Stroke is one of the fatal diseases that affect the brain and causes death within 3 to 10 h. However, most of the deaths caused by a stroke can be avoided with the identification of the nature of stroke and react to it in a timely manner by intelligent health systems. The state-of-the-art cyber-physical systems (CPS) enable interaction between physical and computational world to identify any anomaly in the physical world and respond to it. The response of CPS may vary depending upon the context of the physical world. Extensive research has been done in this area from the perspective of wireless sensor networks, body area networks, and wearable smart devices. This paper proposes a CPS for detecting the occurrence of stroke in patients, who have a high risk of stroke or have survived a stroke before. The developed CPS sends recorded data to the doctor and alerts him when the stroke occurs. The proposed system is operating on data acquired from electroencephalography sensors from patients’ brain. This article aimed at decreasing human mortality rate due to stroke and will bridge the gaps in CPS due to interdisciplinary isolation. The disciplines involved in the development of a CPS include communication networks, pattern recognition, software engineering, mathematics, and biomedical.