Main Article Content
Biological signals that occur during sleep are recorded and classified by specialists. This process is called sleep staging. However, this is a very long and laborious process. Therefore, automatic sleep staging systems are needed. Nevertheless, automatic sleep staging studies to date have not provided satisfactory performance. The main reasons for this are inter-channel interference, electrode disconnection, and noise. In this paper, a new method (eye method) based on the Euclidean distance measurement method has been developed to solve the electrode disconnection or non-contact problem. This method was applied to three different datasets and detected all electrode disconnections with 100% accuracy. Thanks to this advanced method are aimed to increase the success of automatic sleep staging systems to be designed in the future.
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