Classification of Sleep Stages Based on Electrocardiography Using a Hybrid Deep Learning Approach

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Journal Title
Journal ISSN
Volume Title
Perustieteiden korkeakoulu | Master's thesis
Date
2022-12-13
Department
Major/Subject
Systems and Operations Research
Mcode
SCI3055
Degree programme
Master’s Programme in Mathematics and Operations Research
Language
en
Pages
68+6
Series
Description
Supervisor
Ilmonen, Pauliina
Thesis advisor
Kumpula, Ossi
Keywords
sleep staging, electrocardiography analysis, heart rate variability, deep learning, self-attention
Other note
Citation