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Attention Score in Context
| Title |
Distinguishing Anesthetized from Awake State in Patients: A New Approach Using One Second Segments of Raw EEG
|
|---|---|
| Published in |
Frontiers in Human Neuroscience, February 2018
|
| DOI | 10.3389/fnhum.2018.00040 |
| Pubmed ID | |
| Authors |
Bjørn E. Juel, Luis Romundstad, Frode Kolstad, Johan F. Storm, Pål G. Larsson |
| Abstract |
Objective: The objective of this study was to test whether properties of 1-s segments of spontaneous scalp EEG activity can be used to automatically distinguish the awake state from the anesthetized state in patients undergoing general propofol anesthesia. Methods: Twenty five channel EEG was recorded from 10 patients undergoing general intravenous propofol anesthesia with remifentanil during anterior cervical discectomy and fusion. From this, we extracted properties of the EEG by applying the Directed Transfer Function (DTF) directly to every 1-s segment of the raw EEG signal. The extracted properties were used to develop a data-driven classification algorithm to categorize patients as "anesthetized" or "awake" for every 1-s segment of raw EEG. Results: The properties of the EEG signal were significantly different in the awake and anesthetized states for at least 8 of the 25 channels (p < 0.05, Bonferroni corrected Wilcoxon rank-sum tests). Using these differences, our algorithms achieved classification accuracies of 95.9%. Conclusion: Properties of the DTF calculated from 1-s segments of raw EEG can be used to reliably classify whether the patients undergoing general anesthesia with propofol and remifentanil were awake or anesthetized. Significance: This method may be useful for developing automatic real-time monitors of anesthesia. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 17% |
| Australia | 1 | 17% |
| Italy | 1 | 17% |
| United States | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 1 | 17% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 65 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 18% |
| Student > Ph. D. Student | 10 | 15% |
| Student > Bachelor | 5 | 8% |
| Student > Postgraduate | 5 | 8% |
| Student > Master | 4 | 6% |
| Other | 8 | 12% |
| Unknown | 21 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 14% |
| Computer Science | 9 | 14% |
| Neuroscience | 5 | 8% |
| Agricultural and Biological Sciences | 4 | 6% |
| Engineering | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 28 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 February 2018.
All research outputs
#7,444,293
of 23,018,998 outputs
Outputs from Frontiers in Human Neuroscience
#3,197
of 7,192 outputs
Outputs of similar age
#130,464
of 331,045 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#70
of 147 outputs
Altmetric has tracked 23,018,998 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,192 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,045 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 147 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.