Description
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

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.
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Details

Title
  • The Effects of a Multi-View Camera System on Spatial Cognition, Cognitive Workload and Performance in a Minimally Invasive Surgery Task
Contributors
Date Created
2019
Resource Type
  • Text
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    Note
    • Masters Thesis Human Systems Engineering 2019

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