Delasaei Marvi, Sahar and Sherafati, Arash and Tahery, Majid Mohammad and Zein, Samir (2020) Comparison of the Effectiveness of Two Types of Single Port Minimal Invasive Neurosurgical Robots to Ablation and Resection of Brain Tumor. International Clinical Neuroscience Journal, 7 (4). pp. 201-207. ISSN 2383-1871
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Abstract
Background: Using minimally invasive neurosurgical robots is one of the most desirable ablation methods and resection of brain tumors. In this study, forward kinematics and Jacobian matrix calculated for two single-port robots for comparing the effectiveness of two types of single port minimal invasive surgical robots to ablation and resection of brain tumor
Methods: The motion analysis of robots type 1 and 2 has compared to each other. Ablation manipulator in robot type 1 has five degrees of freedom, but in robot type 2, three revolute degrees of freedom of this manipulator has replaced with a revolute joint perpendicular to the previous three revolute joints.
Results: Results showed that for resection surgery, in the same conditions, robot type 2 damaged 58.9 mm3 more of cerebral cortex tissue than robot type 1 to resect the brain tumors. To establish a static balance, robot type 2 needs to tolerate at least 41% more internal loading than robot type 1. The maximum velocity for robot type 1 in the contact location between the end-effector and the tumor is 1.7 times more than robot type 2. The maximum end-effector force of robot type 1 to apply the tumor for ablation surgery is more than 1.8 times in robot type 2, but the maximum moment and power for ablation surgery and resection of these two robots were the same less than 1% difference.
Conclusion: Despite the more straightforward mechanism, a minimum number of joints, and better kinematics range of robot type 2, robot types 1 has the possibility for transformation, establishes the static balancing, and does a better ablation surgery with less damage to the brain.
Item Type: | Article |
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Subjects: | Academics Guard > Medical Science |
Depositing User: | Unnamed user with email support@academicsguard.com |
Date Deposited: | 21 Jan 2023 07:48 |
Last Modified: | 15 Jun 2024 12:04 |
URI: | http://science.oadigitallibraries.com/id/eprint/36 |