Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/434916
Title: Investigations of asthma and ecg morphology segment analysis using gmr sensor and neural network
Researcher: Nithya Selvakumari S
Guide(s): Gowri Shankar A
Keywords: Engineering and Technology
Computer Science
Computer Science Information Systems
Chronic inflammation
arrhythmia disease
neural network
University: Anna University
Completed Date: 2021
Abstract: Recent researches have been focused on major respiratory problems in medical newlinefield. One such problem addressed in the current research work is asthma. Asthma is newlinecharacterised as a persistent airway inflammatory illness. Chronic inflammation is newlineinterlinked with airway hyper responsiveness, which directs to unceasing indications such newlineas gasping, dyspnea (breathlessness), muscle aches and sneezing (increased airwaynarrowing newlinestimulation such as allergic reactions and workout). Episodes of signs are newlineusually associated with widespread, but complex, restriction of ventilation inside the lungs newlinethat is potentially transient either naturally or with adequate care for asthma. newlineThe main objective of the present research work is to propose an efficient algorithm newlineknown as Rational-Dilation Wavelet Transforms (RADWT) algorithm to diagnose the newlineasthma disease. In this proposed work, GMR sensor has been utilized to monitor the newlineparameters of asthma along with algorithm .The methodology or the process obtains the newlinevalues of filter bank using RADWT algorithm with mathematical evaluations by hardware newlineimplementation. The results provided by the proposed algorithm have been increased up to newline85 percent in prediction of asthma disease as compared with existing researches. newline
Pagination: xii,118p.
URI: http://hdl.handle.net/10603/434916
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File42.57 kBAdobe PDFView/Open
02_prelim pages.pdf3.2 MBAdobe PDFView/Open
03_content.pdf18.69 kBAdobe PDFView/Open
04_abstract.pdf21.05 kBAdobe PDFView/Open
05_chapter 1.pdf1.02 MBAdobe PDFView/Open
06_chapter 2.pdf119.19 kBAdobe PDFView/Open
07_chapter 3.pdf1.52 MBAdobe PDFView/Open
08_chapter 4.pdf386.64 kBAdobe PDFView/Open
09_chapter 5.pdf2.1 MBAdobe PDFView/Open
10_chapter 6.pdf26.63 kBAdobe PDFView/Open
11_annexures.pdf135.5 kBAdobe PDFView/Open
80_recommendation.pdf54.74 kBAdobe PDFView/Open
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