Article Figures & Data
Tables
- Table 1.
Potential measurements discussed at the Ei2 workshop that could enhance a seizure-forecasting algorithm
• Mood* • Stress* • Compliance • Cortisol • Fatigue* • Illness* • Orexin • Irritability* • Food/alcohol intake • Patient self-prediction* • Sex hormones • Orientation (cognitive) • Electrical dermal activity • pH (brain) • Gait • Heart rate • Time of day* • Finer movements • Temperature/weather • Antiepileptic drug levels • Ketones • Respiration • Blood oxygen • Speech • Sleep cycle changes (sleep/wake staging) • Inflammatory markers • Body Temperature • Sleep quality • Glucose • External environment These measurements could be collected in numerous ways. An asterisk indicates those that could be captured by patient diary, others could be measured through smartphone, biosensors, or through sweat collection.
In this issue
Seizure Forecasting from Idea to Reality. Outcomes of the My Seizure Gauge Epilepsy Innovation Institute Workshop
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- Article
- Abstract
- Significance Statement
- Introduction
- Seizures Have Multi-Temporal Patterns on Ultradian, Circadian, and Multi-Day Time Scales
- Multimodal Analysis of Seizure Events Coupling EEG with Non-EEG Measures May Enhance Seizure-Forecasting Algorithms
- Individualization and Personalization of a Seizure-Forecasting Algorithm Is Necessary
- Next Steps
- Acknowledgments
- Footnotes
- References
- Figures & Data
- Info & Metrics
- eLetters