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Use Of Classification Algorithms In Determining Surgical Skill Levels Through Surgeons’ Hand Movement Behaviors

Oluşturulma Tarihi: 20-09-2018

Niteleme Bilgileri

Tür: Tez

Alt Tür: Doktora (Mühendislik)

Yayınlanma Durumu: Yayınlanmamış

Dosya Biçimi: PDF

Dil: İngilizce

Konu(lar): TEKNOLOJİ,

Yazar(lar): Topallı, Damla (Yazar),

Emeği Geçen(ler): Çağıltay, Nergiz E. (Danışman),

Anahtar Kelimeler

virtual simulation environment, surgical education, skill-based training, eye-hand coordination, hand movement event metrics, feature selection, classification


Özet

Today, endoscopic surgeries have become an alternative for open procedures whenever possible. In this technique, the surgeon performs the operation by using a camera and light source, called „endoscope‟, and special operational tools in order to operate through small entry points. For such types of operations, surgeons are required to gain several skills, whose development needs hands-on practice in them which is a challenge in surgical education programs. Several technology-enhanced training environments have been developed to improve current surgical education programs. However, in order to better integrate these technologies into the traditional methods, it is critical to understand the skill levels and prepare appropriate content according to the trainees‟ requirements. In other words, the trainees‟ skill levels need to be assessed regularly for better preparing the content and the sequence of the training program according to their individual requirements. The current skill level assessment techniques are mainly based on expert observations which are criticized as expensive and subjective. In this respect, the present study aims to evaluate the surgical skills objectively by using hand movement metrics through computer-based simulation software in Neurosurgery. This study is conducted with 28 surgicalivresidents who were considered as intermediate or novice in their education. The evaluations are mainly concentrated on the hand movements of the trainees on computer simulated surgical training software. Accordingly, first an estimation of skill levels of intermediate and novice surgeons by using classification methods through performance metrics is performed. Secondly, velocity-based hand metrics are calculated using the hand movement data for classifying intermediate and novice surgeons. After that, by adapting BIT algorithm, which is an open source eye-event classification algorithm, to the hand movement data, new hand movement event metrics are proposed. Through these metrics, the participants‟ eye and hand movement events are analyzed. Finally, the results of the classification by using these newly introduced metrics are presented. As a conclusion, this thesis study attempts to better classify the intermediate and novice surgical residents‟ skill levels through their hand-movement events. The results are very promising showing that the proposed metrics potentially improve the accuracy of the classification. The researchers believe that, in the future by using the performance metrics together with hand- and eye- movement events metrics in a combined manner, the level of the accuracy may even be improved.


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Sosyal Medya ve Araçlar

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