The Research Of Key Technologies In The Real-time Arm Motion Monitoring System For Smart Terminals

With the repid development of wearable devices,increased people use warable devices in their daily life.Smart watches and smart bracklets are coming into their life.Available and high precison arm motion moniting system based on wearable devices is very useable for people's life scenarios,such as sports posture correction,driving safety supervision,gesture tracking using VR devices,etc.Recent research related to the IMUbased sensors in wearable devices for motion monitoring of people continues to progress and face vital challenges.One of them is to track people's motion using a single wearable device.The aim of this thesis is to investigate a real-time arm motion monitoring method for smart devices,using a smartphone and a smart watch to monitor people's arm motion with high accuracy and in real time without additional cost.This thesis focuses on three key issues: real-time arm motion monitoring based on a single wearable device,highprecision ultrasonic ranging based on FMCW,and real-time motion monitoring based on the fusion of IMU and ultrasonic FMCW.The method of real-time motion monitoring based on a single warable device first obtains the user's wrist orientation and acceleration through user's watch or bracklets,pre-processes the data,including coordinate alignment and denoising,and then inputs the pre-precessed data into the point cloud query module to query the point cloud corresponding to the instantaneous orientation.The point cloud contains a one-to-many relationship from the wrist orientation to wrist joint positions,and the specific wrist position cannot be inferrd from a wrist joint orientation.Thus,the user's wrist position is predicted by fusing the oritentaion and acceleration of the user's wrist through a Hidden Morkov Model(HMM),which use the acceleration as the observed state.Additionally,by controlling the size of point clouds,optimizing the point cloud query efficiency,and giving a further constrains with user's wrist motion speed,it can meet the requirements of real-time.The elbow joint position can be deduced by the wrist joint position and the wrist orientation.Finally,it outputs the position of the two joints to realize the real-time monitoring of the arm motion.The ultrasonic ranging based on FMCW dual transmitting and receiving is based on the time of arrival(To A)High accuracy acsoutic ranging relies on the measurement accuracy of To A,which often affectd by the device clock skew,system delay and clock synchronization.We propose an ultrasonic ranging method based on FMCW,which compensating for the possible multipath effect,doppler shift and signal distortion.In addition,the use of inaudible ultrasound frequency band reduces the interference to users,and finally realizes real-time ultrasonic ranging with high accuracy and availability.The real-time motion monitoring method based on the fusion of fusion of IMU and ultrasonic FMCW,combines the method of predictiong joint position by point clouds based on a single wearable device with the ultrasonic ranging based on FMCW.It constrains the range of the point cloud by the relative distance between the user's phone and the wearable device.We propose a motion monitoring method based on HMM-EKF.An EKF is fused in the method to give a correction of the user's wrist position predicted by the basic HMM model,with the accuracy and efficiency improvement.In addition,by analyzing the motion characteristics of the shoulder joint,we propose a non-linear optimization method to predict the should joint position with the elbow joint position,while the user's torso stable.Finally,this thesis verifies the feasibility and effectiveness of each method through extensive theoretical analysis and relevant experiments.