Research On Sensing System Of Flex-feet Walking Assistant Robot For Gait Detection

Wearable walking assistant robot, which is an interactive robot system, has great potentials in daily activity, sports rehabilitation, clinical medical and military applications. Robot acquires wearer's movement intentions with sensing system, and detects current status in which human body and robot are, then uses those information to plan and control robot's actions of actors. With robot's help, wearer can finish walking movement.To help human body walking, the first step is to recognize the movement intention of human body. And the most important feature of walking is periodicity. Robot needs to detect and recognize each phase of gait cycle first, and plan robot's actions with different characteristics of each phase. The contact force between foot and ground is very important information. The contact force shows cyclical response along with the process of walking. This article analyzes walking movement of human body first, then finds the simultaneous relationship between plantar pressure changes period and gait cycle. Sensing system has been designed to acquire plantar pressure information. By acquiring information on plantar pressure changes in gait cycle, gait cycle is classified and identified. For a better effect of walking assistance, the control system can plan the actions of robot which would be more compliant depend on different phases.The main content of this paper is as follows:1. Analysis of features of human gait: the movement of limbs is analyzed from anatomy. Research on gait detection is done.2. Design and implementation of sensing system: The overall concept of the sensing system is introduced first. Then plantar pressure sensors are selected and signal conditioning circuits are designed. After that sensors are calibrated. At last data acquisition software is written to finish the sensing system.3. Experiment research on human walking with sensing system: article introduces experiment methods and experiment environment first. Then the experiment data is described and interpreted, and the characteristics of each phase of gait cycle are analyzed in-depth. Finally, division method and identification method of gait cycle are presented, and validity of those methods is verified.