Background Minimally invasive neurosurgery poses several challenges to surgeons due to constrained working environment, and its implications on the surgical outcome are an area of growing concern. The instrument handle… Click to show full abstract
Background Minimally invasive neurosurgery poses several challenges to surgeons due to constrained working environment, and its implications on the surgical outcome are an area of growing concern. The instrument handle design directly affects surgeon's performance, and the conventional ring handle causes ergonomic discomfort. Objective The aim of this study was to design and validate a palm grasping-based ergonomic handle for skull-base neuroendoscopic instruments. Materials and Methods The handle was designed based on the palm grasping technique and to naturally match the contours of hand. The ergonomic handle was fabricated and assembled with the end-effector of biopsy forceps. Fifteen participants with no experience of neuroendoscopic procedures validated the ergonomic handle. During data collection, participants performed the ring transfer task on straight, right tilt (+30°) and left tilt (-30°) of activity plates of neuro-endo-trainer (NET) with 0° and 30° endoscopes. Results Feedback from participants indicated that there was significant improvement in degree of discomfort in performing the task on straight (P = 0.006) and tilted plate (P = 0.001) and degree of pain (0.0001) using the ergonomic handle. Furthermore, video analysis of the performed task shows that there was statistical improvement in hitting events (P = 0.001, P = 0.04), tugging events (P = 0.00001, P = 0.00001,) and picking attempts (P = 0.04, P = 0.0004) on straight and tilted plates, respectively. There was reduction in ring drop, jerk, and average moving time, but results were not significant. Conclusion The subjective validation of ergonomic handle by neurosurgeons shows that the designed handle offers ergonomic advantages. Objective validation by video analysis shows that the ergonomic handle results in better task performance on NET surgical trainer.
               
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