Topological classifier for detecting the emergence of epileptic seizures
| Title: | Topological classifier for detecting the emergence of epileptic seizures |
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| Authors: | Piangerelli, Marco, Rucco, Matteo, Merelli, Emanuela |
| Source: | BMC Res Notes 11, 392, 2018 |
| Publication Year: | 2016 |
| Collection: | Computer Science Mathematics Quantitative Biology |
| Subject Terms: | Quantitative Biology - Neurons and Cognition, Computer Science - Information Theory, I.5.2 |
| More Details: | In this work we study how to apply topological data analysis to create a method suitable to classify EEGs of patients affected by epilepsy. The topological space constructed from the collection of EEGs signals is analyzed by Persistent Entropy acting as a global topological feature for discriminating between healthy and epileptic signals. The Physionet data-set has been used for testing the classifier. Comment: Open data: Physionet data-set |
| Document Type: | Working Paper |
| DOI: | 10.1186/s13104-018-3482-7 |
| Access URL: | http://arxiv.org/abs/1611.04872 |
| Accession Number: | edsarx.1611.04872 |
| Database: | arXiv |
| DOI: | 10.1186/s13104-018-3482-7 |
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