Deep learning based arrhythmia classification on low-cost and low-compute MCU

Deep learning based arrhythmia classification on low-cost and low-compute MCU

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Detalhes bibliográficos
Principais autores: Zishan, Md Abu Obaida, Shihab, H M, Rahman, Gazi Mashrur, Islam, Sabik Sadman, Riya, Maliha Alam
Outros Autores: Mukta, Jannatun Noor
Formato: Tese
Idioma:English
Publicado em: Brac University 2023
Assuntos:
ECG
Arrhythmia
Low-cost
Low-compute
Low-power
Machine learning
Micro-controller
Cognitive learning theory (Deep learning)
Acesso em linha:http://hdl.handle.net/10361/22018

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