Pagán Ortiz, JosuéMoya Fernández, José ManuelRisco Martín, José LuisAyala Rodrigo, José Luis2024-01-232024-01-232017Josué Pagán, José M. Moya, José L. Risco-Martín, and José L. Ayala. 2017. Advanced migraine prediction simulation system. In Proceedings of the Summer Simulation Multi-Conference (SummerSim '17). Society for Computer Simulation International, San Diego, CA, USA, Article 24, 1–12.10.5555/3140065.3140089https://hdl.handle.net/20.500.14352/94860In the Internet of Things (IoT) era, there is growing interest in wireless monitoring sensors for detection, classification and prediction of health symptoms. The prediction of symptoms in chronic diseases such as migraines brings new hope to improve patients' lives. The prediction of a migraine symptomatic event through monitoring hemodynamic variables has been previously demonstrated in our earlier work. In this paper, a simulation-based approach for a real-time migraine prediction system is described. The simulation has been implemented using the specifications of the formal description language Discrete EVent Systems (DEVS). The simulation system is a proof of concept that is ready for testing in a real-world ambulatory monitoring environment. The results obtained encourage developing a hardware/software (HW/SW) co-simulation system that incorporates Hardware-in-the-Loop (HIL) components as prior step to the expensive and slow hardware implementation of a complete migraine prediction device. When such a system is used in a real-time setting, it can simulate failures in sensors and trigger alarms for active patient response.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/conference paperhttps://doi.org/10.5555/3140065.3140089restricted accessMigraine predictionFailure detectorRobust systemInteligencia artificial (Informática)1203.04 Inteligencia Artificial1203.26 Simulación