ArticleScientific reports2017
Validation of a smartphone-based EEG among people with epilepsy: A prospective study.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 citations in OpenAlex.
- Noninvasive mobile EEG as a tool for seizure monitoring and management: A systematic review.Epilepsia · 2022Pooled it
- Smartphone Apps in the Context of Tinnitus: Systematic Review.Sensors (Basel, Switzerland) · 2020Pooled it
- Single-channel EEG-based seizure prediction using deep learning.Scientific reports · 2026Article
- Enhancing mobile EEG: Software development and performance insights of the DreamMachine.HardwareX · 2025Article
- Low-Cost Strategies for the Development of Neurocritical Care in Resource-Limited Settings.Neurocritical care · 2025Review
- Assistive Artificial Intelligence in Epilepsy and Its Impact on Epilepsy Care in Low- and Middle-Income Countries.Brain sciences · 2025Review
- Open access EEG dataset of repeated measurements from a single subject for microstate analysis.Scientific data · 2024Article
- Remote collection of electrophysiological data with brain wearables: opportunities and challenges.Bioelectronic medicine · 2023Review
- The Power of ECG in Semi-Automated Seizure Detection in Addition to Two-Channel behind-the-Ear EEG.Bioengineering (Basel, Switzerland) · 2023Article
- Epilepsy diagnosis using a clinical decision tool and artificially intelligent electroencephalography.Epilepsy & behavior : E&B · 2023Article
- Application of a Low-Cost mHealth Solution for the Remote Monitoring of Patients With Epilepsy: Algorithm Development and Validation.JMIR neurotechnology · 2023Article
- Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer.Sensors (Basel, Switzerland) · 2021Article
- Patterns and Perceptions of Smartphone Use Among Academic Neurologists in the United States: Questionnaire Survey.JMIR mHealth and uHealth · 2020Article
- Tablet-based electroencephalography diagnostics for patients with epilepsy in the West African Republic of Guinea.European journal of neurology · 2020Article
- Biosensors for Personal Mobile Health: A System Architecture Perspective.Advanced materials technologies · 2020Article
- Comparison of mobile and clinical EEG sensors through resting state simultaneous data collection.PeerJ · 2020Article
- Article
- A deep learning approach for real-time detection of sleep spindles.Journal of neural engineering · 2019Article
- Managing Epilepsy by Telemedicine in Resource-Poor Settings.Frontiers in public health · 2019Article
- Teleneurology and mobile technologies: the future of neurological care.Nature reviews. Neurology · 2018Review
Corrections and comments
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Authors and funding
23 authors at 9 institutions in 3 countries.
Funding
Abstract
Our objective was to assess the ability of a smartphone-based electroencephalography (EEG) application, the Smartphone Brain Scanner-2 (SBS2), to detect epileptiform abnormalities compared to standard clinical EEG. The SBS2 system consists of an Android tablet wirelessly connected to a 14-electrode EasyCap headset (cost ~ 300 USD). SBS2 and standard EEG were performed in people with suspected epilepsy in Bhutan (2014-2015), and recordings were interpreted by neurologists. Among 205 participants (54% female, median age 24 years), epileptiform discharges were detected on 14% of SBS2 and 25% of standard EEGs. The SBS2 had 39.2% sensitivity (95% confidence interval (CI) 25.8%, 53.9%) and 94.8% specificity (95% CI 90.0%, 97.7%) for epileptiform discharges with positive and negative predictive values of 0.71 (95% CI 0.51, 0.87) and 0.82 (95% CI 0.76, 0.89) respectively. 31% of focal and 82% of generalized abnormalities were identified on SBS2 recordings. Cohen's kappa (κ) for the SBS2 EEG and standard EEG for the epileptiform versus non-epileptiform outcome was κ = 0.40 (95% CI 0.25, 0.55). No safety or tolerability concerns were reported. Despite limitations in sensitivity, the SBS2 may become a viable supportive test for the capture of epileptiform abnormalities, and extend EEG access to new, especially resource-limited, populations at a reduced cost.
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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.