Published in:
01-06-2017 | Original Article
Entire Frequency Domain Analysis of Rodent EEG and EMG Recordings Using Relative Thresholds
Published in: Sleep and Vigilance | Issue 1/2017
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Aim
The aim of this work was to develop a simple computer-based sleep-scoring algorithm to detect the three vigilance states—rapid eye movement (REM) sleep, non-REM (NREM) sleep, and wakefulness—using the entire frequency domain with relative thresholds.
Methods
A variety of frequencies and time-domain features were extracted from each 4-s epoch in retrospective 24-h sleep data sets from mice using an algorithm developed in Matlab version 7.0. This algorithm is composed of five steps: (1) determining the EMG–power ratio, (2) determining the three energy areas (high, middle, and low) using EMG–power ratio thresholds (e.g., 5.5 and 6), (3) determining the θ/δ ratio, (4) distinguishing wakefulness from NREM sleep using the θ/δ ratio in the middle-energy area, and (5) distinguishing REM from NREM sleep using the θ/δ ratio in the low-energy area.
Results
We were able to achieve a high degree (92%) of agreement between the results of this algorithm and the results of a waveform-recognition procedure.
Conclusion
This algorithm should overcome the inconsistencies inherent in manual scoring and reduce the time required for expert analysis. This algorithm is a reliable and efficient tool for automated detection of the three vigilance states.