Fuzzy inference system wireless body area network architecture simulation for health monitoring

According to WHO, 22% of the world population, about 2 billion people, will be age 60 years and older in 2050. About 80% of these elderly people will be living in the developing nations. Population ageing are faced with challenges such as increased in the cases of chronic non-communicable diseases (NCDs) like cardiovascular diseases, obstructive pulmonary diseases, cancer, diabetes, musculoskeletal problems, and ageing-associated mental health conditions. The current healthcare infrastructure cannot cope with the projected increase in demands for health care monitoring and assistance of elderly people. These challenges must be met with improvements in the current health care systems and infrastructure. A wireless body area network (WBAN) that uses a fuzzy inference system (FIS) which can determine the condition of a person by employing sensors to monitor the heart rate, respiration rate, blood pressure, body temperature, and oxygen saturation of hemoglobin in the blood (SpO2) is proposed in this study. Remote patient monitoring with increased patient to health care personnel ratio can be achieved using this method. The results showed that body condition, ranging from critical to very good condition, can be determined using this method.