Effects of sampling parameter variation on the complexity analysis of EEG / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 616-620, 2002.
Article
in Chinese
| WPRIM
| ID: wpr-340953
ABSTRACT
The algorithmic complexity and the approximate entropy of EEG were calculated and analyzed with different data points, different sample frequencies and different sample time duration. The results showed that under fixed sample frequency, the longer the data was, the more stable the complexity values were. With fixed sample time duration or fixed data point, lower sample frequency would be better both for EEG distinguishing and for computing time saving.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Signal Processing, Computer-Assisted
/
Rats, Sprague-Dawley
/
Entropy
/
Electroencephalography
/
Methods
Limits:
Animals
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2002
Type:
Article
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