AUTOMATIC DIAGNOSIS OF MITRAL STENOSIS DISEASE BY IMPEDANCE CARDIOGRAPHY SIGNAL PROCESSING (ICG)

Journal Title: INNOVATIVE JOURNAL OF MEDICAL AND HEALTH SCIENCE - Year 2017, Vol 7, Issue 1

Abstract

The di ag nosis of car diovascular diseas es could b e pe rform ed by seve ral invasive an d no n-inv asive methods. A no n-invasive m et hod for c ar diac diseases quantification is described in this paper. Our method uses discriminant analysis of seven cepstral parameters computed from the Impe da nce ca rdiog ra phy sign al (ICG) which r ep rese nts a n imped anc e variation in explored tho racic r e gion at th e level of t he ascen din g ao r ta. I n this study we have performed the assessment of two ki nds of serious mitral stenosis (MS++) and very serious (M S+++) disease. Thes e diseas esare alre ady w ell known by conve ntio nal m etho ds (ca rdiovascular cath et eriz ation an d ec ho-Doppler methods). A data base of 62 subjects (10 normal and 52 with different kinds of cardiac diseases) is used. The sample of the mitral stenosis diseases is constituted by six cases. Results show that the fish er dista nces (dij) of mitral stenosis diseases are minimum which rep res en ts a confirm atio n of th e n at ur e of th ese dise ases. Thes e res ults ar e confirme d by Stew art Ha milton dilu tion m ethod an d C ardiac Echo-Do pple r meth od.

Authors and Affiliations

Tareq Hadidi

Keywords

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  • EP ID EP312614
  • DOI 10.15520/ijmhs.2017.vol7.iss1.152.
  • Views 110
  • Downloads 0

How To Cite

Tareq Hadidi (2017). AUTOMATIC DIAGNOSIS OF MITRAL STENOSIS DISEASE BY IMPEDANCE CARDIOGRAPHY SIGNAL PROCESSING (ICG). INNOVATIVE JOURNAL OF MEDICAL AND HEALTH SCIENCE, 7(1), 12-17. https://europub.co.uk/articles/-A-312614