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IEEE International Conference on Robotics and Automation (ICRA)

作者： Ko Ayusawa Gentiane Venture Yoshihiko Nakamura Department of Mechano-Informatics University of Tokyo Bunkyo Tokyo Japan Department of Mechanical System Engineering Tokyo University of Agriculture슠and슠Technology Koganei Tokyo Japan

The mass properties are important to control robot dynamics or study human dynamics. In our previous works, we proposed a method to identify inertial parameters of legged mechanisms from base-link dynamics, using generalized coordinates and external forces information. In this paper, we propose an identification method based on floating-base dynamics, when the system has no external force. Inertial parameters can be identified without force measurement, only from motion data. The method has been tested on two examples; a simple chain consisted of two links and the human body dynamics.

关键词： Humans Robot kinematics Equations Matrix decomposition Robotics and automation Humanoid robots Force measurement Orbital robotics Mobile robots USA Councils

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Optimal estimation of human body segments dynamics using realtime visual feedback

Optimal estimation of human body segments dynamics using rea...

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2009 IEEE/RSJ International Conference on Intelligent Robots and systems, IROS 2009

作者： Venture, Gentiane Ayusawa, Ko Nakamura, Yoshihiko Department of Mechano-Informatics University of Tokyo Japan Department of Mechanical System Engineering Tokyo University of Agriculture and Technology Japan

ISBN: (纸本)9781424438044

Mass parameters of the human body segments are mandatory when studying motion dynamics. In orthopedics, biomechanics and rehabilitation they are of crucial importance. Inaccuracies their value generate errors in the motion analysis, misleading the interpretation of results. No systematic method to estimate them has been proposed so far. Rather, parameters are scaled from generic tables or estimated with methods inappropriate for in-patient care. Based on our previous works, we propose a real-time software and its interface that allow to estimate the whole-body segment parameters, and to visualize the progresses of the completion of the identification. The visualization is used as a visual feedback to optimize the excitation and thus the identification results. The method is experimentally tested and obtained results are discussed. © 2009 IEEE.

关键词： Parameter estimation

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Real-time identification and visualization of human segment parameters

Real-time identification and visualization of human segment ...

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31st Annual International Conference of the IEEE engineering in Medicine and Biology Society: engineering the Future of Biomedicine, EMBC 2009

作者： Venture, Gentiane Ayusawa, Ko Nakamura, Yoshihiko Department of Mechanical System Engineering Tokyo University of Agriculture and Technology Japan Department of Mechano-Informatics University of Tokyo Japan

ISBN: (纸本)9781424432967

Mass parameters of the body segments are mandatory to study motion dynamics. No systematic method to estimate them has been proposed so far. Rather, parameters are scaled from generic tables or estimated with methods inappropriate for in-patient care. Based on our previous works, we propose a real-time software that allows to estimate the whole-body segment parameters, and to visualize the progresses of the completion of the identification. The visualization is used as a feedback to optimize the excitation and thus the identification results. The method is experimentally tested. ©2009 IEEE.

关键词： Visualization

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Real-time identification and visualization of human segment parameters

Real-time identification and visualization of human segment ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Gentiane Venture Ko Ayusawa Yoshihiko Nakamura Department of Mechanical System Engineering Tokyo University of Agriculture슠and슠Technology Japan Department of Mechano-Informatics University of Tokyo Japan

Mass parametersof the body segments are mandatory to study motion dynamics. No systematic method to estimate them has been proposed so far. Rather, parameters are scaled from generic tables or estimated with methods inappropriate for in-patient care. Based on our previous works, we propose a real-time software that allows to estimate the whole-body segment parameters, and to visualize the progresses of the completion of the identification. The visualization is used as a feedback to optimize the excitation and thus the identification results. The method is experimentally tested.

关键词： Humans Interpolation Equations Data visualization USA Councils Testing Biological system modeling Orthopedic surgery Biomechanics Nervous system

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Optimal estimation of human body segments dynamics using realtime visual feedback

Optimal estimation of human body segments dynamics using rea...

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2009 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Ko Ayusawa Yoshihiko Nakamura Gentiane Venture Department of Mechanical System Engineering Tokyo University of Agriculture슠and슠Technology Japan Department of Mechano-Informatics University of Tokyo Japan

关键词： Humans Feedback Interpolation Biological system modeling Motion estimation Orthopedic surgery Biomechanics Visualization Condition monitoring Robustness

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Detecting changes in motion characteristics during sports training

Detecting changes in motion characteristics during sports tr...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Dana Kulic Gentiane Venture Yoshihiko Nakamura Department of Mechano-Informatics University of Tokyo Japan Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada Department of Mechanical System Engineering Tokyo University of Agriculture슠and슠Technology Koganei Tokyo Japan Department of Mechano-Informatics University of Tokyo Bunkyo Tokyo Japan

This paper proposes a stochastic approach for representing and analyzing the gradual changes that occur in human movement during sports training. Human movement primitives are described using factorial hidden Markov models, and compared using the Kullback-Liebler distance, a measure of information divergence between two models. This representation is combined with an automated segmentation and clustering approach to enable the system to autonomously extract and group together movement primitives from continuous observation of human movement data. The proposed system is tested on a human movement dataset obtained over 4 months during training for a marathon. Experimental results demonstrate that the system is able to detect gradual changes in the human movement.

