Evaluating machine learning methods for detecting sleep arousal

Evaluating machine learning methods for detecting sleep arousal

Sleep arousal is a phenomenon that affects the sleep of a large amount of people. The process of predicting and classifying arousal events is done manually with the aid of certified technologists, although some research has been done on automation using Artificial Neural Networks (ANN). This study e...

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Bibliographic Details
Main Authors: Ivarsson, Anton, Stachowicz, Jacob
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2019
Subjects:
Machine learning
Sleep Arousal
Polysomnography
Automatic Detection
Bachelors Thesis
Big Data
Maskininlärning
Sömnstörningar
Polysomnografi
Automatisk Detektion
Kandidatuppsats
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259996

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259996

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