Use Case: Real-Time Brain Activity Monitoring
Industry: Neurological Health / Remote Patient Monitoring
Technology Trend Alignment: Agentic AI (Gartner, 2024)
The Challenge
Patients with epilepsy and seizure-related conditions need earlier, more personalized intervention. Most current monitoring systems are either manual, relying on journals or wearables triggered by the patient, or reactive, detecting events only after they happen. There is no widely available system that learns from individual brain patterns in real time and adapts accordingly. The goal is to create a system that not only monitors but also recognizes deviations from a patient’s unique baseline and initiates a response to validate or anticipate seizure events.
Strategic Vision: Agentic AI Applied to Seizure Monitoring
In Gartner’s 2024 report, Agentic AI was named one of the top strategic trends for 2025. Agentic systems are defined as those that can sense, reason, make decisions, and act autonomously based on changing conditions. Our seizure monitoring solution is being developed with this vision in mind—an intelligent agent that doesn’t just observe but participates in care through personalized, real-time engagement.
Current Development Focus
The system is being built to collect continuous EEG data via a wearable headset, initially to establish a dynamic baseline of each patient’s brain activity. Once the baseline is in place, the system will monitor for deviations in real time. When a meaningful deviation is detected, a conversational AI agent will engage the patient to validate whether a seizure or related symptoms occurred. Over time, the validated data will be used to train AI models capable of identifying individualized seizure onset markers. These markers will eventually support a predictive alert system that can provide early warnings based on the patient’s unique neural patterns.
How Agentic AI Principles Apply
While the system is still under development, it is designed to follow the core principles of Agentic AI. It will sense real-time biometric data, compare it against a personalized baseline, make initial determinations about potential risk, and take action by initiating a conversational check-in. This human-in-the-loop validation process is essential to building a learning model that becomes more accurate over time. In future phases, the AI will identify trends and patterns unique to each user, enabling proactive intervention rather than reactive alerts.
Why It Matters
Gartner forecasts that Agentic AI will handle 15% of enterprise decision-making by 2026. Most healthcare technologies are still reactive and rules-based, missing the opportunity for truly adaptive care. This use case shows how agentic principles can be applied in real-world health monitoring scenarios to enable intelligent, context-aware engagement that evolves with each patient.
Next Steps
The team is focused on completing baseline data collection, refining anomaly detection thresholds, and optimizing the AI-patient validation loop. As labeled data accumulates, model training will begin to identify seizure precursors unique to each user. This will lay the foundation for a future alerting system that can provide advance warnings based on individual biometric signatures.
Reference
Gartner, “Top Strategic Technology Trends for 2025: Agentic AI”
Published October 21, 2024
https://www.gartner.com/doc/reprints?id=1-2J9CSAG9&ct=241104
