Document Details

Document Type : Thesis 
Document Title :
Operating Room Ergonomics, Training and Assessment Algorithm using Virtual Reality and Machine Learning
خوارزمية التدريب والتقييم لوضعية الجراح في غرفة العمليات باستخدام الواقع الافتراضي والتعلم الآلي
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
Abstract : In the medical field, there has been an accentuated acknowledgement of the importance of ergonomics and the analysis of data. Due to long term standing, difficult body postures, and the need to exert pressure on tissues, neurosurgeons are subjected to occupational risks when performing open surgical operations. This dissertation is divided into two parts. The first part provides a training approach for residents that enable them to acquire the ergonomic skills needed for spine surgeries. The need to show if that Virtual Reality simulators can improve the ergonomics skill in residents. A Virtual Reality training simulator has been designed and implemented, the simulator measures two ergonomic skills need to be maintained during any surgery: neck angle and table height. The experiments showed that the users are usually focused on their work and tend to pay less attention to their body position and movements. This result in a bad ergonomics setup which leads to back and neck pain. Thus, the users need to be trained to have good ergonomics positions. In the proposed system, this is measured using a specific metric that collects head positions, angles, hands movements as well as elbow height and other parameters. The designed model showed that incorporating simulations into resident training, simulated surgeries will strengthen the surgeon’s skills and outcomes. The second part of this dissertation aims to build a machine learning model utilizing some machine learning algorithms including YOLO, HOG, SVM, CNN, and VGG16 in order to estimate surgeons poses during operations. This technique will give a report that precisely measuring the ergonomic skills about the surgeons and the team. Key Word: ergonomics, training, surgery, simulation, algorithm 
Supervisor : Prof. Wadee Alhalabi 
Thesis Type : Doctorate Thesis 
Publishing Year : 1443 AH
2022 AD
 
Co-Supervisor : Dr. Abdulrahman Sabbagh 
Added Date : Wednesday, January 25, 2023 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
هند هزاع الشريفAlsharif, Hind HazzaResearcherDoctorate 

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