SynthesisClinical autonomic research : official journal of the Clinical Autonomic Research Society2019
Ictal autonomic changes as a tool for seizure detection: a systematic review.
Synthesis in Clinical autonomic research : official journal of the Clinical Autonomic Research Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Heart rate variability as possible marker of brain damage in neonates with hypoxic ischemic encephalopathy: a systematic review.European journal of pediatrics · 2021Pooled it
- Pulse-based photoplethysmography quality assessment improves wearable seizure detection performance.Epilepsia open · 2026Article
- ECG-Based Detection of Epileptic Seizures in Real-World Wearable Settings: Insights from the SeizeIT2 Dataset.Sensors (Basel, Switzerland) · 2025Article
- Early hemodynamic differences between generalized and focal epilepsy measured by photoplethysmography.Scientific reports · 2025Article
- Sudden unexpected death in epilepsy: respiratory vs. cardiac contributions.Cardiovascular research · 2025Review
- Heart Rate Variability as a Tool for Seizure Prediction: A Scoping Review.Journal of clinical medicine · 2024Article
- Multimodal nocturnal seizure detection: Do we need to adapt algorithms for children?Epilepsia open · 2022Article
- Article
- The Prospects of Non-EEG Seizure Detection Devices in Dogs.Frontiers in veterinary science · 2022Review
- Autonomic manifestations of epilepsy: emerging pathways to sudden death?Nature reviews. Neurology · 2021Review
- Identification of Ictal Tachycardia in Focal Motor- and Non-Motor Seizures by Means of a Wearable PPG Sensor.Sensors (Basel, Switzerland) · 2021Article
- Cardiac-based detection of seizures in children with epilepsy.Epilepsy & behavior : E&B · 2021Article
- Article
- The Challenging Path to Developing a Mobile Health Device for Epilepsy: The Current Landscape and Where We Go From Here.Frontiers in neurology · 2021Review
- Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit.Frontiers in neurology · 2021Article
- Owner's Perception of Seizure Detection Devices in Idiopathic Epileptic Dogs.Frontiers in veterinary science · 2021Article
- Noninvasive detection of focal seizures in ambulatory patients.Epilepsia · 2020Review
- A review of epileptic seizure detection using machine learning classifiers.Brain informatics · 2020Review
- Synuclein in red blood cells: a potential biomarker for multiple system atrophy, and other updates on recent autonomic research.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2020Article
- Personalizing Heart Rate-Based Seizure Detection Using Supervised SVM Transfer Learning.Frontiers in neurology · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeAdequate epileptic seizure detection may have the potential to minimize seizure-related complications and improve treatment evaluation. Autonomic changes often precede ictal electroencephalographic discharges and therefore provide a promising tool for timely seizure detection. We reviewed the literature for seizure detection algorithms using autonomic nervous system parameters.
methodsThe PubMed and Embase databases were systematically searched for original human studies that validate an algorithm for automatic seizure detection based on autonomic function alterations. Studies on neonates only and pilot studies without performance data were excluded. Algorithm performance was compared for studies with a similar design (retrospective vs. prospective) reporting both sensitivity and false alarm rate (FAR). Quality assessment was performed using QUADAS-2 and recently reported quality standards on reporting seizure detection algorithms.
resultsTwenty-one out of 638 studies were included in the analysis. Fifteen studies presented a single-modality algorithm based on heart rate variability (n = 10), heart rate (n = 4), or QRS morphology (n = 1), while six studies assessed multimodal algorithms using various combinations of HR, corrected QT interval, oxygen saturation, electrodermal activity, and accelerometry. Most studies had small sample sizes and a short follow-up period. Only two studies performed a prospective validation. A tendency for a lower FAR was found for retrospectively validated algorithms using multimodal autonomic parameters compared to those using single modalities (mean sensitivity per participant 71-100% vs. 64-96%, and mean FAR per participant 0.0-2.4/h vs. 0.7-5.4/h).
conclusionsThe overall quality of studies on seizure detection using autonomic parameters is low. Unimodal autonomic algorithms cannot reach acceptable performance as false alarm rates are still too high. Larger prospective studies are needed to validate multimodal automatic seizure detection.
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