2007 Fiscal Year Final Research Report Summary
Study on the kinematic measurement and durability assessment for the artificial knee joint by using a robot
| Project/Area Number |
17300156
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (B)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Biomedical engineering/Biological material science
|
|---|
| Research Institution | Kyushu University |
|---|
Principal Investigator |
HIROKAWA Shunji Kyushu University, Faculty of Engineering, Professor (80150374)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
MURAKAMI Teruo KYUSHU UNIVERSITY, Faculty of Engineering, Professor (90091347)
IWAMOTO Yukihide KYUSHU UNIVERSITY, Faculty of Medical Science, Professor (00213322)
ARIYOSHI Shogo KYUSHU UNIVERSITY, Faculty of Engineering, Associate Professor (40038493)
MIURA Hiromasa KYUSHU UNIVERSITY, University Hospital, Associate Professor (10239189)
TSURUNO Reiji KYUSHU UNIVERSITY, Faculty of Design, Associate Professor (10197775)
|
|---|
| Project Period (FY) |
2005 – 2007
|
| Keywords | Simulation Engineering / Biomaterial / Biology・Biomechanics / Tribology / Clinical Medicine / Artificial Knee Joint / X-ray Photography / Robot |
|---|
| Research Abstract |
In this study, we proposed three ideas to improve a kinematic estimation algorithm for Total Knee Arthroplasty. The first was a two-step estimation algorithm that improves estimation accuracy by excluding certain assumptions needed for the current pattern matching algorithm. The second was incorporating a 3D geometric articulation model into the algorithm to improve estimation accuracy substantially for the depth translation, and to introduce contact points' trajectories between the articular surfaces. The third was an algorithm to process estimation even when the silhouettes of two components overlap. To assess our algorithm's potential for clinical application, we carried out two experiments. First, we used a robot to position a prosthesis. Estimation accuracy was checked by comparing input data to the robot with the estimates from X-ray photographs. Incorporating our articulation model remarkably reduced the error in the depth translation. Next, we performed a clinical assessment by applying the algorithm and articulation model to fluoroscopy images of six patients who had recently had TKA.
|
Research Products
(36 results)
