3D human mesh recovery system for motor function assessment
Stroke is a leading cause of disabilities worldwide, with hemiplegia emerging as the prevalent impairment after stroke. Such impairment is associated with restricted activities and worse health-related quality of life. Traditional rehabilitation assessment methods are qualitative, such as Fugl-Mey...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175963 |
| _version_ | 1811682317157007360 |
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| author | Wang, Ruisi |
| author2 | Liu Ziwei |
| author_facet | Liu Ziwei Wang, Ruisi |
| author_sort | Wang, Ruisi |
| collection | NTU |
| description | Stroke is a leading cause of disabilities worldwide, with hemiplegia emerging as the prevalent impairment after stroke. Such impairment is associated with restricted activities and worse health-related quality of life.
Traditional rehabilitation assessment methods are qualitative, such as Fugl-Meyer scale. Generally, different therapists have
different evaluations. Additionally, it is labour-intensive and time-consuming, including a large number of repetitive body movements with the assistance of doctors or professional therapists.
This report proposes an automated upper extremity motor function assessment system that can be practically used in a clinical environment, utilizing three calibrated Azure Kinect cameras. Benefits from SMPLer-X, a generalist foundation model for monocular motion capture, patients can be reconstructed in 3D space. Based on the confidence level of 3D joints, the resultant parametric human model (SMPL-X) undergoes further optimization using multi-view images, offering a detailed representation of the patient’s body pose and joint positions. Following the Fugl-Meyer Assessment (FMA) guidelines, a rule-based logic classification algorithm has been developed to automatically assign FMA scores using the extracted features obtained from the Kinect cameras.
Furthermore, we have adapted this pose estimation system for mobile phones to enhance its accessibility and usability for future development. Normal assessment such as Upper limb rehabilitation requires long-term, repetitive rehabilitation training and assessment. Most stroke survivors cannot receive adequate outpatient stroke rehabilitation due to barriers including costs, travel and limited use of public transportation. The future work aims to develop a home-based virtual rehabilitation system that could be a useful alternative for conventional rehabilitation to overcome barriers for outpatient rehabilitation. |
| first_indexed | 2024-10-01T03:54:55Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/175963 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:54:55Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1759632024-05-10T15:40:58Z 3D human mesh recovery system for motor function assessment Wang, Ruisi Liu Ziwei School of Computer Science and Engineering ziwei.liu@ntu.edu.sg Computer and Information Science Stroke is a leading cause of disabilities worldwide, with hemiplegia emerging as the prevalent impairment after stroke. Such impairment is associated with restricted activities and worse health-related quality of life. Traditional rehabilitation assessment methods are qualitative, such as Fugl-Meyer scale. Generally, different therapists have different evaluations. Additionally, it is labour-intensive and time-consuming, including a large number of repetitive body movements with the assistance of doctors or professional therapists. This report proposes an automated upper extremity motor function assessment system that can be practically used in a clinical environment, utilizing three calibrated Azure Kinect cameras. Benefits from SMPLer-X, a generalist foundation model for monocular motion capture, patients can be reconstructed in 3D space. Based on the confidence level of 3D joints, the resultant parametric human model (SMPL-X) undergoes further optimization using multi-view images, offering a detailed representation of the patient’s body pose and joint positions. Following the Fugl-Meyer Assessment (FMA) guidelines, a rule-based logic classification algorithm has been developed to automatically assign FMA scores using the extracted features obtained from the Kinect cameras. Furthermore, we have adapted this pose estimation system for mobile phones to enhance its accessibility and usability for future development. Normal assessment such as Upper limb rehabilitation requires long-term, repetitive rehabilitation training and assessment. Most stroke survivors cannot receive adequate outpatient stroke rehabilitation due to barriers including costs, travel and limited use of public transportation. The future work aims to develop a home-based virtual rehabilitation system that could be a useful alternative for conventional rehabilitation to overcome barriers for outpatient rehabilitation. Bachelor's degree 2024-05-10T05:27:07Z 2024-05-10T05:27:07Z 2024 Final Year Project (FYP) Wang, R. (2024). 3D human mesh recovery system for motor function assessment. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175963 https://hdl.handle.net/10356/175963 en SCSE23-0240 application/pdf Nanyang Technological University |
| spellingShingle | Computer and Information Science Wang, Ruisi 3D human mesh recovery system for motor function assessment |
| title | 3D human mesh recovery system for motor function assessment |
| title_full | 3D human mesh recovery system for motor function assessment |
| title_fullStr | 3D human mesh recovery system for motor function assessment |
| title_full_unstemmed | 3D human mesh recovery system for motor function assessment |
| title_short | 3D human mesh recovery system for motor function assessment |
| title_sort | 3d human mesh recovery system for motor function assessment |
| topic | Computer and Information Science |
| url | https://hdl.handle.net/10356/175963 |
| work_keys_str_mv | AT wangruisi 3dhumanmeshrecoverysystemformotorfunctionassessment |