Name
Title | ||
|---|---|---|
Multiple sensor integration for seizure onset detection in human patients comparing conventional disc versus novel tripolar concentric ring electrodes. |
Abstract | ||
|---|---|---|
As epilepsy affects approximately one percent of the world population, electrical stimulation of the brain has recently shown potential for additive seizure control therapy. Closed-loop systems that apply electrical stimulation when seizure onset is automatically detected require high accuracy of automatic seizure detection based on electrographic brain activity. To improve this accuracy we propose to use noninvasive tripolar concentric ring electrodes that have been shown to have significantly better signal-to-noise ratio, spatial selectivity, and mutual information compared to conventional disc electrodes. The proposed detection methodology is based on integration of multiple sensors using exponentially embedded family (EEF). In this preliminary study it is validated on over 26.3 hours of data collected using both tripolar concentric ring and conventional disc electrodes concurrently each from 7 human patients with epilepsy including five seizures. For a cross-validation based group model EEF correctly detected 100% and 80% of seizures respectively with <0.76 and <1.56 false positive detections per hour respectively for the two electrode modalities. These results clearly suggest the potential of seizure onset detection based on data from tripolar concentric ring electrodes. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/EMBC.2013.6609426 | EMBC |
Keywords | Field | DocType |
time 26.3 hour,medical disorders,bioelectric potentials,medical signal detection,brain electrical stimulation,seizure onset detection,seizure control therapy,noise,electrographic brain activity,biomedical electrodes,exponentially embedded family,human patient,epilepsy,electroencephalography,medical signal processing,disc electrode,tripolar concentric ring electrode,closed-loop system,eef group model,multiple sensor integration,sensors,data collection,signal-to-noise ratio,electrodes,band pass filters,sensitivity,signal to noise ratio | Biomedical engineering,Seizure detection,Concentric,Computer science,Electronic engineering,Epilepsy,Electrical brain stimulation,Multiple sensors,Electroencephalography,Electrode | Conference |
Volume | ISSN | Citations |
2013 | 1557-170X | 0 |
PageRank | References | Authors |
0.34 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Oleksandr Makeyev | 1 | 125 | 17.48 |
| Quan Ding | 2 | 59 | 7.72 |
| Iris E Martínez-Juárez | 3 | 0 | 0.34 |
| John Gaitanis | 4 | 0 | 0.34 |
| S. Kay | 5 | 309 | 40.73 |
| Walter G Besio | 6 | 5 | 3.41 |