Gait Training Algorithm of an End-Effector Typed Hybrid Walking Rehabilitation Robot

The present study focused on the gait training algorithm of an end-effector typed hybrid walking rehabilitation robot that our research group developed in 2017. One motor and five link mechanism in the end-effector typed hybrid walking rehabilitation robot were used to mimic normal gait patterns. Depending on patients' condition and training difficulty, three gait rehabilitation training modes were proposed. Mode 1 is a passive mode that motor leads to patients' walking entirely, Mode 2 is an assisted-active mode that a part of patients' muscle strength were supported depending on their walking intention, and Mode 3 is an active mode that patients walk on their own muscle strength under gait resistance by eddy current brake. At each training mode, patients' muscle strength performance by driving motor was experimentally verified using electromyography. In addition, gait symmetry between injured limb and uninjured limb improved as evidenced by motion capture analysis using inertial measurement unit.