Hybrid intelligent artificial limb control method and system

Abstract

The invention discloses a hybrid intelligent artificial limb control method and system. The method comprises the following steps: detecting gait information from a healthy limb through an artificial limb detection module, transmitting the gait information to a gait planning module, generating an artificial limb gait through the gait planning module, and transmitting the artificial limb gait to a hybrid driving mechanism. An artificial limb executing mechanism is driven by the hybrid driving mechanism to move, the ground-human-artificial limb interaction process is completed, and the gait information comprises gait parameters and gait types. The method has the beneficial effects that the motion intention of an amputated person can be sensed, the artificial limb controlled by a micro-processing unit can achieve any gait, and the other healthy leg of the amputated person can be accurately coordinated to act. The effectiveness and reliability of the system are higher, and in order to improve the man-machine interaction capability and adaptability of the system, the system can adapt to different users to freely and naturally walk under different road conditions and different walking modes.

Description

technical field [0001] The invention relates to a hybrid intelligent prosthesis control method, in particular to a hybrid intelligent prosthesis control method and system, belonging to the technical field of prosthesis control applications. Background technique [0002] Many scholars have given different views on the modular division and design of the intelligent prosthetic control system. Jung-Hoon Kim et al. designed an above-knee prosthetic joint based on a magneto-rheological damper. With sensors, the gait tracking adopts PD control, which has achieved certain results. However, this knee joint adopts a single-axis rotation structure, and the control However, there is still a certain practical gap in the estimation of gait parameters. Gong Siyuan et al. designed a lower limb prosthetic control model, simulated it through Matlab's Sim PowerSystem toolbox, and downloaded it to TI's TMS320F2812 system through Simulink for execution, confirming the reliability of the algorit...

AI Technical Summary

Problems solved by technology

Jung-Hoon Kim et al. designed an above-knee prosthetic joint based on a magneto-rheological damper. With sensors, the gait tracking adopts PD control, which has achieved certain results. However, this knee joint adopts a single-axis rotation structure, and the control However, there is still a certain practical gap in the estimation of gait parameters.

Gong Siyuan et al. designed a lower limb prosthetic control model, simulated it through Matlab's Sim PowerSystem toolbox, and downloaded it to TI's TMS320F2812 system through Simulink for execution, confirming the reliability of the algorithm, but this active lower limb development The platform does not take into account the human-computer interaction system, and the experience of prosthetic users needs to be further improved

Frank Sup et al. designed a prototype active knee and ankle prosthesis. They carefully designed the structure of the prosthesis and designed the load unit, but this prosthesis uses a fixed gait planning curve, which is different for different gait parameters and different The gait in the environment cannot be adjusted adaptively, so further work can be done on human-computer interaction, and the average power of this active prosthesis is tens of watts, which is also a challenge for the battery design of portable prostheses.

T. Latif et al. gave a prosthetic control system model driven by surface electromyography and designed a drive circuit, but this prosthesis is too bulky and slow to respond. Therefore, intelligent prosthetics based on surface electromyography The control system is still immature, and the system speed and reliability need to be improved urgently

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