最低センサー数を用いた人間の動さ計測と認識とその応用

Vincent Bonnet博士成功地完成了他的研究计划，并提供了比预期更多的结果。他成功地用低成本设备在人类身上实现了我们通常用于机器人和高精度传感器的识别程序。他还成功地实现了二次优化，不仅估计动态参数的子集，但整个动态参数集。该方法已被验证与机器人手臂（用于测量精度验证）和几个人的主题（方法验证）的参数识别相对较低的误差。人体的动态参数可以在不到60秒的时间内获得，一个简单的任务，可以调整的水平的运动能力的主题。该运动可以在范围、速度、加速度方面从健康运动员适应于具有病理的老年人。因此，该系统和理论可以用于临床领域，以获得更广泛的应用。他与国立残疾人康复中心的Noritaka Kawashima博士合作进行了实验，以验证临床应用。他的研究成果导致在临床和康复领域使用特定于主题的模型，在新的诊断和量化程序的新突破。

Dr. Vincent Bonnet has succeeded in fulfilling his research plan and providing even more results than expected. He has implemented successfully our identification procedure usually used for robots and high precision sensors, on the human with low cost equipment. He has also successfully implemented the quadratic optimization to estimate not only the subset of dynamics parameters but the entire set of dynamic parameters. The parameters are identified with relative low error and the method has been validated with a robot arm (for measurement accuracy validation) and with several human subjects (for methodology validation).Dynamic parameters of the human body can be obtained in less than 60s, with a simple task, that can be adjusted with the level of motion ability of the subject. The motion can be adapted in term of range, velocity, acceleration from healthy athletes to elderly with pathologies. The system and the theory can thus be used in the clinical field for broader applications. He conducted experiments in collaboration with Dr. Noritaka Kawashima at the National Rehabilitation Center for People with Disabilities to validate the clinical application. His research results lead to new break-through in the use of subject-specific models in the clinical and rehabilitation fields, in new diagnosis and quantification procedures.