ReviewCurrent neurology and neuroscience reports2018
Seizure detection: do current devices work? And when can they be useful?
Review in Current neurology and neuroscience reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Deep learning-based detection of generalized convulsive seizures using a wrist-worn accelerometer.Epilepsia · 2025Article
- SeizFt: Interpretable Machine Learning for Seizure Detection Using Wearables.Bioengineering (Basel, Switzerland) · 2023Article
- The Prospects of Non-EEG Seizure Detection Devices in Dogs.Frontiers in veterinary science · 2022Review
- Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit.Frontiers in neurology · 2021Article
- Let's talk SUDEP.Noro psikiyatri arsivi · 2019Review
- Biosensors for Epilepsy Management: State-of-Art and Future Aspects.Sensors (Basel, Switzerland) · 2019Review
- Risk Factors for Sudden Unexpected Death in Epilepsy (SUDEP) and Their Mitigation.Current treatment options in neurology · 2019Review
- Classification of Scalp EEG States Prior to Clinical Seizure Onset.IEEE journal of translational engineering in health and medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
purpose of reviewThe unpredictability and apparent randomness of epileptic seizures is one of the most vexing aspects of epilepsy. Methods or devices capable of detecting seizures may help prevent injury or even death and significantly improve quality of life. Here, we summarize and evaluate currently available, unimodal, or polymodal detection systems for epileptic seizures, mainly in the ambulatory setting. RECENT
findingsThere are two broad categories of detection devices: EEG-based and non-EEG-based systems. Wireless wearable EEG devices are now available both in research and commercial arenas. Neuro-stimulation devices are currently evolving and initial experiences of these show potential promise. As for non-EEG devices, different detecting systems show different sensitivity according to the different patient and seizure types. Regardless, when used in combination, these modalities may complement each other to increase positive predictive value. Although some devices with high sensitivity are promising, practical widespread use of such detection systems is still some way away. More research and experience are needed to evaluate the most efficient and integrated systems, to allow for better approaches to detection and prediction of seizures. The concept of closed-loop systems and prompt intervention may substantially improve quality of life for patients and carers.
Indexed as
Identifiers
29796939What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.