Research On Human Motion Recognition Based On Inertial Sensor

With the development of the times,motion analysis and recognition technology is developing continuously,and its application scope is also expanding.In this paper,a new scheme is proposed for human motion analysis and recognition.Unlike the traditional motion capture technique,human motion analysis and recognition based on inertial sensors is an emerging field of pattern recognition.It overcomes the disadvantages of traditional video action recognition of the many shortcomings and limitations,with a higher operability and practicality.The essence is that the movement information of the human body is collected by the inertial sensor fixed in the specific part of the human body and transmitted to the PC through the wireless transmission module,and then the data is pre-processed,the feature extracted and selected and the action classified.Human behavioral analysis and recognition technology have been widely applied and produced great value in many fields,such as medical rehabilitation engineering,somatosensory game field,film and television works creation,virtual reality,professional sports analysis and so on.In this paper,the human motion is analyzed,and the acquisition scheme based on the inertial sensor is defined,and the format of the collected motion data is analyzed in detail.On the basis of the analysis,the human joint,the human body model,the joint angle and the attitude angle are analyzed,and the attitude angle is applied to the human body motion analysis,and the hip joint angle is identified as the original data.Then the human body structure and rigid body model were defined,and 15 parts were selected as sensors.The movement data were acquired by inertial sensor-based motion capture system,and a database based on inertial sensor has been built.Secondly,we did a detailed research on the action level,summed up a variety of basic movements contained in the daily human movement,and standardize the data collection and collection conditions.After that,the related algorithms of data preprocessing and motion feature extraction and recognition are studied.Considering the noise of the system,the original data are preprocessed to eliminate the large deviation from the normal value,and the Butterworth low-pass filtering is taken into account to take the low-pass of the human action to extract the feature points for the multidimensional attitude angle data.Finally,the motion recognition based on the dynamic time regularization method is given,and the recognition rates of each action of the inertial sensor are given,and compared with the classical algorithm HMM identification method.The main contribution of this paper is innovation in three aspects.Firstly,a database based on the inertial sensor motion isestablished,and a method and a process for preprocessing the motion data are proposed.Secondly,the main recognition feature of the attitude angle of the hip position is proposed,and the feature extraction algorithm of the key feature frame is defined.And the feature sequence of state space is proposed.Thirdly,the identification of inertial sensors is realized based on the dynamic time regularization recognition algorithm and the recognition rate of inertial sensors based on spatial state motion are improved.