The potential value of three-dimensional accelerometry for detection of motor seizures in severe epilepsy
Abstract
Seizure detection results based on the visual analysis of three-dimensional (3D) accelerometry (ACM) and video/EEG recordings are reported for 18 patients with severe epilepsy. They were monitored for 36 hours during which 897 seizures were detected. This was seven times higher than the number of seizures reported by nurses during the registration period. The results in this article demonstrate that 3D ACM is a valuable sensing method for seizure detection in this population. Four hundred twenty-eight (48%) seizures were detected by ACM. With 3D ACM alone it was possible to detect all the seizures in 10 of the 18 patients. Three-dimensional ACM also was complementary to EEG in our population. ACM patterns during seizures were stereotypical in 95% of the motor seizures. These characteristic patterns are a starting point for automated seizure detection.
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In epilepsy, wearables are used to detect and differentiate seizures in hospital settings.
“In epilepsy, wearables are used to detect and differentiate seizures in hospital settings.”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [14]
In epilepsy, stereotypical movement patterns for motor seizures were detected with three-axes accelerometers in 95% of motor seizures identified with video-EEG.
“In epilepsy, stereotypical movement patterns for motor seizures were detected with three-axes accelerometers in 95% of the motor seizures identified with video-EEG [14].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [14]
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- Authors
- Nijsen, T. M. E., Arends, J. B. A. M., Griep, P. A. M., & Cluitmans, P. J. M.
- Affiliations
- Kempenhaeghe (NL)
- Corresponding author
- Nijsen, Tamara M.E.
- ORCID
- Arends, Johan B.A.M.
- Venue
- Epilepsy & Behavior
- Publisher
- Elsevier BV
- Published
- 2005-08
- Volume
- 7
- Issue
- 1
- Pages
- 74-84
- ISSN
- 1525-5050 (ISSN-L)
- OpenAlex
- W2126448734
- Cited by
- 139
- References
- 19
- Citations by year
- 2026: 2 · 2025: 3 · 2023: 4 · 2022: 8 · 2021: 11 · 2020: 7 · 2019: 6 · 2018: 17 · 2017: 10 · 2016: 14 · 2015: 9 · 2014: 3 · 2013: 9 · 2012: 7
- FWCI
- 1.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Epilepsy & Behavior (publishedVersion)
- PubMed (publishedVersion)
- TU/e Research Portal (publishedVersion)
- TU/e Research Portal (submittedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Epilepsy research and treatment
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- motor seizures, seizure detection, severe epilepsy, wearable sensors, automated seizure detection, video-EEG monitoring
- MeSH terms
- Adult, Diagnosis, Computer-Assisted, Diagnosis, Differential, Electroencephalography, Epilepsy, Female, Humans, Male, Middle Aged, Monitoring, Physiologic, Movement, Predictive Value of Tests, Prospective Studies, Seizures, Videotape Recording
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