Systolic and diastolic multiclass classification of PPG signals using neural network with random weight

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Systolic and diastolic multiclass classification of PPG signals using neural network with random weight

Photoplethysmography (PPG) signals can be defined as a type of signal which obtained through a noninvasive optical method that contains information of the cardiovascular system such as arterial blood pressure, tissue perfusion, heart rate and respiratory rate. Due to its noninvasive characteristics...

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Bibliographic Details
Main Authors:	Tan, Jiun Hann, Noor liza, Simon, Asrul, Adam
Format:	Conference or Workshop Item
Language:	English English
Published:	IEEE 2019
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/27704/ http://umpir.ump.edu.my/id/eprint/27704/1/43.%20Systolic%20and%20diastolic%20multiclass%20classification%20of%20PPG.pdf http://umpir.ump.edu.my/id/eprint/27704/2/43.1%20Systolic%20and%20diastolic%20multiclass%20classification%20of%20PPG.pdf

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