Constant Q–Transform–Based Deep Learning Architecture for Detection of Obstructive Sleep Apnea

Constant Q–Transform–Based Deep Learning Architecture for Detection of Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a long-term sleep disorder that causes temporary disruption in breathing while sleeping. Polysomnography (PSG) is the technique for monitoring different signals during the patient’s sleep cycle, including electroencephalogram (EEG), electromyography (EMG), electrocar...

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Hlavní autoři: Kandukuri Usha Rani, Prakash Allam Jaya, Patro Kiran Kumar, Neelapu Bala Chakravarthy, Tadeusiewicz Ryszard, Pławiak Paweł
Médium: Článek
Jazyk:English
Vydáno: Sciendo 2023-09-01
Edice:International Journal of Applied Mathematics and Computer Science
Témata:
apnea
convolutional neural network
constant q-transform
deep learning
single-lead ecg signals
non-apnea
obstructive sleep apnea
On-line přístup:https://doi.org/10.34768/amcs-2023-0036

Internet

https://doi.org/10.34768/amcs-2023-0036

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