Research regarding stroke indicates that short elapsed time between accident and treatment can be fundamental to allow saving patient's life and avoid future sequels. This paper describes a model for monitoring and rescue victims in situations of possible stroke occurrence. It uses stroke symptoms that can be monitored by mobile equipment, ambient intelligence and artificial neural networks. The model is independent from human operation and applications or third parties devices, therefore adding facilities to increase the quality of life for people with stroke sequel, due to constant monitoring and follow-up provided, allowing the stroke patient to consider a recovery period with greater autonomy. A prototype based on free software platforms was developed, in order to assess the accuracy and the time elapsed between the prototype to detect and to send an alert. The results indicate a positive outlook for the work continuity.