2007 Fiscal Year Final Research Report Summary
Development of Methods for Assisting Diagnosis and Rehabilitation of Neuromuscular Disorders based on Musculoskeletal Dynamics Computation
| Project/Area Number |
17200012
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
YAMANE Katsu The University of Tokyo, Graduate School of Information Science and Technology, Associate Professor (00361543)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAMURA Yoshihiko The University of Tokyo, Graduate School of Information Science and Technology, Professor (20159073)
YAMAMOTO Tomotaka The University of Tokyo, Faculty of Medicine University Hospital, Associate Professor (60361490)
TSUJI Shoji The University of Tokyo, Faculty of Medicine University Hospital, Professor (70150612)
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| Project Period (FY) |
2005 – 2007
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| Keywords | Neuro-Musculoskeletal Model / Somatic Reflex / Noninvasive Motion Measurement / Neurology / Rehabilitation / Motion Simulation / Muscle Tension Database / Body Model Parameter Identification |
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| Research Abstract |
1. Development of a Neuromusculoskeletal Model and its Forward/Inverse Dynamics Alforithms, and their Improvements based on Neurological Knowledge We have developed a detailed musculoskeletal human model with 155 degrees-of-freedom skeleton and approximately 1000 muscles. We also modeled the network between the spinal cord and muscles. Physiological knowledge such as somatic reflex and muscle dynamics were used to improve the algorithms for estimating muscle tensions.
2. Visualization and Dimension Reduction of Analysis Results and their Application to Assisting Diagnosis and Rehabilitation We developed software systems to visualize measured and computed motion and/or muscle tension data. We also developed algorithms for dimension reduction fur easy interpretation of the results.
3. Development of Identification Methods with Noninvasive Measurements We developed a number of methods to identify the parameters of our neuromusculoskeletal model, including kinematics, inertia, joint stiffness, muscle, and neuromuscular network parameters. The methods only use noninvasive measurements of motion and electromyography.
4. Proposal of New Methods for Noninvasive Motion Measurement We developed two prototype systems that are supposed to replace conventional optical motion capture systems using spherical markers. The first system utilizes mesh-shaped markers to increase the number of measurement points and improve the safety during measurements. The second method is a markerless approach that can obtain the information on both motion and topology at the same time.
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Research Products
(59 results)
