Evaluation of Gait Phase Detection Methods for Walking Assist Robot

Lower paralysis interrupts the mobility and depresses quality of life. Some incomplete paraplegia have an ability to walk in rehabilitation. However, incomplete paraplegia consumes larger energy for the gait motion than able-bodied people. Therefore, it is difficult for them to walk a long time. To solve this problem, many walking assist exoskeletons have been developed. In the case of walking assist, assist timing is one of the essential factors. The mismatch of assist timing interferes user's motion, thus it is required to adjust the assist timing. To control the assist timing, gait phase detection methods are used. Gait motion is divided into several phases. Many researchers introduce the gait phase detection method to control the assist timing. However, there is a mismatch between assist torque and ideal torque which is required by the user. There are no researches to evaluate the gait phase detection methods based on the analysis of the transition of assist torque required by the user. The purposes of this research are to propose the novel FSBM and evaluate the gait phase detection methods. In the experiment, a subject walks on the treadmill with wearing knee exoskeleton. The motor of the exoskeleton is controlled by the bilateral controller. Therefore, the assist torque can be adjusted to be suited to the user by manipulating master side motor. After the experiment, the assist torque and detected gait phases of proposed FSBM are compared to the conventional methods.