The Effects of a Multi-View Camera System on Spatial Cognition, Cognitive Workload and Performance in a Minimally Invasive Surgery Task

• Other Authors: Schroll, Katelyn (Author)
• Format: Dissertation
• Language: English
• Published: 2019
• Subjects: Cognitive psychology; Surgery; Laparoscopic; Minimally Invasive Surgery; Multi-View Camera System; Spatial Cognition; Surgical Training Box
• Online Access: http://hdl.handle.net/2286/R.I.53914

abstract: Minimally invasive surgery is a surgical technique that is known for its reduced patient recovery time. It is a surgical procedure done by using long reached tools and an endoscopic camera to operate on the body though small incisions made near the point of operation while viewing the live camera feed on a nearby display screen. Multiple camera views are used in various industries such as surveillance and professional gaming to allow users a spatial awareness advantage as to what is happening in the 3D space that is presented to them on 2D displays. The concept has not effectively broken into the medical industry yet. This thesis tests a multi-view camera system in which three cameras are inserted into a laparoscopic surgical training box along with two surgical instruments, to determine the system impact on spatial cognition, perceived cognitive workload, and the overall time needed to complete the task, compared to one camera viewing the traditional set up. The task is a non-medical task and is one of five typically used to train surgeons’ motor skills when initially learning minimally invasive surgical procedures. The task is a peg transfer and will be conducted by 30 people who are randomly assigned to one of two conditions; one display and three displays. The results indicated that when three displays were present the overall time initially using them to complete a task was slower; the task was perceived to be completed more easily and with less strain; and participants had a slightly higher performance rate. === Dissertation/Thesis === Masters Thesis Human Systems Engineering 2019