f Advancing Sleep Stage Classification with EEG Signal Analysis: LSTM Optimization Using Puffer Fish Algorithm and Explainable AI
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Advancing Sleep Stage Classification with EEG Signal Analysis: LSTM Optimization Using Puffer Fish Algorithm and Explainable AI

Author(s): Srinivasa Rao Vemula, Maruthi Vemula, Ghamya Kotapati, Lokesh Sai Kiran Vatsavai, Lakshmi Naga Jayaprada Gavarraju and Ramesh Vatambeti*

Publisher : FOREX Publication

Published : 25 June 2024

e-ISSN : 2347-470X

Page(s) : 596-604




Srinivasa Rao Vemula, Software Test Analyst Senior, FIS Management Services, Durham, North Carolina 27703-8589, USA; Email: srinivas.vemula@fisglobal.com

Maruthi Vemula, Student, North Carolina School of Science and Mathematics, Durham, North Carolina 27705, USA; Email: vemula24m@ncssm.edu

Ghamya Kotapati, Department of AI & ML, School of Computing, Mohan Babu University, Tirupati 517102, India; Email: ghamyakotapati@gmail.com

Lokesh Sai Kiran Vatsavai, Department of Information Technology, SRKR Engineering College, Bhimavaram 534204, India; Email: lokesh3069@srkrec.ac.in

Lakshmi Naga Jayaprada Gavarraju, Department of Computer Science and Engineering, Malla Reddy College of Engineering and Technology, Hyderabad 500100, India; Email: lakshminagajayaprada.g@mrcet.ac.in

Ramesh Vatambeti*, School of Computer Science and Engineering, VIT-AP University, Vijayawada 522237, India; Email: v2ramesh634@gmail.com

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Srinivasa Rao Vemula, Maruthi Vemula, Ghamya Kotapati, Lokesh Sai Kiran Vatsavai, Lakshmi Naga Jayaprada Gavarraju and Ramesh Vatambeti (2024), Advancing Sleep Stage Classification with EEG Signal Analysis: LSTM Optimization Using Puffer Fish Algorithm and Explainable AI. IJEER 12(2), 596-604. DOI: 10.37391/IJEER.120235.