Human Motion Measurement And Evaluation Based On Body Sensor Network

Body Sensor Network is a concept which emerged in the latest decade. Compared with traditional wireless network, it has an obvious advantage leading to wide interests from scientific research. Based on the idea of BSN(Body Sensor Network), this paper designs a wearable device, including IMUs, smart shoes and an oxygen sensor, which is used for human motion measurement and evaluation especially in some complex environment, such as climbing stairs. Through this device, some kinematic and dynamic analysis can be done based on some models. Here is the main research content in this paper:First of all. it introduces the basic concept and composition of BSN and the several major researches based on BSN from research institutions at home and abroad. Besides, it introduces the current research results of climbing stairs.Secondly, in the hardware part, this system is mainly composed of 79-axis inertial sensors, a pair of smart shoes used to measure both the human gait and plantar pressure and the sensor used to measure the consumption of oxygen. In addition, there is one controller connecting to each unit by CAN bus and to the PC by WIFI. The transfer rate is up to 100Hz.Thirdly, in the software part, it mainly uses the sensor measurement model to designs an 7-D Extended Kalman Filter based on quaternion to make the angle velocity and quaternion more accurate. Then it designs a new quaternion algorithm to estimate the human low limbs motion. In addition,.it designs a fuzzy control rule using the arctangent fuzzy function for human body gait identification during climbing stairs slowly.Fourthly, according to the principle of Lagrange, it sets up the 7 connecting-rod model of climbing stairs slowly using the quasi static characteristics. The whole process of walking gait in the model is divided into five phases:DS(double support phase), RSLE(right leg support and left leg redundancy phase), RSLT(right leg support and left leg transfer phase), LSRE(left leg support and right leg redundancy phase) and LSRT(left leg support and right leg transfer phase).At Last, it designs three experiments:The first one is to recognize the gait during climbing stairs to verify the validity of the fuzzy controller. Then the experiment of climbing stairs with loads weighing Okg, 5kg,10kg and 15kg is done and the results is compared with the classic method based on high-speed camera motion capture technology to verify the validity of the model. Last one experiment is about the energy consumption during climbing stairs, which is compared with that walking on the flat floor, and it shows it is more energy-consuming during climbing than that walking on the flat floor.