An automatic EEG-based sleep staging system with introducing NAoSP and NAoGP as new metrics for sleep staging systems.

ABSTRACT: Different biological signals are recorded in sleep labs during sleep for the diagnosis and treatment of human sleep problems. Classification of sleep stages with electroencephalography (EEG) is preferred to other biological signals due to its advantages such as providing clinical information, cost-effectiveness, comfort, and ease of use. The evaluation of EEG signals taken during sleep by clinicians is a tiring, time-consuming, and error-prone method. Therefore, it is clinically mandatory to determine sleep stages by using software-supported systems. Like all classification problems, the accuracy rate is used to compare the performance of studies in this domain, but this metric can be accurate when the number of observations is equal in classes. However, since there is not an equal number

SUBMITTER: Melek M 

PROVIDER: S-EPMC8131449 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature