The classification of Electrooculogram (EOG) through the application of Linear Discriminant Analysis (LDA) of selected time-domain signals

• Main Authors: Farhan Anis, Azhar, Mahfuzah, Mustafa, Norizam, Sulaiman, Mamunur, Rashid, Bari, Bifta Sama, Islam, Md Nahidul, Hasan, Md Jahid, Nur Fahriza, Mohd Ali
• Format: Conference or Workshop Item
• Language: English; English
• Published: Springer Science and Business Media Deutschland GmbH 2022
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General); TJ Mechanical engineering and machinery; TK Electrical engineering. Electronics Nuclear engineering; TS Manufactures
• Online Access: http://umpir.ump.edu.my/id/eprint/42237/1/The%20classification%20of%20Electrooculogram%20%28EOG%29.pdf; http://umpir.ump.edu.my/id/eprint/42237/2/The%20classification%20of%20Electrooculogram%20%28EOG%29%20through%20the%20application%20of%20Linear%20Discriminant%20Analysis%20%28LDA%29%20of%20selected%20time-domain%20signals_ABS.pdf; http://umpir.ump.edu.my/id/eprint/42237/; https://doi.org/10.1007/978-981-33-4597-3_53

Recently, Human Computer Interface (HCI) has been studied extensively to handle electromechanical rehabilitation aids using different bio-signals. Among various bio-signals, electrooculogram (EOG) signal have been studied in depth due to its significant signal pattern stability. The primary goal of...