Coherence Estimation between EEG signals using Multiple Window Time-Frequency Analysis compared to Gaussian Kernels
(2006) 14th European Signal Processing Conference (EUSIPCO 2006)- Abstract
- It is believed that neural activity evoked by cognitive tasks is spatially correlated in certain frequency bands. The electroencephalogram (EEG) is highly affected by noise of large amplitude which calls for sophisticated time local coherence estimation methods.
In this paper we investigate different approaches to estimate time local coherence between two real valued signals. Our results indicate that the method using two dimensional Gaussian kernels has a slightly better average SNR compared to the multiple window approach. On the other hand, the multiple window approach has a more narrow SNR distribution and seems to perform better in the worst case.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/601330
- author
- Sandberg, Johan LU and Sandsten, Maria LU
- organization
- publishing date
- 2006
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Non-stationary, Time-Frequency-Analysis, EEG, Coherence
- host publication
- 14th European Signal Processing Conference
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 14th European Signal Processing Conference (EUSIPCO 2006)
- conference location
- Florence, Italy
- conference dates
- 2006-09-04 - 2006-09-08
- external identifiers
-
- scopus:84862629486
- language
- English
- LU publication?
- yes
- id
- b978dc31-2248-4429-b1c3-9a6cb31a2fbf (old id 601330)
- alternative location
- http://www.eurasip.org/Proceedings/Eusipco/Eusipco2006/papers/1568981924.pdf
- date added to LUP
- 2016-04-04 11:35:00
- date last changed
- 2022-01-29 22:04:10
@inproceedings{b978dc31-2248-4429-b1c3-9a6cb31a2fbf, abstract = {{It is believed that neural activity evoked by cognitive tasks is spatially correlated in certain frequency bands. The electroencephalogram (EEG) is highly affected by noise of large amplitude which calls for sophisticated time local coherence estimation methods.<br/><br> <br/><br> <br/><br> <br/><br> In this paper we investigate different approaches to estimate time local coherence between two real valued signals. Our results indicate that the method using two dimensional Gaussian kernels has a slightly better average SNR compared to the multiple window approach. On the other hand, the multiple window approach has a more narrow SNR distribution and seems to perform better in the worst case.}}, author = {{Sandberg, Johan and Sandsten, Maria}}, booktitle = {{14th European Signal Processing Conference}}, keywords = {{Non-stationary; Time-Frequency-Analysis; EEG; Coherence}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Coherence Estimation between EEG signals using Multiple Window Time-Frequency Analysis compared to Gaussian Kernels}}, url = {{http://www.eurasip.org/Proceedings/Eusipco/Eusipco2006/papers/1568981924.pdf}}, year = {{2006}}, }