Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 0 0 2026 06 12 1185 1185 Hamideza Jalali Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran majid pouladian Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran Ali Motie Nasrabadi Biomedical Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran Azin Movahed Music Department, School of Performing Arts and Music, College of Fine Arts, University of Tehran, Tehran, Iran 2024 12 31 2025 02 15 Purpose: Automatic classification of sleep stages is one of the fundamental factors in diagnosing sleep disorders to prevent and treat various diseases, and it can significantly aid in saving specialists' time and energy. In this study, a novel method for mapping electroencephalogram (EEG) signals to music for sleep stage classification is proposed. Materials and Methods: A total of 15.233, 30-second data segments from the Sleep-EDF database were used as the statistical population for this evaluation. Initially, single-channel EEG data are mapped to musical pieces using a long short-term memory (LSTM) network structure. Subsequently, seven features are extracted from the generated music sequences and applied to classification structures. Results: The overall classification accuracy for the five sleep stages according to the AASM standard is 85.3% for the Sleep-EDF database. Another objective of this study is to present a novel single-channel EEG sonification method, achieving classification accuracy that is either higher than or comparable to contemporary methods.  Conclusion: The results of this study show that this audio signal mapping contains effective information for sleep stage classification and the proposed method performs well compared to new methods without the need for complex classifier structures. https://fbt.tums.ac.ir/index.php/fbt/article/view/1185 https://fbt.tums.ac.ir/index.php/fbt/article/download/1185/566