The Research Of Wearable System Based On Motion Information Monitoring

The rapid development of the intelligent wearable device for improving the quality of the people's life provides a portable and efficient tool, and with health care has become the current hot research topic, using the wearable devices to detect human movement state and health indicators is the research focus in the problem. With the help of a wearable device can easily access and all kinds of biological signal collection, combined with the feature of biological mechanism and the movement can be further analysis and determine the state of the human body, thus achieve the purpose of testing. But the actual demand of test results and can not effectively reasonable exercise plan and reflect the change of physical health in the movement, and most existing methods only provides a uniform standard, fail to reflect the personalized bring differences. Therefore, how to integrate the existing research achievements of sports medicine and other physical indicators, for individuals to provide reasonable personalized health standards, implementation planning in advance, the purpose of real-time monitoring has become the new direction of the development of the intelligent wearable devices.This paper using a series of sensor module and controller design for specific scenarios for the human body movement and health indicators testing and evaluation of practical system, and through data analysis and processing, combining the theory of kinematics and the experimental results, gives the quantitative indicators can be used for sports and health assessment, have certain reference significance for practical applications. At first, this paper mainly use of calories index to reflect the movement effect, this paper expounds the reflection of the human body health commonly used quantitative indicators, has been clear about the calories as a measure of exercise and health and compare the rationality of the existing calorie consumption analysis method and the principle, designed and implemented based on the triaxial acceleration calories detection module. Secondly, Combining the theory of regional anatomy, to clarify the mechanism and characteristics of the multi-channel semg and the effectiveness of the electromyographic signal to measure the activity of arm movements, and analyze and compare the time domain analysis, frequency domain analysis and time-frequency domain analysis, empirical mode decomposition of electromyographic signal analysis method of the principle and advantages and disadvantages. Design has realized the data acquisition module, multi-channel semg and completed a simple scenario based on arm movements in data collection, design an effective pretreatment method based on the signal. Through carries on the empirical mode decomposition(EEMD) multi-channel semg, build relevant feature extracting reflect the status of muscle fatigue, and exercise the quantitative relation, thus for reasonable evaluation provides a clear movement effect and intensity measure. Constructed based on EEMD Hilbert spectrum analysis(EEMD- HHT) muscle coherence between the model and analysis of electromyographic signal characteristics in different aspects, and the muscle fatigue characteristics in the process of motion estimation, and based on the analysis of the test data movement process of sEMG average instantaneous frequency and coupling characteristics between between muscle, muscle fatigue analysis provides a comprehensive evaluation method. Finally, Test and analysis the effectiveness of muscle fatigue of EEMD- HHT method of actual data, comprehensive the above results provide personalized sports health with reasonable evaluation index, the measure for exercise program specified and the provided reference standard.