A study on algorithm to identify the abnormal status of a patient using acceleration algorithm - Kim, Yougn-Hyuk; Lim, Il-Kwon; Lee, Jae-Kwang (Personal and ubiquitous computing, 2014)
The system discussed in this paper targets high-risk patients and the elderly living alone requiring ongoing status checking. For services that quickly identify abnormal symptoms that occurred to the subject and send them to medical staff, changes in the patient’s condition are detected by using acceleration (tangent) algorithm. We conducted a study sensing sudden changes based on the value of the location information and temperature/pulse/heartbeat/blood pressure values measured in personal health devices (PHDs), a biological information measuring device attached to the patient. PHDs based on ZigBee, and smartphone will replace the role of the sensor gateway. ZigBee sensor nodes were connected to PHDs, which measure the bio-signals of patients, to form a wireless network.