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PhD viva presentation

Haptic feedback of rigid tool/soft object interaction in medical training and robot-assisted minimally invasive surgery Sense of touch is crucial for surgeons to effectively identify tumours and boundaries, and, thus to achieve successful cancer resections. To overcome the touch information loss which occurs during robotic-assisted surgical procedures, researchers have proposed methods capable of acquiring partial haptic feedback and mimicking the physical interaction which takes place between surgical tools and human tissue during palpation. This thesis proposes and evaluates haptic palpation systems and suggests the combination of different feedback methods for tumour identification in medical training and robot-assisted minimally invasive surgery using tissue models based on rolling indentation. Novel pseudo-haptic tissue stiffness simulation methods, multi-fingered haptic interfaces, and hybrid feedback methods are proposed and evaluated.