Summary of Sleep Staging From Airflow Signals Using Fourier Approximations Of Persistence Curves, by Shashank Manjunath et al.
Sleep Staging from Airflow Signals Using Fourier Approximations of Persistence Curves
by Shashank Manjunath, Hau-Tieng Wu, Aarti Sathyanarayana
First submitted to arxiv on: 12 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The abstract presents an AI-based approach for automating sleep staging using airflow signals, which can replace traditional electroencephalogram (EEG) based manual analysis. The proposed method, Fourier approximations of persistence curves (FAPC), builds upon previous work in topological data analysis (TDA) and Hermite function expansions of persistence curves (HEPC). FAPC is shown to provide complementary information to HEPC, resulting in a 4.9% performance increase over baseline methods when evaluated on pediatric sleep studies from the Nationwide Children’s Hospital Sleep DataBank (NCHSDB). |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Sleep researchers have developed an innovative way to automatically identify different stages of sleep using airflow signals instead of traditional brain wave recordings. This new method, called Fourier approximations of persistence curves, helps computers better understand these signals and improve their accuracy in classifying sleep stages. |
