Haptic-Assisted Collaborative Robot Framework for Improved Situational Awareness in Skull Base Surgery
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913203128107008 |
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| author | Ishida, Hisashi Sahu, Manish Munawar, Adnan Nagururu, Nimesh Galaiya, Deepa Kazanzides, Peter Creighton, Francis X. Taylor, Russell H. |
| author_facet | Ishida, Hisashi Sahu, Manish Munawar, Adnan Nagururu, Nimesh Galaiya, Deepa Kazanzides, Peter Creighton, Francis X. Taylor, Russell H. |
| contents | Skull base surgery is a demanding field in which surgeons operate in and around the skull while avoiding critical anatomical structures including nerves and vasculature. While image-guided surgical navigation is the prevailing standard, limitation still exists requiring personalized planning and recognizing the irreplaceable role of a skilled surgeon. This paper presents a collaboratively controlled robotic system tailored for assisted drilling in skull base surgery. Our central hypothesis posits that this collaborative system, enriched with haptic assistive modes to enforce virtual fixtures, holds the potential to significantly enhance surgical safety, streamline efficiency, and alleviate the physical demands on the surgeon. The paper describes the intricate system development work required to enable these virtual fixtures through haptic assistive modes. To validate our system's performance and effectiveness, we conducted initial feasibility experiments involving a medical student and two experienced surgeons. The experiment focused on drilling around critical structures following cortical mastoidectomy, utilizing dental stone phantom and cadaveric models. Our experimental results demonstrate that our proposed haptic feedback mechanism enhances the safety of drilling around critical structures compared to systems lacking haptic assistance. With the aid of our system, surgeons were able to safely skeletonize the critical structures without breaching any critical structure even under obstructed view of the surgical site. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_11709 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Haptic-Assisted Collaborative Robot Framework for Improved Situational Awareness in Skull Base Surgery Ishida, Hisashi Sahu, Manish Munawar, Adnan Nagururu, Nimesh Galaiya, Deepa Kazanzides, Peter Creighton, Francis X. Taylor, Russell H. Robotics Systems and Control Skull base surgery is a demanding field in which surgeons operate in and around the skull while avoiding critical anatomical structures including nerves and vasculature. While image-guided surgical navigation is the prevailing standard, limitation still exists requiring personalized planning and recognizing the irreplaceable role of a skilled surgeon. This paper presents a collaboratively controlled robotic system tailored for assisted drilling in skull base surgery. Our central hypothesis posits that this collaborative system, enriched with haptic assistive modes to enforce virtual fixtures, holds the potential to significantly enhance surgical safety, streamline efficiency, and alleviate the physical demands on the surgeon. The paper describes the intricate system development work required to enable these virtual fixtures through haptic assistive modes. To validate our system's performance and effectiveness, we conducted initial feasibility experiments involving a medical student and two experienced surgeons. The experiment focused on drilling around critical structures following cortical mastoidectomy, utilizing dental stone phantom and cadaveric models. Our experimental results demonstrate that our proposed haptic feedback mechanism enhances the safety of drilling around critical structures compared to systems lacking haptic assistance. With the aid of our system, surgeons were able to safely skeletonize the critical structures without breaching any critical structure even under obstructed view of the surgical site. |
| title | Haptic-Assisted Collaborative Robot Framework for Improved Situational Awareness in Skull Base Surgery |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2401.11709 |