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Artificial intelligence based non-invasive blood glucose level estimation using PPG sensor

By:

Azam Khan (27711)

Material type: Text

TextPublication details: Islamabad (Unpublished) 2024Description: xiii , 43 p. : ill. ; 30 cm. +CDSubject(s):

Electrical engineering -- power line interference -- Primatene ventricular -- Motion artifact -- Single wave -- Energy -- FEAS

DDC classification:

621.31 AZA

Dissertation note: Thesis (M.S.)--Riphah International University, 2024

List(s) this item appears in: FEAS & DBS Thesis I-14 Campus

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Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Thesis	Main Campus	621.31 AZA (Browse shelf(Opens below))	1	NOT for LOAN		102795

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering to the Faculty of Engineering and Applied Sciences.

Includes bibliographical references.

Thesis supervisor: Dr. Shahreyar Najam

Thesis (M.S.)--Riphah International University, 2024

English

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