A genetic approach for personalized healthcare

Remote Health monitoring involves continuous monitoring of vital signs and transmission of alert signals to the physician when vital sign values fluctuate above or below the threshold. Existing healthcare systems obtain the vital data of a patient periodically and require the intervention of a doctor to detect the severity of abnormality which is time consuming. Hence, there is a need for an intelligent, personalized and efficient healthcare system to detect the abnormality. In a multipatient environment when several patients have abnormalities, existing scheduling schemes do not consider the degree of severity in order to schedule the most critical patient who has to be served first. To overcome these issues, this paper proposes a Genetic Algorithm (GA) based Personalized Healthcare System (GAPHS). This system represents the abnormality levels of the vital parameters of the patient as a chromosome and determines the Severity Index of the chromosome to identify the severity. The proposed system outperforms in terms of speed and accuracy when compared to traditional GA in dynamic scenarios.