Post-graduate theses
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Current Record: 20 of 1204
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Identifier |
000457827 |
Title |
Automatic obstructive sleep apnea detection |
Alternative Title |
Αυτόματος εντοπισμός υπνικής άπνοιας |
Author
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Μπάντρα, Κωνσταντίνα
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Thesis advisor
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Σάκκαλης, Βαγγέλης
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Abstract |
Over the years, ballistocardiography (BCG) has emerged as a unob-
structive, non-invasive, and safe technique that can be used for cal-
culating the heart rate of a patient. As the heart rate is an essential
element not only for the differential diagnosis process but also for mon-
itoring patients, various scholars have conducted research on possible
applications and use for the BCG signal. Among these, sleep apnea
has gained a lot of interest as it benefits greatly from the unobstructive
nature of the BCG recording. Compared to Polysomnography (PSG),
the golden standard used today, BCG bears the advantage of record-
ing the heart rate and the respiration rate without physically touching
the patient, thus removing the discomfort of the multiple attached
wires and sensors which are needed during the PSG. This is crucial,
as for an accurate diagnosis, multiple hours of recordings have to be
acquired and most of the time the procedure has to be repeated for
more than one night. By removing the discomfort for the patient we
could obtain more accurate results and people would be less hesitant
to undergo the diagnosis procedure. Furthermore, as the BCG sensor
is a very small and portable device, at home monitoring could also be a
possibility. With the present thesis we aim to assess the possibility of
monitoring the heart rate and respiration rate of a patent using solely
a BCG recording. Additionally, the possibility of developing a system
which can utilize the calculated physiological signals and automat-
ically detect Obstructive Sleep Apnea Events during patient’s sleep,
using machine learning and Artificial Intelligence techniques is also
explored hoping that the system will, in the long run, help in reducing
diagnostic ambiguity and also in creating more concise and realizable
results
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Language |
English |
Issue date |
2023-07-28 |
Collection
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School/Department--School of Medicine--Department of Medicine--Post-graduate theses
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Type of Work--Post-graduate theses
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Permanent Link |
https://elocus.lib.uoc.gr//dlib/1/1/e/metadata-dlib-1693646477-437516-11328.tkl
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Views |
413 |