关键词： Motion detection Hidden Markov models Stochastic processes Motion analysis Humans Data mining system testing Principal component analysis Power system modeling USA Councils

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Monitoring the segment parameters during long term physical training from motion capture data

Monitoring the segment parameters during long term physical ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Gentiane Venture Ko Ayusawa Dana Kulic Yoshihiko Nakamura Department of Mechanical System Engineering Tokyo University of Agriculture슠and슠Technology Japan Department of Mechano-Informatics University of Tokyo Japan Department of Electrical and Computer Engineering University of Waterloo Canada

The segment parameters (SP) consisting of inertia and position of the center of mass of each segment, of the human body are crucial data when one wants investigate motion dynamics. The segment parameters vary with time according to immobilization, physical training, rehabilitation, muscular diseases. This knowledge provides valuable information to support medical diagnosis and to quantify the effect of medical treatment, rehabilitation or training. However they are usually difficult to measure in-vivo for these kinds of applications and thus are not specifically used. In this paper we propose to apply a previously developed identification method in order to monitor the evolutions of those parameters over 5 months, during which the candidate followed a 16-week marathon training before running the 2009 Tokyo Marathon. The motion data is recorded on a weekly basis and the parameters are computed after each session. The obtained results are presented and the changes in body SP are discussed in the light of typical results occurring to the body fitness.

关键词： Condition monitoring Humans Biological system modeling Diseases Biomedical monitoring USA Councils Medical diagnosis Medical treatment Biomechanics Medical services

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Skill-Assist Safety and Intelligence Technology

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International Journal of Automation Technology 2009年第6期3卷 643-652页

作者： Lee, Suwoong Yamada, Yoji Department of Bio-System Engineering Graduate School of Science and Engineering Yamagata University 419 Building No.8 4-3-16 Jonan Yamagata Yonezawa992-8510 Japan Mechano-Informatics and Systems Department of Mechanical Science and Engineering Graduate School of Engineering Nagoya University 303 Building No.2 North Furo-cho Chikusa-ku Nagoya464-8603 Japan

Skill-Assist for automobile manufacturing enables op-erators to move heavy component modules to tar-get sites, playing a valuable role on production lines. Skill-Assist has high-powered actuators and operates in physical contact with users, so safety is a top pri-ority. This paper describes safety technology developed for and implemented in Skill-Assist at the National Institute of Advanced Industrial Science and Technology, Japan (Skill-Assist@AIST). Risk was as-sessed for main causes of potentially hazardous events, which were projected to result from abnormal command signals generated by the controller, human er-ror, and unauthorized access. In this paper, we focus on safety measures against abnormal command signals and human error, and introduce current safety technology for Skill-Assist@AIST. Highly reliable control includes a dual-channel controller and fail-safe fault-detection hardware (FSFDH) for ensuring functional safety through command signal monitoring. A reaching-gesture recognition (RGR) algorithm based on laser range sensor data and a hidden Markov model (HMM) predictively detect operator error that outlies predefined safe reaching. © Fuji Technology Press Ltd.

关键词： Accident prevention

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Biorhythm-Based Awakening Timing Modulation

Biorhythm-Based Awakening Timing Modulation

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yuki Wakuda Akiko Noda Kosuke Sekiyama Yasuhisa Hasegawa Toshio Fukuda Department of Mechano-Informatics System Engineering University of Nagoya Nagoya Aichi Japan School of Health Science University of Nagoya Nagoya Japan Department of Inteligent Interaction Technologies University of Tsukuba Tsukuba Ibaraki Japan

The purpose of the present study is to control human biological rhythm and life cycle by optimization of awakening timing. We developed a wearable interface for controlling awakening time named "BRAC (biological rhythm based awakening timing controller)". BRAC could estimate bio-rhythm by pulse wave from finger tip and send awake signal to user. An ordinary alarm clock operates according to set times that have to be set in advance. However, humans have a rhythm in their sleep, which affects one's sleep depth and wake-up timing. We consider the simplest way to control or reset human's bio-rhythm or life style is to optimize the awakening timing and the sleeping hours. We examined the relationship between controlling awakening timing based on autonomous nerve rhythm and equilibrium function. Our findings suggest indicate that the prototype "BRAC" could evaluate user's biological rhythm and awakes user at the time optimized for physical function of equilibrium.

关键词： Timing Rhythm Biological control systems Humans Sleep Control systems Biomedical monitoring Medical control systems Automatic control Clocks

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Intelligent Robotic systems: Safety, Security, Health, and Dependability

Intelligent Robotic Systems: Safety, Security, Health, and D...

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International Conference on Hybrid Intelligent systems (HIS)

作者： T. Fukuda Department of Micro System Engineering and Department of Mechano-Informatics and Systems University of Nagoya Japan

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