| Title |
EEG-Based Automatic Classification of ‘Awake’ versus ‘Anesthetized’ State in General Anesthesia Using Granger Causality
|
|---|---|
| Published in |
PLOS ONE, March 2012
|
| DOI | 10.1371/journal.pone.0033869 |
| Pubmed ID | |
| Authors |
Nicoletta Nicolaou, Saverios Hourris, Pandelitsa Alexandrou, Julius Georgiou |
| Abstract |
General anesthesia is a reversible state of unconsciousness and depression of reflexes to afferent stimuli induced by administration of a "cocktail" of chemical agents. The multi-component nature of general anesthesia complicates the identification of the precise mechanisms by which anesthetics disrupt consciousness. Devices that monitor the depth of anesthesia are an important aide for the anesthetist. This paper investigates the use of effective connectivity measures from human electrical brain activity as a means of discriminating between 'awake' and 'anesthetized' state during induction and recovery of consciousness under general anesthesia. |
Mendeley readers
The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| Portugal | 1 | <1% |
| France | 1 | <1% |
| Belarus | 1 | <1% |
| Unknown | 127 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 18% |
| Researcher | 24 | 18% |
| Student > Master | 18 | 14% |
| Student > Doctoral Student | 11 | 8% |
| Student > Bachelor | 9 | 7% |
| Other | 23 | 17% |
| Unknown | 24 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 21 | 16% |
| Medicine and Dentistry | 20 | 15% |
| Engineering | 17 | 13% |
| Agricultural and Biological Sciences | 12 | 9% |
| Computer Science | 9 | 7% |
| Other | 23 | 17% |
| Unknown | 31 | 23% |