Abstract

Information communication technology in IT field is being united with technologies in many other fields. Even the medical field was united with IT technology, thereby having allowed new technology called Ubiquitous Health System to appear. As the U-health system, which is being served now, is in the early stage, it relies upon sensor equipment of checking patient's condition, and is using a coping method, by which family and medical institution directly analyze the measured data from sensor. This method has a demerit as saying that family and medical institution cannot cope correctly and promptly given the occurrence of malfunction and emergency situation on sensor equipment. Accordingly, the purpose of this study is to supplement demerit of the U-health system. It enhances reliability in order to possibly diagnose patient's condition and judge abnormal sign or emergency situation by applying the disease-identification algorithm to the existing U-health system. Also, the aim is to play a role of notice by sending text message to family and medical institution when a result of identifying disease is judged to be emergency situation, and is to enhance speed by allowing patient's condition to be possibly confirmed with real time by using smart phone. The system, which is proposed in this study, obtains the incidence of emergency situation by using DCAP(Disease Combination Appearance Probability) prediction algorithm, which is statistical method after creating the extracted data from the body into the combined message in a new form while allowing patient to wear several sensors based on USN(Ubiquitous Sensor Network). Also, it makes it available for coping promptly by giving notice of emergency situation to family and medical institution through sending text message given the occurrence of emergency situation, and enhances speed by offering mobile service so that patient's information can be searched, through using smart phone available for wireless network.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call