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

文森特·邦纳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。他成功地实现了我们通常用于机器人和高精度传感器的识别程序，在低成本的设备上。他还成功地实现了二次优化，不仅估计了动力学参数的子集，而且估计了整个动力学参数集。参数的识别误差相对较低，该方法已通过机械臂（用于测量精度验证）和几个人类受试者（用于方法学验证）进行验证。人体的动态参数可以在60秒内获得，任务简单，可以根据受试者的运动能力水平进行调整。运动范围，速度，加速度可以适应从健康运动员到老年病理。因此，该系统和理论可以在临床领域得到更广泛的应用。他与国家残疾人康复中心的Noritaka Kawashima博士合作进行了实验，以验证临床应用。他的研究成果在临床和康复领域使用特定学科模型，在新的诊断和量化程序方面取得了新的突破。

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.