Gait phase recognition under proportion-uncontrolled body weight support based on plantar pressure sensor
SONG Guang-yue, SONG Zhi-bin, XIANG Zhong-xia
Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, School of Mechanical Engineering,Tianjin University, Tianjin 300350, China
The lower extremity exoskeleton robot is a new means to help patients with lower extremity motor dysfunction, which can reduce the labor intensity of therapists. Body weight support is often used to complete the auxiliary training. However, for the ground walking weight-loss exoskeleton robot system, the ratio of body weight support would change with the gait and wearing situation, so it is important to recognize the gait phase under proportion-uncontrolled body weight support. A plantar pressure acquisition system based on the Arduino Mega2560 board and eight single-membrane pressure sensors in one side shoe was established, and the plantar pressure information of normal walking and body weight support walking with weight-loss belt under proportion-uncontrolled body weight support was collected. Then, the gait phase recognition was carried out using neural network algorithm. The results showed that the pressure values of left and right feet significantly decreased and two sides were symmetrical in body weight support walking compared with normal walking, but the pressure reduction ratio of each pressure sensor was different. The gait phase recognition rate of normal walking reached 96.8% and the gait phase recognition rate of body weight support walking could still reach 94.8% by using neural network algorithm. The research results show that the plantar pressure acquisition system can effectively measure the plantar pressure under body weight support walking, and provide some support for the formulation of control strategy for body weight support exoskeleton robots with weight-loss belt under proportion-uncontrolled body weight support on the ground.
SONG Guang-yue, SONG Zhi-bin, XIANG Zhong-xia. Gait phase recognition under proportion-uncontrolled body weight support based on plantar pressure sensor. Chinese Journal of Engineering Design, 2019, 26(3): 260-266.
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