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Title: Development of sensing systems for improving surgical grasper performance
Author: Jones, Dominic Paul
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2019
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Minimally invasive techniques play a vital and increasing role in modern surgery. In these procedures, surgical graspers are essential in replacing the surgeon's fingertips as the main manipulator of delicate soft tissues. Current graspers lack haptic feedback, restricting the surgeon to visual feedback. Studies show that this can frequently lead to morbidity or task errors due to inappropriate application of force. Existing research has sought to address these concerns and improve the safety and performance of grasping through the provision of haptic feedback to the surgeon. However, an effective method of grasping task optimisation has not been found. This thesis explores new sensing approaches intended to reduce errors when manipulating soft tissues, and presents a novel tactile sensor designed for deployment in the grasper jaw. The requirements were first established through discussion with clinical partners and a literature review. This resulted in a conceptual approach to use multi-axis tactile sensing within the grasper jaw as a potential novel solution. As a foundation to the research, a study was conducted using instrumented graspers to investigate the characteristics of grasp force employed by surgeons of varying skill levels. The prevention of tissue slip was identified as a key method in the prevention of grasper misuse, preventing both abrasion through slip and crush damage. To detect this phenomena, a novel method was proposed based on an inductive pressure sensing system. To investigate the efficacy of this technique, experimental and computational modelling investigations were conducted. Computational models were used to better understand the transducer mechanisms, to optimise sensor geometry and to evaluate performance in slip detection. Prototype sensors were then fabricated and experimentally evaluated for their ultimate use in slip detection within a surgical grasper. The work concludes by considering future challenges to clinical translation and additional opportunities for this research in different domains.
Supervisor: Culmer, Peter ; Alazmani, Ali Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available