Research And Implementation Of Fall Detection Mechanism Based On Mobile Intelligent Terminal

As the Chinese aging population has become a serious problem which leads to a significantly increase amount of elderly people,the society starts to draw more attention to the problem about how to improve the quality of elderly people's life.Since the cost of looking after these elderly people for their children is too high,elderly people sometimes could not receive enough care and therefore have to go outside home by themselves.In this case,the potential risk of elderly people falling down on the ground when they are alone also increases,which becomes one of the most major threats to elderly people's health.With the development of modern society,it is necessary for those suppliers to realize the importance of intelligent terminals and mechanism that fit elderly people's needs.The main work of the thesis focuses on three aspects.Firstly,this thesis starts with the related research of fall detection based on independent sensor.Thesis uses the intelligent terminal sensor to obtain sensor data of various actions including falls,analyzes the sensor data characteristics of each posture,and proposes that it can be used for fall detection.The new features;then,the paper combines the new features that can be used for fall detection and the conclusions of other related research,designs the fall detection algorithm based on intelligent terminal,and tests the accuracy of the algorithm through experiments;finally,the paper elaborates based on The design and implementation of the fall detection prototype system of Android mobile intelligent terminal further verified the feasibility and application significance of the detection mechanism.The main innovations of the thesis focus on combining multi-sensor data,combining the angular velocity change as a new feature with the algorithm of the traditional algorithm based on the acceleration threshold value,and giving an algorithm to evaluate whether the elderly have a fall action.Using the combination of multiple sensor data including angular velocity to perform the fall detection has basically the same accuracy as the similar research,but the algorithm no longer requires the smart terminal to be strictly fixed on the user,and the error of the measurement data is the result.The influence is small,the robustness of the algorithm is improved,and a new method is provided for the intelligent terminal to obtain motion information through the sensor,and the analysis of the fall action has practical application significance.