Estimation of Finite Finger Joint Centers of Rotation Using 3D Hand Skeleton Motions Reconstructed from CT Scans
The present study proposed a method to estimate the finite finger joint centers of rotation (CoRs) with high accuracy using 3D hand skeleton motions reconstructed from CT scans. Ten hand postures starting from a fully extended posture and ending at a fist posture with about 10° difference in flexion...
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MDPI AG
2020-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/24/9129 |
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| author | Xiaopeng Yang Zhichan Lim Hayoung Jung Younggi Hong Mengfei Zhang Dougho Park Heecheon You |
| author_facet | Xiaopeng Yang Zhichan Lim Hayoung Jung Younggi Hong Mengfei Zhang Dougho Park Heecheon You |
| author_sort | Xiaopeng Yang |
| collection | DOAJ |
| description | The present study proposed a method to estimate the finite finger joint centers of rotation (CoRs) with high accuracy using 3D hand skeleton motions reconstructed from CT scans. Ten hand postures starting from a fully extended posture and ending at a fist posture with about 10° difference in flexion between the adjacent postures were captured by a CT scanner for 15 male participants, and their 3D hand skeletons were reconstructed using the CT scans. Each bone segment from the full extension posture was registered to the corresponding bone segments of the remaining hand postures. The proximal bone segments of a joint from two postures were aligned to estimate the finite CoR of the joint between the two postures. Centerlines of the distal bone segments of the joint were then identified using the principal component analysis method, and the finite CoR of the joint was determined as the intersection point of the identified centerlines. The proposed method reduced the variation of estimated finite joint CoRs by 16.0% to 67.0% among the finger joints compared to the existing methods. The variation of estimated finite joint CoRs decreased as the rotation angle of the joint increased. The proposed method can be used for the simulation of finger movement with high accuracy. |
| first_indexed | 2024-03-10T13:53:33Z |
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| id | doaj.art-80617555457742268dafce32cfa4f42e |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T13:53:33Z |
| publishDate | 2020-12-01 |
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| series | Applied Sciences |
| spelling | doaj.art-80617555457742268dafce32cfa4f42e2023-11-21T01:50:46ZengMDPI AGApplied Sciences2076-34172020-12-011024912910.3390/app10249129Estimation of Finite Finger Joint Centers of Rotation Using 3D Hand Skeleton Motions Reconstructed from CT ScansXiaopeng Yang0Zhichan Lim1Hayoung Jung2Younggi Hong3Mengfei Zhang4Dougho Park5Heecheon You6School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, ChinaDepartment of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang 37673, KoreaDepartment of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang 37673, KoreaDepartment of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang 37673, KoreaSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, ChinaDepartment of Rehabilitation Medicine, Pohang Stroke and Spine Hospital, Pohang 37659, KoreaDepartment of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang 37673, KoreaThe present study proposed a method to estimate the finite finger joint centers of rotation (CoRs) with high accuracy using 3D hand skeleton motions reconstructed from CT scans. Ten hand postures starting from a fully extended posture and ending at a fist posture with about 10° difference in flexion between the adjacent postures were captured by a CT scanner for 15 male participants, and their 3D hand skeletons were reconstructed using the CT scans. Each bone segment from the full extension posture was registered to the corresponding bone segments of the remaining hand postures. The proximal bone segments of a joint from two postures were aligned to estimate the finite CoR of the joint between the two postures. Centerlines of the distal bone segments of the joint were then identified using the principal component analysis method, and the finite CoR of the joint was determined as the intersection point of the identified centerlines. The proposed method reduced the variation of estimated finite joint CoRs by 16.0% to 67.0% among the finger joints compared to the existing methods. The variation of estimated finite joint CoRs decreased as the rotation angle of the joint increased. The proposed method can be used for the simulation of finger movement with high accuracy.https://www.mdpi.com/2076-3417/10/24/9129finite center of rotationfinger jointhand skeleton motionCT scan |
| spellingShingle | Xiaopeng Yang Zhichan Lim Hayoung Jung Younggi Hong Mengfei Zhang Dougho Park Heecheon You Estimation of Finite Finger Joint Centers of Rotation Using 3D Hand Skeleton Motions Reconstructed from CT Scans Applied Sciences finite center of rotation finger joint hand skeleton motion CT scan |
| title | Estimation of Finite Finger Joint Centers of Rotation Using 3D Hand Skeleton Motions Reconstructed from CT Scans |
| title_full | Estimation of Finite Finger Joint Centers of Rotation Using 3D Hand Skeleton Motions Reconstructed from CT Scans |
| title_fullStr | Estimation of Finite Finger Joint Centers of Rotation Using 3D Hand Skeleton Motions Reconstructed from CT Scans |
| title_full_unstemmed | Estimation of Finite Finger Joint Centers of Rotation Using 3D Hand Skeleton Motions Reconstructed from CT Scans |
| title_short | Estimation of Finite Finger Joint Centers of Rotation Using 3D Hand Skeleton Motions Reconstructed from CT Scans |
| title_sort | estimation of finite finger joint centers of rotation using 3d hand skeleton motions reconstructed from ct scans |
| topic | finite center of rotation finger joint hand skeleton motion CT scan |
| url | https://www.mdpi.com/2076-3417/10/24/9129 |
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