Research And Development Of Plantar 3D Force Sensor

The measurement of plantar force is a prerequisite for gait analysis,clinical diagnosis,and treatment of foot disorders.However,most plantar force sensors currently available only measure plantar pressure,and the measurement of plantar shear force is necessary when detecting various parameters of the foot’s contact with a surface due to the unevenness of the plantar surface.Therefore,this paper designs a plantar 3D force sensor based on the improved traditional cross-beam structure and the combined resistive characteristics of thin-film pressure sensors.This paper improves the structure of the traditional flat cross-beam elastic body structure for the usage scenarios and conditions of the plantar 3D force sensor.The force beam is combined with the cross-beam to complete the preliminary design of the plantar force sensor’s structure.On this basis,this paper parametrically processes the structural parameters of the plantar force sensor and optimizes the elastic body structure of the plantar force sensor through central combination experiments,and designs other component structures and sizes to achieve the external packaging of the plantar 3D force sensor.To collect signals from the plantar 3D force sensor,this paper uses a resistive conversion amplification module to convert the resistance value of the thin-film pressure sensor into a voltage signal,and transmits the voltage signal to the upper computer through the analog data acquisition module.This paper uses the graphical programming language Lab VIEW to write data processing software,which uses array index functions to separate signal data and achieve real-time display and storage of plantar force information.Finally,this article establishes a calibration test bench for plantar force sensors to conduct calibration experiments.The plantar force sensors are decoupled using the BP neural network,and the experimental data are normalized.Once the error reaches the predetermined requirement,the parameters of the network model are determined,thus obtaining the BP neural network model for the plantar force sensors.After decoupling using the BP neural network method,the static errors of the plantar force sensors are relatively small,indicating the effectiveness of employing this method for decoupling the plantar force sensors.