Real-time synchronized recording of force and position data during a mastoidectomy – Toward robotic mastoidectomy development
Background: Robotics is currently being adopted across the spectrum of neurosurgery from deep brain stimulation to spine surgery instrumentation. Mastoidectomy is a cognitively demanding procedure that involves careful removal of bone around the critical structures of the temporal bone. Herein, we r...
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| Autores principales: | , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2022
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/68924b71f33a4dc6a771639fdf44253e |
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| Sumario: | Background: Robotics is currently being adopted across the spectrum of neurosurgery from deep brain stimulation to spine surgery instrumentation. Mastoidectomy is a cognitively demanding procedure that involves careful removal of bone around the critical structures of the temporal bone. Herein, we report a pilot study that serves as a proof of concept for real-time, multiparameter recording during mastoidectomy. Methods: This pilot study involved the iterative development of a platform for the real time recording of video, 3D position, velocity, acceleration, and force data during the performance of mastoidectomy using cadaveric specimens. Results: Across all 8 replicates, the average distance traveled by the drill tip in the x, y, and z axes was 39.88 mm (±11.98 mm), 38.52 mm (±8.24 mm), 31.40 mm (±7.89 mm), respectively. The overall average ranges for velocity and acceleration of the drill tip in the x axis were 412.81 mm/s (±91.12 mm/s) and 6383.05 mm/s2 (±941.05 mm/s2). The range of forces recorded was 8.52 N (±2.90 N), 40.94 N (±9.81 N), and 35.42 N (±11.06 N) in the x-, y-, and z-axis, respectively. Conclusions: This study represents a proof-of-concept that the mechanical parameters associated with surgeon-performed mastoidectomy can be recorded in real-time. This represents a crucial step in understanding the human drilling process which incorporates visual and haptic sensory input with experiential and explicit knowledge using fuzzy logic feedback. Ultimately, data collected using this methodology may provide the groundwork for the development of an algorithm for robotic mastoidectomy. |
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