Artificial intelligence-driven closed-loop devices in sudden unexpected death in epilepsy prediction and prevention: Insights from persons with epilepsy and caregivers

Comprehensive Summary

The leading cause of an epilepsy-related mortality is an event called “sudden unexpected death in epilepsy (SUDEP).” Occurring at a rate of 1.2 per 1,000 person years, these events are becoming increasingly common in those who have developed drug-resistant epilepsy. Considering the lethality of SUDEPs, a method for intervention would be key to identify events during or before an occurrence. Ferreira et al. propose an AI-driven closed loop device (AI-CLD) that is attached to the person either dermally or implantation. This device consists of “(1) a continuous seizure detection sensor, (2) a continuous sensor monitoring the SUDEP biomarker, (3) a processor, and (4) an actuator–emergency drug delivery system.” Working in coordination with AI analysis, biomarkers in the interstitial fluid of the wearer would be constantly monitored. When a SUDEP or high-risk seizure is detected, microneedles on the device inject an anti-SUDEP drug. In multiple focus groups, persons with epilepsy and their caregivers conveyed comfortability and a positive attitude towards an AI-based monitoring system.

Outcomes and Implications

The potential of AI-CLDs to revolutionize SUDEP management by improving early risk detection is one that is crucial to epilepsy survivability. Being able to monitor biomarkers constantly will inevitably lead to improvements in care aside from the device itself. By enabling detection of fluctuations in homeostasis over time, this can enable even better clinician-based decisions. In an increasingly AI-infused world, this medical device could be a drastic marker in the use of AI to decrease mortality in a specific condition.