Wearable Health Care Ubiquitous System for Stroke Monitoring and Alert

Abstract

Research regarding stroke indicates that ensuring a 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 rescuing 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 of human operation and applications or third party 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, to assess the accuracy and the time elapsed between the prototype to detect and to send an alert. The results indicate a positive outcome for the work continuity.