Research On A Type Of Fall Detection System For The Elderly Based On CC2541

With the rapid aging of Chinese society,the total number of elderly people increases rapidly.Most of the elderly people are accompanied by chronic non-infectious diseases.These diseases can cause physiological decline and physical dysfunction,making the elderly fall significantly more often than other groups.Falls in the elderly may cause different degrees of injury or even death,and the consequences of falling are closely related to the time difference between receiving help after falling.Therefore,it is especially important for the elderly to get timely help when they fall down.Along with the quickly development of electronic information technology,more and more methods and equipment are emerging to detect falls.Compared with video,environment and other detection methods,wearable fall detection methods have advantages in cost,space and other aspects.Therefore,a wearable system designed with CC2541 chip is designed to detect the fall of the elderly.The main work contents are as follows:(1)We study the methods and discriminant algorithms used to detect the elderly fall and research on the market mainstream testing equipment.According to the application scenario,the overall scheme of the system is determined,including the characteristic position of the device wearing,the establishment of reference coordinate system and the setting of the overall system architecture.(2)In accordance with the system overall scheme,the hardware scheme of the fall detection system is clarified and the production of the prototype is completed,including the peripheral Circuit design of the sensor,the impedance matching of low-power bluetooth,and the design of Printed Circuit Board(PCB).(3)In view of the hardware system,we design the lower computer program and mobile application software which realize the function of data collection,transmission and preservation.Besides,two-step extended Kalman filter,complementary filter and DMP-Kalman filter are used to calculate the attitude angle of the measured object and the decision basis of fall is put forward.(4)The feasibility of the prototype was verified by testing the daily behavior data and fall behavior data of the elderly.Three data fusion algorithms are used to process and analyze the collected data,proving the effectiveness of the algorithm.Among them,DMP-Kalman filtering algorithm has good performance.It can be seen from the test results that the design of this paper can accurately detect the attitude angle of human body,providing an effective reference for the detection equipment of fall.