Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm
Abstract This study introduces an innovative method for gesture recognition in medical robotics, utilizing Capsule Neural Networks (CNNs) in conjunction with the Modified Spring Search Algorithm (MSSA). This approach achieves remarkable efficiency in gesture identification, facilitating precise cont...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-95288-0 |
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| author | Ziang Liu Xiangzhou Jian Touseef Sadiq Zaffar Ahmed Shaikh Osama Alfarraj Fahad Alblehai Amr Tolba |
| author_facet | Ziang Liu Xiangzhou Jian Touseef Sadiq Zaffar Ahmed Shaikh Osama Alfarraj Fahad Alblehai Amr Tolba |
| author_sort | Ziang Liu |
| collection | DOAJ |
| description | Abstract This study introduces an innovative method for gesture recognition in medical robotics, utilizing Capsule Neural Networks (CNNs) in conjunction with the Modified Spring Search Algorithm (MSSA). This approach achieves remarkable efficiency in gesture identification, facilitating precise control over medical robots. The proposed system undergoes thorough evaluation through both simulations and practical experiments, showing its capability to enhance patient outcomes in robotic surgical procedures. The primary contributions of this research include the creation of a unique CNN-MSSA architecture for gesture recognition, an extensive assessment of the system’s performance, and evidence of its potential to advance patient care. The findings indicate that the system attains an accuracy rate of 95% with a processing duration of 0.5 s, surpassing existing methodologies. These results carry significant implications for the advancement of autonomous medical robots and the enhancement of patient care in robotic surgery, underscoring the technology’s potential to improve the precision and efficiency of medical interventions. |
| format | Article |
| id | doaj-art-94b9d37c2f5b4c19971ab0ed1e488d5f |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-94b9d37c2f5b4c19971ab0ed1e488d5f2025-08-20T03:14:07ZengNature PortfolioScientific Reports2045-23222025-04-0115112510.1038/s41598-025-95288-0Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithmZiang Liu0Xiangzhou Jian1Touseef Sadiq2Zaffar Ahmed Shaikh3Osama Alfarraj4Fahad Alblehai5Amr Tolba6Department of Electrical and Computer Engineering, Carnegie Mellon UniversityDepartment of Mechanical Engineering, Columbia UniversityCentre for Artificial Intelligence Research (CAIR), Department of Information and Communication Technology, University of AgderDepartment of Computer Science and Information Technology, Benazir Bhutto Shaheed University Lyari Computer Science Department, Community College, King Saud University Computer Science Department, Community College, King Saud University Computer Science Department, Community College, King Saud UniversityAbstract This study introduces an innovative method for gesture recognition in medical robotics, utilizing Capsule Neural Networks (CNNs) in conjunction with the Modified Spring Search Algorithm (MSSA). This approach achieves remarkable efficiency in gesture identification, facilitating precise control over medical robots. The proposed system undergoes thorough evaluation through both simulations and practical experiments, showing its capability to enhance patient outcomes in robotic surgical procedures. The primary contributions of this research include the creation of a unique CNN-MSSA architecture for gesture recognition, an extensive assessment of the system’s performance, and evidence of its potential to advance patient care. The findings indicate that the system attains an accuracy rate of 95% with a processing duration of 0.5 s, surpassing existing methodologies. These results carry significant implications for the advancement of autonomous medical robots and the enhancement of patient care in robotic surgery, underscoring the technology’s potential to improve the precision and efficiency of medical interventions.https://doi.org/10.1038/s41598-025-95288-0Bio-inspiredRobotsMedical applicationsGesture-based controlCapsule neural networkModified spring search algorithm |
| spellingShingle | Ziang Liu Xiangzhou Jian Touseef Sadiq Zaffar Ahmed Shaikh Osama Alfarraj Fahad Alblehai Amr Tolba Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm Scientific Reports Bio-inspired Robots Medical applications Gesture-based control Capsule neural network Modified spring search algorithm |
| title | Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm |
| title_full | Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm |
| title_fullStr | Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm |
| title_full_unstemmed | Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm |
| title_short | Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm |
| title_sort | efficient control of spider like medical robots with capsule neural networks and modified spring search algorithm |
| topic | Bio-inspired Robots Medical applications Gesture-based control Capsule neural network Modified spring search algorithm |
| url | https://doi.org/10.1038/s41598-025-95288-0 |
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