Research Of Human Motion Pattern Recognition Based On Multi-Sensor

With the continuous improvement of the level of people’s daily lives, the progress of science and the improvement of health conditions, the average human life expectancy is also increasing, which also makes the proportion of aging population in the general population improve, this phenomenon is called the aging of the population. With the deepening of the extent of an aging society, people have paid more and more attention to old people’s day-to-day health care. Along with the growth of the age, the ability of old people begins to decline, all kinds of dangers can easily occur in everyday life. Now many families have only one child, because of the fast pace of life and the work pressure, children can not always accompany the elderly side, resulting in a lot of elderly people in their daily lives is unattended for a long period of time, leading to the occurrence of the phenomenon of empty nest. When danger occurs, empty nesters are often unable to carry out for help and get the medical assistance, resulting in more serious consequences.In order to reduce this risk, it is necessary to real-time monitor and identify the daily activities of old people. It can be found in time when danger occurs, to avoid the situation worse. Real-time motion monitoring methods based on WBAN is one of the hot issues in the field. On the basis of the summary of research in the field, combined with the demand for the formation of topics such as Family Health Network, a portable human motion information acquisition device is designed and then a data acquisition experiment of different human motion mode is organized. On the basis of the data from the device an effective motion pattern recognition algorithm based on support vector machine is put forward.In this paper, the following work was done:1) A portable human body information acquisition device is designed, the device includes a three-axis accelerometer and a three-axis digital gyro, and the two sensors can measure the human body movement acceleration and angular velocity in real time.2) Comprehensive analysis of the strengths and weaknesses of the quaternion method and acceleration method for solving attitude angle, and based on this, a method based on acceleration calibration is put forward, the attitude angle of the human body at any time can be more accurately obtained with this method.3) A human motion pattern recognition algorithm based on support vector machine is put forward. Using the body’s posture characteristics and acceleration characteristics as recognition features, using support vector machine to identify different motion patterns, verification test results show that the method has a good recognition performance.