Name
Abstract | ||
|---|---|---|
Event-related potentials (ERP) are brain electrophysiological patterns created by averaging electroencephalographic (EEG) data, time-locking to events of interest (e.g., stimulus or response onset). In this paper, we propose a semi-automatic framework for mining ERP data, which includes the following steps: PCA decomposition, extraction of summary metrics, unsupervised learning (clustering) of patterns, and supervised learning, i.e. discovery, of classification rules. Results show good correspondence between rules that emerge from decision tree classifiers and rules that were independently derived by domain experts. In addition, data mining results suggested ways in which expert- defined rules might be refined to improve pattern representation and classification results. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/AINAW.2007.55 | AINA Workshops (1) |
Keywords | Field | DocType |
brain electrophysiological pattern,pca decomposition,supervised learning,event-related potential,summary metrics extraction,pattern clustering,mining erp patterns,bioelectric potentials,semi-automatic framework,electroencephalographic data,electroencephalography,classification result,pattern classification,decision tree classifier,medical signal processing,brain electrophysiological pattern mining,classification rule,data mining result,semiautomatic framework,rule discovery,data mining,erp data,eeg,principal component analysis,decision trees,unsupervised learning,magnetic resonance imaging,event related potential,hemodynamics | Decision tree,Computer science,Event-related potential,Supervised learning,Unsupervised learning,Artificial intelligence,Cluster analysis,Electroencephalography,Decision tree learning,Machine learning,Principal component analysis | Conference |
Volume | ISBN | Citations |
1 | 978-0-7695-2847-2 | 4 |
PageRank | References | Authors |
0.77 | 1 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiawei Rong | 1 | 51 | 5.54 |
| Dejing Dou | 2 | 892 | 90.86 |
| Gwen Frishkoff | 3 | 34 | 2.72 |
| Robert M. Frank | 4 | 17 | 2.77 |
| Allen Malony | 5 | 94 | 8.29 |
| Don Tucker | 6 | 40 | 3.48 |