An energy-efficient dual-branch spiking neural network for epileptic seizure detection from electroencephalogram signals

Key Points

• Epileptic seizures were effectively detected using an energy-efficient dual-branch spiking neural network.
• The model achieved a detection accuracy of over 90%, significantly enhancing traditional EEG signal analysis.
• Analysis involved real-time processing of electroencephalogram signals across diverse patient cohorts.
• Future applications may improve seizure management framework, but clinical trials are necessary to validate results.