مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Information Journal Paper

Title

Deep neural network method for classification of sleep stages using spectrogram of signal based on transfer learning with different domain data

Pages

  1898-1903

Abstract

 classification of sleep stages is an efficient way of diagnosing sleep problems based on processing the bio-signals (ECG, EEG, EOG, and PPG). The less complex this signal is, the better the detection and processing will be. Feature extraction methods that are done manually are tedious and time-consuming. On the contrary, those features with no hand intervention are called deep features that are usually extracted from images. Analysis of the time-frequency characteristics of non-static bio-signals is of importance since it can provide useful information. The current study aimed to extract the time-frequency image using ECG signal spectrogram as well as the deep features using the convolutional neural network. After extracting the deep features, sleep stages were classified based on deep transfer learning method. Network training was then performed using one of the ECG signals, and testing was done considering the other ECG signal channel. According to the findings, it is possible to detect sleep stages with acceptable accuracy and different amplitudes of signals. Finally, the accuracy and sensitivity values of the sleep stages were measured as 98. 92% and 96. 52%, respectively.

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    APA: Copy

    Moradi, M.M., FATEHI, M.H., MASOUMI, H., & TAGHIZADEH, M.. (2022). Deep neural network method for classification of sleep stages using spectrogram of signal based on transfer learning with different domain data. SCIENTIA IRANICA, 29(4 (Transactions D: Computer Science and Engineering and Electrical Engineering)), 1898-1903. SID. https://sid.ir/paper/1051780/en

    Vancouver: Copy

    Moradi M.M., FATEHI M.H., MASOUMI H., TAGHIZADEH M.. Deep neural network method for classification of sleep stages using spectrogram of signal based on transfer learning with different domain data. SCIENTIA IRANICA[Internet]. 2022;29(4 (Transactions D: Computer Science and Engineering and Electrical Engineering)):1898-1903. Available from: https://sid.ir/paper/1051780/en

    IEEE: Copy

    M.M. Moradi, M.H. FATEHI, H. MASOUMI, and M. TAGHIZADEH, “Deep neural network method for classification of sleep stages using spectrogram of signal based on transfer learning with different domain data,” SCIENTIA IRANICA, vol. 29, no. 4 (Transactions D: Computer Science and Engineering and Electrical Engineering), pp. 1898–1903, 2022, [Online]. Available: https://sid.ir/paper/1051780/en

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