↓ Skip to main content

Automatic Computer-Based Detection of Epileptic Seizures

Overview of attention for article published in Frontiers in Neurology, August 2018
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
110 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Automatic Computer-Based Detection of Epileptic Seizures
Published in
Frontiers in Neurology, August 2018
DOI 10.3389/fneur.2018.00639
Pubmed ID
Authors

Christoph Baumgartner, Johannes P. Koren, Michaela Rothmayer

Abstract

Automatic computer-based seizure detection and warning devices are important for objective seizure documentation, for SUDEP prevention, to avoid seizure related injuries and social embarrassments as a consequence of seizures, and to develop on demand epilepsy therapies. Automatic seizure detection systems can be based on direct analysis of epileptiform discharges on scalp-EEG or intracranial EEG, on the detection of motor manifestations of epileptic seizures using surface electromyography (sEMG), accelerometry (ACM), video detection systems and mattress sensors and finally on the assessment of changes of physiologic parameters accompanying epileptic seizures measured by electrocardiography (ECG), respiratory monitors, pulse oximetry, surface temperature sensors, and electrodermal activity. Here we review automatic seizure detection based on scalp-EEG, ECG, and sEMG. Different seizure types affect preferentially different measurement parameters. While EEG changes accompany all types of seizures, sEMG and ACM are suitable mainly for detection of seizures with major motor manifestations. Therefore, seizure detection can be optimized by multimodal systems combining several measurement parameters. While most systems provide sensitivities over 70%, specificity expressed as false alarm rates still needs to be improved. Patients' acceptance and comfort of a specific device are of critical importance for its long-term application in a meaningful clinical way.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 110 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 18%
Student > Ph. D. Student 16 15%
Student > Master 12 11%
Student > Bachelor 8 7%
Student > Doctoral Student 7 6%
Other 16 15%
Unknown 31 28%
Readers by discipline Count As %
Engineering 19 17%
Neuroscience 18 16%
Medicine and Dentistry 15 14%
Computer Science 11 10%
Physics and Astronomy 2 2%
Other 9 8%
Unknown 36 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 August 2018.
All research outputs
#21,709,675
of 24,226,848 outputs
Outputs from Frontiers in Neurology
#9,822
of 13,253 outputs
Outputs of similar age
#292,960
of 335,222 outputs
Outputs of similar age from Frontiers in Neurology
#238
of 309 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,253 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 335,222 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 309 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.