Large Deformation Object Modeling Using Finite Element Method And Proper Orthogonal Decomposition For Haptic Robots

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2008Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2008Bu çalışmada, hissedici arabirimler ve bu arabirimlerde kullanılan hesaplama metotları incelenmiştir. Bu amaçla doğrultusunda, yüksek deformasyon özelliğine sahip doğrusal olmayan bir kirişin modeli sonlu elemanlar metodu kullanılarak elde edilmiştir ve bu model gerçek zamalı olarak PHANTOM® Premium 6 DOF hissedici arabirimi ile etkileşime geçirilmiştir. Etkileşimi elde etmek amacıyla, kiriş modeli OpenGL kütüphanesi kullanılarak görselleştirilmiştir ve cihaza OpenHaptics kütüphanesinin HDAPI fonksiyonları kullanılarak hükmedilmiştir. Hissedici cihazların ihtiyaç duyduğu yüksek hesaplama hızlarını elde edebilmek amacıyla uygun ortogonal ayrıştırma metodunu kullanarak düşük mertebeli model elde edilmiştir. Her iki modelin davranışı incelendiginde uygun orthogonal ayrıştırma metodunun, orjinal model davranışı gösterdiği saptanmış ve hesaplama zamanlarının büyük oranda azaldığı görülmüştür.In this study, haptic systems are introduced with investigation of haptic interfaces and haptic rendering. To this end, a large deformation real time beam model is developed and integrated with the PHANTOM® Premium 6 DOF haptic robot. OpenGL library is used as a visualization tool of the model and the haptic robot is manipulated using libraries of OpenHaptics named as HDAPI. In order to obtain high computational demands of the haptic systems, Proper Orthogonal Decomposition method is used to obtain a low order model. Investigations of both models have revealed that lower order model behaves exactly in a similar manner as the original model with reduced computational effort.Yüksek LisansM.Sc

Virtual Reality Simulator for Training in Myringotomy with Tube Placement

Myringotomy refers to a surgical incision in the eardrum, and it is often followed by ventilation tube placement to treat middle-ear infections. The procedure is difficult to learn; hence, the objectives of this work were to develop a virtual-reality training simulator, assess its face and content validity, and implement quantitative performance metrics and assess construct validity. A commercial digital gaming engine (Unity3D) was used to implement the simulator with support for 3D visualization of digital ear models and support for major surgical tasks. A haptic arm co-located with the stereo scene was used to manipulate virtual surgical tools and to provide force feedback. A questionnaire was developed with 14 face validity questions focusing on realism and 6 content validity questions focusing on training potential. Twelve participants from the Department of Otolaryngology were recruited for the study. Responses to 12 of the 14 face validity questions were positive. One concern was with contact modeling related to tube insertion into the eardrum, and the second was with movement of the blade and forceps. The former could be resolved by using a higher resolution digital model for the eardrum to improve contact localization. The latter could be resolved by using a higher fidelity haptic device. With regard to content validity, 64% of the responses were positive, 21% were neutral, and 15% were negative. In the final phase of this work, automated performance metrics were programmed and a construct validity study was conducted with 11 participants: 4 senior Otolaryngology consultants and 7 junior Otolaryngology residents. Each participant performed 10 procedures on the simulator and metrics were automatically collected. Senior Otolaryngologists took significantly less time to completion compared to junior residents. Junior residents had 2.8 times more errors as compared to experienced surgeons. The senior surgeons also had significantly longer incision lengths, more accurate incision angles, and lower magnification keeping both the umbo and annulus in view. All metrics were able to discriminate senior Otolaryngologists from junior residents with a significance of p \u3c 0.002. The simulator has sufficient realism, training potential and performance discrimination ability to warrant a more resource intensive skills transference study

Haptic Enhancement of Sensorimotor Learning for Clinical Training Applications

Modern surgical training requires radical change with the advent of increasingly complex procedures, restricted working hours, and reduced ‘hands-on’ training in the operating theatre. Moreover, an increased focus on patient safety means there is a greater need to objectively measure proficiency in trainee surgeons. Indeed, the existing evidence suggests that surgical sensorimotor skill training is not adequate for modern surgery. This calls for new training methodologies which can increase the acquisition rate of sensorimotor skill. Haptic interventions offer one exciting possible avenue for enhancing surgical skills in a safe environment. Nevertheless, the best approach for implementing novel training methodologies involving haptic intervention within existing clinical training curricula has yet to be determined. This thesis set out to address this issue. In Chapter 2, the development of two novel tools which enable the implementation of bespoke visuohaptic environments within robust experimental protocols is described. Chapters 3 and 4 report the effects of intensive, long-term training on the acquisition of a compliance discrimination skill. The results indicate that active behaviour is intrinsically linked to compliance perception, and that long-term training can help to improve the ability of detecting compliance differences. Chapter 5 explores the effects of error augmentation and parameter space exploration on the learning of a complex novel task. The results indicate that error augmentation can help improve learning rate, and that physical workspace exploration may be a driver for motor learning. This research is a first step towards the design of objective haptic intervention strategies to help support the rapid acquisition of sensorimotor skill. The work has applications in clinical settings such as surgical training, dentistry and physical rehabilitation, as well as other areas such as sport