The Research Of Elderly Instability Posture Detection System

With China gradual enters an aging society,the proportion of the elderly in Chinese population is growing,and the issue of guardianship of the elderly healthy has become a more important social problem.Numerous studies have shown that the fall behavior caused by the instability of the elderly has become the first killer of the physical and mental health of the elderly.Therefore,the research of this essay focuses on the fall of the elderly after the posture instability happens.In view of the problem that the elderly are prone to fall down,besides the timely care and prevention in advance,the most important thing is to contact the important guardians and rescue centers in time after the occurrence of unusual dangerous situations,get the first aid and reduce the injury.The purpose of this study is to design a set of instability detection and alarm system which can detect the posture and movement of the elderly in real time.The system can detect the posture of the human body in real-time when the elderly are in danger,especially when the falls occur,the elderly can actively trigger the release of alarm information,or when the system detects a serious situation,actively trigger the release of alarm infor-mation.This article focuses on the following contents:1.Determine the way of collecting human posture information and how to use wearable technology reliably to acquire human physiological parameters.2.To determine the algorithm of fall detection,a new method based on triaxial acceleration and inclination angle is proposed to improve the existing algorithm of fall detection.3.Using embedded microcontroller to carry out reliable data processing,coordinate the task of each module,at the same time,ensure the trigger interruption in the event of need to ensure reliable alarm.Experimental analysis shows that when a dangerous event such as a fall occurs,the posture information of the human body can be determined and an alarm message can be issued within 15 seconds.The accuracy rate of judging non-protective falls was 100%and 89.5%respectively.