A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis
Alleviating the burden on amputees in terms of high-level control of their prosthetic devices is an open research challenge. EMG-based intention detection presents some limitations due to movement artifacts, fatigue, and stability. The integration of exteroceptive sensing can provide a valuable solu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Series: | Robotics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-6581/12/6/152 |
| _version_ | 1797379461639831552 |
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| author | Gianmarco Cirelli Christian Tamantini Luigi Pietro Cordella Francesca Cordella |
| author_facet | Gianmarco Cirelli Christian Tamantini Luigi Pietro Cordella Francesca Cordella |
| author_sort | Gianmarco Cirelli |
| collection | DOAJ |
| description | Alleviating the burden on amputees in terms of high-level control of their prosthetic devices is an open research challenge. EMG-based intention detection presents some limitations due to movement artifacts, fatigue, and stability. The integration of exteroceptive sensing can provide a valuable solution to overcome such limitations. In this paper, a novel semiautonomous control system (SCS) for wrist–hand prostheses using a computer vision system (CVS) is proposed and validated. The SCS integrates object detection, grasp selection, and wrist orientation estimation algorithms. By combining CVS with a simulated EMG-based intention detection module, the SCS guarantees reliable prosthesis control. Results show high accuracy in grasping and object classification (≥97%) at a fast frame analysis frequency (2.07 FPS). The SCS achieves an average angular estimation error ≤18° and stability ≤0.8° for the proposed application. Operative tests demonstrate the capabilities of the proposed approach to handle complex real-world scenarios and pave the way for future implementation on a real prosthetic device. |
| first_indexed | 2024-03-08T20:24:35Z |
| format | Article |
| id | doaj.art-f09c8a5df3fd479ca41f242dcd21c886 |
| institution | Directory Open Access Journal |
| issn | 2218-6581 |
| language | English |
| last_indexed | 2024-03-08T20:24:35Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Robotics |
| spelling | doaj.art-f09c8a5df3fd479ca41f242dcd21c8862023-12-22T14:39:36ZengMDPI AGRobotics2218-65812023-11-0112615210.3390/robotics12060152A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist ProsthesisGianmarco Cirelli0Christian Tamantini1Luigi Pietro Cordella2Francesca Cordella3Research Unit of Advanced Robotics and Human-Centred Technologies, Universitá Campus Bio-Medico di Roma, 00128 Rome, ItalyResearch Unit of Advanced Robotics and Human-Centred Technologies, Universitá Campus Bio-Medico di Roma, 00128 Rome, ItalyUniversitá di Napoli Federico II, 80125 Naples, ItalyResearch Unit of Advanced Robotics and Human-Centred Technologies, Universitá Campus Bio-Medico di Roma, 00128 Rome, ItalyAlleviating the burden on amputees in terms of high-level control of their prosthetic devices is an open research challenge. EMG-based intention detection presents some limitations due to movement artifacts, fatigue, and stability. The integration of exteroceptive sensing can provide a valuable solution to overcome such limitations. In this paper, a novel semiautonomous control system (SCS) for wrist–hand prostheses using a computer vision system (CVS) is proposed and validated. The SCS integrates object detection, grasp selection, and wrist orientation estimation algorithms. By combining CVS with a simulated EMG-based intention detection module, the SCS guarantees reliable prosthesis control. Results show high accuracy in grasping and object classification (≥97%) at a fast frame analysis frequency (2.07 FPS). The SCS achieves an average angular estimation error ≤18° and stability ≤0.8° for the proposed application. Operative tests demonstrate the capabilities of the proposed approach to handle complex real-world scenarios and pave the way for future implementation on a real prosthetic device.https://www.mdpi.com/2218-6581/12/6/152hand–wrist prosthesisartificial visionsemiautonomous control |
| spellingShingle | Gianmarco Cirelli Christian Tamantini Luigi Pietro Cordella Francesca Cordella A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis Robotics hand–wrist prosthesis artificial vision semiautonomous control |
| title | A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis |
| title_full | A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis |
| title_fullStr | A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis |
| title_full_unstemmed | A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis |
| title_short | A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis |
| title_sort | semiautonomous control strategy based on computer vision for a hand wrist prosthesis |
| topic | hand–wrist prosthesis artificial vision semiautonomous control |
| url | https://www.mdpi.com/2218-6581/12/6/152 |
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