Papers › Retrieving Filter Spectra in CNN for Explainable Sleep Stage Classification
Retrieving Filter Spectra in CNN for Explainable Sleep Stage Classification
Stephan Goerttler, Yucheng Wang, Emadeldeen Eldele, Fei He, Min Wu
Despite significant advances in deep learning-based sleep stage classification, the clinical adoption of automatic classification models remains slow. One key challenge is the lack of explainability, as many models function as black boxes with millions of parameters. In response, recent work has increasingly focussed on enhancing model explainability. This study contributes to these efforts by globally explaining spectral processing of individual EEG channels. Specifically, we introduce a method to retrieve the filter spectrum of low-level convolutional feature extraction and compare it with the classification-relevant spectral information in the data. We evaluate our approach on the MSA-CNN model using the ISRUC-S3 and Sleep-EDF-20 datasets. Our findings show that spectral processing plays a significant role in the lower frequency bands. In addition, comparing the correlation between filter spectrum and data-based spectral information with univariate performance indicates that the model naturally prioritises the most informative channels in a multimodal setting. We specify how these insights can be leveraged to enhance model performance. The code for the filter spectrum retrieval and its analysis is available at https://github.com/sgoerttler/MSA-CNN.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections