| Summary: | 碩士 === 國立屏東科技大學 === 資訊管理系所 === 102 === As the populace of elderly is growing quickly, the healthcare system based the state-of-the-art ICT technology is more and more important. According to the statistics of Department of Health Executive Yuan, falling-down accident is the second place of elder accident injury. In addition, there are 30% people, who will fall down in the hospital. Most falls occur at the time points of out off the bed and get on the bed in the hospital. At before, although the hospital provided the emergent bell beside the bed for emergency calls, there are few patients using the emergent bell for the off-bed situation. There is no one thought he will fall before the falls occur. Most of elders consider they can leave bed in safe by themselves. To solve the falling accidents, this project will design the smart sensing and detection system based on the triaxial accelerometer and Back-propagation neural network algorithm to detect abnormal body movement and achieve the smart action awareness. The proposed system not only correctly detects the actions of off-bed and falls, the system but also precisely detects falls before falling. Furthermore, since many elder patients, who have the high risk of fall, are getting out of bed three to five steps then fall occur. The proposed system can detect the actions of the elder patient leaving the bed, and then the system sends the alarm messages to the nursing stations and the duty nurses, who can help the elders leave the bed and to prevent the accident injury. This research project firstly proposed the formal models of off-bed. The proposed detection system used the triaxial accelerations and Back-propagation neural network algorithm to improve the accuracy of action detection. The final purpose of this project is to assist the medical professionals and people to help the elders and help the elders prevent from falling.
|
|---|
