Knowledge based System for the Diagnosis of Sleep Disorders
%J International Journal of Computer Applications
%@ 0975-8887
%V 110
%N 1
%P 47-51
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Intelligent computing systems (ICS) and knowledge-based systems (KBS) have shown an imperative aspect in the detection and interpretation of electroencephalography (EEG) based sleep disorders that are associated by psychological and physiological factors like Sleep Apnea, Insomnia, Parasomnia and Snoring. Heuristic detection methods based on EEG parameters for sleep disorders have also been described in the paper, and a small attempt has been made to integrate rule-based reasoning (RBR) and case-based reasoning belongs to KBS. Integrated methods of RBR and CBR enhance the computation and logical competence of thought process involved to solve a problem. In this paper, an integrated model is developed in which RBR and CBR used for developing cases which are further used for detection and interpretation of sleep disorders. All these sleep disorders are framed into physio-psycho (muscular, cognitive and psychological) and EEG based parameters. The prime aim of this paper is to develop a combined model based on RBR and CBR in which RBR interacts with the sign and symptoms of the disorders, CBR is used for recognize the sleep disorders.

References
  1. B. Pandey, R. B. Mishra, "An integrated intelligent computing model for the interpretation of EMG based neuromuscular diseases", Expert Systems with Applications, Elsevier, Vol. 36, Issue 5, July 2009, pp. 9201–921.
  2. B. Pandey, R. B. Mishra, "An integrated intelligent computing model for the detection and interpretation of ECG based cardiac diseases", Int. J. Knowledge Engineering and Soft Data Paradigms, Vol. 2(2), 2010, pp. 182-203.
  3. M Cabrero-Canosaa, M Castro-Pereiroa, M Grana-Ramosa, E Hernandez-Pereiraa, V Moret-Bonilloa, M Martin-Eganab, H Verea-Hernandob, "An intelligentsystem for the detection and interpretation of sleep apneas" Expert Systems with Applications, Elsevier, Vol. 24, Issue 4, May 2003, pp. 335–349.
  4. Derong Liu, Zhongyu Pang and Stephen R. Lloyd, "A Neural Network Method for Detection of Obstructive Sleep Apnea and Narcolepsy Based on Pupil Size and EEG", IEEE Transactions on Neural Networks, Vol. 19, NO. 2, Feb 2008, pp. 308-318.
  5. F. Roche, V. Pichot, E. Sforza , I. Court-Fortune, D. Duverney , F. Costes , M. Garet and J-C. Barthelemy, " Predicting sleep apnoea syndrome from heart period: a time-frequency wavelet analysis", European Respiratory Journal, 2003, pp. 943-950.
  6. Ancoli-Israel S, Cole R, Alessi C et al, "The role of actigraphy in the study of sleep and circadian rhythms. American Academy of Sleep Medicine", Review Paper. Sleep, Vol. 26, issue 3, 2003, pp. 342-92.
  7. R. Nisha Aurora, Susmita Chowdhuri, Kannan Ramar, Sabin R. Bista, Kenneth R. Casey, Carin I. Lamm, David A. Kristo, Jorge M. Mallea, James A. Rowley, Rochelle S. Zak, Sharon L. Tracy, "Practice Parameters with an Evidence-Based Literature Review and Meta-Analyses", The Treatment of Central Sleep Apnea Syndromes in Adults, Vol. 35, No. 1, 2012.
  8. Schenck CH, Boyd JL, Mahowald MW, "A parasomnia overlap disorder involving sleepwalking, sleep terrors, and REM sleep behavior disorder in 33 polysomnographically confirmed cases", US National Library of Medicine National Institutes of Health , Vol. 20, Issue 11, 1997, pp. 972-981.
  9. Taylor DJ, Mallory LJ, Lichstein KL et al, "Comorbidity of chronic insomnia with medical problems", Sleep, Vol. 30, Issue 2, 2007, pp. 213-218.
  10. Dominique Petita, Jean-François Gagnona, Maria Livia Fantinia, Luigi Ferini-Strambid, Jacques Montplaisir, "Sleep and quantitative EEG in neurodegenerative disorders ", Journal of Psychosomatic Research Vol. 56, Issue 5, May 2004, pp. 487–496.
  11. Almendros I, Acerbi I, Puig F et al, "Upper-airway inflammation triggered by vibration in a rat model of snoring" SLEEP, Vol. 30, Issue 2, 2006, pp. 225-227.
  12. http://www. jblearning. com/catalog/9780763776473/
  13. http://www. webmd. com/sleep-disorders/tc/snoring-symptoms
  14. http://www. webmd. com/sleep-disorders/sleep-disorders-causes
  15. http://www. helpguide. org/life/sleep_disorders. htm
  16. Sinton, C. M. and McCarley, R. W. 2012. Sleep Disorders. els
  17. http://en. wikipedia. org/wiki/Case-based_reasoning
  18. http://en. wikipedia. org/wiki/Rule-based_reasoning
Index Terms

Computer Science
Information Sciences

Keywords

CBR EEG RBR Sleep Disorders

Powered by PhDFocusTM