Abstract
Lower limb rehabilitation robots are of great significance for poststroke patients to regain locomotion ability. However, most rehabilitation robots fail to take the movement of CoM of human body into account. Considering that CoM is an essential index to assess the recovery effect and improve the treatment, we propose a simple, economic, portable, and highly efficient CoM perception approach based on Kinect camera. This novel method is capable of detecting the displacement and rotation of CoM in multi-planes. Results of walking tests show that our approach has competitive performance in capturing the variation trends of CoM compared with multi-cameras motion capture system, especially in some directions with large displacement variation. The high accuracy, simple and low-cost detection of CoM is a major step forward towards practical application in the assessment of rehabilitation after stroke.
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Notes
- 1.
When the depth camera is set to wide field-of-view depth mode.
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Acknowledgement
This work was supported in part by the National Natural Science Foundation of China (Grant No. 52075177), Joint Fund of the Ministry of Education for Equipment Pre-Research (Grant No. 6141A02033124), Research Foundation of Guangdong Province (Grant No. 2019A050505001 and 2018KZDXM002), Guangzhou Research Foundation (Grant No. 202002030324 and 201903010028), Zhongshan Research Foundation (Grant No.2020B2020), and Shenzhen Institute of Artificial Intelligence and Robotics for Society (Grant No. AC01202005011).
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Liu, Y., Liu, B., Zhou, Z., Cai, S., Xie, L. (2021). A Novel Center of Mass (CoM) Perception Approach for Lower-Limbs Stroke Rehabilitation. In: Li, H., et al. Social Robotics. ICSR 2021. Lecture Notes in Computer Science(), vol 13086. Springer, Cham. https://doi.org/10.1007/978-3-030-90525-5_53
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DOI: https://doi.org/10.1007/978-3-030-90525-5_53
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