Name
Abstract | ||
|---|---|---|
In an effort to detect pain in an objective way, Electrocorticography (ECoC) signals were acquired from male Sprague-Dawley rats in response to thermally induced pain. A wearable, wireless multichannel system was utilized to acquire signals from freely-behaving animals during the experiments. ECoC signals were recorded before (baseline) and during the heat exposure for which animals withdrew their paws in response to the painful feeling. Analysis of the signals revealed a clear, high-amplitude peak at the moment of the paw withdrawal across all four recording channels in each test. Analysis in the frequency domain found the peaks coincided with an abrupt increase of delta rhythms (under 4 Hz). In the baseline, heating, and post-withdrawal segments, these rhythms were relatively low, indicating that the sharp increase in delta activity might be associated with pain. Theta, alpha, beta, and gamma rhythms were also measured, but no significant differences were found between each phase of the signals. These preliminary results are promising; however, more animal models will need to be tested to provide statistically significant results with high confidence. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/EMBC.2012.6346480 | 2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Keywords | Field | DocType |
data acquisition,frequency domain analysis,electroencephalography | Alpha (ethology),Computer vision,Electrocorticography,Psychology,Artificial intelligence,Audiology,Electrical engineering,Rhythm,Electroencephalography | Conference |
Volume | ISSN | Citations |
2012 | 1557-170X | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aydin Farajidavar | 1 | 1 | 2.08 |
| Shariq M Athar | 2 | 0 | 0.34 |
| Christopher E Hagains | 3 | 0 | 0.34 |
| Yuan B Peng | 4 | 0 | 0.34 |
| Jung-Chih Chiao | 5 | 16 | 4.99 |