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We propose a novel methodology for predicting human gait pattern kinematics based on a statistical and stochastic approach using a method called Gaussian process regression (GPR). We selected 14 body parameters that significantly affect the gait pattern and 14 joint motions that represent gait kinematics. The body parameter and gait kinematics data were(More)
In order to implement promising robot applications in our daily lives, robots need to perform manipulation tasks within the human environments. Especially for a humanoid robot, it is essential to manipulate a variety of objects with different shapes and sizes to assist humans in the human environments. This paper presents a method of manipulating objects(More)
This paper represents the method to manipulate the objects with the upper body of a humanoid robot by capturing human motions in real-time. To control the upper body of a humanoid robot and make it behave as a human does, we define several virtual spring-damper elements between the humanoid robot and the human. The resultant motions given by the virtual(More)
Training for balancing, which is governed by the motion of pelvis and thorax, is a key for gait rehabilitation. COWALK, which is a gait rehabilitation robot under development in our institute, is capable of pelvic motion training. In this paper, we describe a statistical method to generate pelvic motion which is considered to fit each person, i.e.,(More)
The purpose of this paper is to propose a new assessment method for evaluating motor function of the patients who are suffering from physical weakness after stroke, incomplete spinal cord injury (iSCI) or other diseases. In this work, we use a robotic device to obtain the information of interaction occur between patient and robot, and use it as a measure(More)
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