Abstract
This paper investigates the performance of time-frequency based EEG spike detection techniques. The non-stationary nature of EEG makes time-frequency methodology a suitable tool for analysis. The high instantaneous energy of spikes are reflected as very localised energy patterns in the time-frequency domain with reduced time duration toward the high frequency area. These characteristics of spikes in the time-frequency domain makes them recognisable from the background. Two recently published spike detection methods, based on quadratic time-frequency and adaptive time-frequency parameterisation are considered in this investigation. These methods have been applied on both synthetic and real EEG signals. The obtained results show the superior performance of the quadratic time-frequency method for detecting EEG spikes in terms of resolution and robustness to noise.
| Original language | English |
|---|---|
| Title of host publication | 13th European Signal Processing Conference, EUSIPCO 2005 |
| Pages | 297-300 |
| Number of pages | 4 |
| Publication status | Published - 2005 |
| Event | 13th European Signal Processing Conference, EUSIPCO 2005 - Antalya, Turkey Duration: Sep 4 2005 → Sep 8 2005 |
Other
| Other | 13th European Signal Processing Conference, EUSIPCO 2005 |
|---|---|
| Country | Turkey |
| City | Antalya |
| Period | 9/4/05 → 9/8/05 |
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ASJC Scopus subject areas
- Signal Processing
Cite this
Comparative performance of time-frequency based EEG spike detection techniques. / Hassanpour, Hamid; Rankine, Luke; Mesbah, Mostefa; Boashash, Boualem.
13th European Signal Processing Conference, EUSIPCO 2005. 2005. p. 297-300.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Comparative performance of time-frequency based EEG spike detection techniques
AU - Hassanpour, Hamid
AU - Rankine, Luke
AU - Mesbah, Mostefa
AU - Boashash, Boualem
PY - 2005
Y1 - 2005
N2 - This paper investigates the performance of time-frequency based EEG spike detection techniques. The non-stationary nature of EEG makes time-frequency methodology a suitable tool for analysis. The high instantaneous energy of spikes are reflected as very localised energy patterns in the time-frequency domain with reduced time duration toward the high frequency area. These characteristics of spikes in the time-frequency domain makes them recognisable from the background. Two recently published spike detection methods, based on quadratic time-frequency and adaptive time-frequency parameterisation are considered in this investigation. These methods have been applied on both synthetic and real EEG signals. The obtained results show the superior performance of the quadratic time-frequency method for detecting EEG spikes in terms of resolution and robustness to noise.
AB - This paper investigates the performance of time-frequency based EEG spike detection techniques. The non-stationary nature of EEG makes time-frequency methodology a suitable tool for analysis. The high instantaneous energy of spikes are reflected as very localised energy patterns in the time-frequency domain with reduced time duration toward the high frequency area. These characteristics of spikes in the time-frequency domain makes them recognisable from the background. Two recently published spike detection methods, based on quadratic time-frequency and adaptive time-frequency parameterisation are considered in this investigation. These methods have been applied on both synthetic and real EEG signals. The obtained results show the superior performance of the quadratic time-frequency method for detecting EEG spikes in terms of resolution and robustness to noise.
UR - http://www.scopus.com/inward/record.url?scp=84863688056&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863688056&partnerID=8YFLogxK
M3 - Conference contribution
SN - 1604238216
SN - 9781604238211
SP - 297
EP - 300
BT - 13th European Signal Processing Conference, EUSIPCO 2005
ER -