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Personal‐specific gait recognition based on latent orthogonal feature space

机译:基于潜在正交特征空间的个人特定步态认可

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摘要

Abstract Exoskeleton has been applied in the field of medical rehabilitation and assistance. However, there are still some problems in the interaction between human and exoskeleton, such as time delay, the existence of certain constraints on the human body, and the movement in time is hard to follow. A human motion pattern recognition model based on the long short‐term memory (LSTM) is proposed, which can recognise the state of the human body. Meanwhile, the orthogonalisation method is integrated to make personal‐specific disentangling, and it can effectively improve the generalisation ability of different groups of people, so as to improve the effective follower ability of the exoskeleton. Compared with some other traditional methods, this model has better performance and stronger generalisation ability, which has certain significance in the field of exoskeleton algorithm.
机译:摘要外骨骼已应用于医疗康复和援助领域。然而,人和外骨骼之间的相互作用仍存在一些问题,例如延迟,人体对某些约束的存在,以及难以遵循的运动。提出了一种基于长短期存储器(LSTM)的人体运动模式识别模型,其可以识别人体的状态。同时,整体性分析方法融合以使个人特定的解除响应,可以有效地改善不同群体的泛化能力,从而提高外骨骼的有效跟随力能力。与其他一些传统方法相比,该模型具有更好的性能和更强的泛化能力,在外骨骼算法领域具有一定的重要性。

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