title: Evaluation of stiffness feedback for hard nodule identification on a phantom silicone model.
abstract: Haptic information in robotic surgery can significantly improve clinical outcomes and help detect hard soft-tissue inclusions that indicate potential abnormalities. Visual representation of tissue stiffness information is a cost-effective technique. Meanwhile, direct force feedback, although considerably more expensive than visual representation, is an intuitive method of conveying information regarding tissue stiffness to surgeons. In this study, real-time visual stiffness feedback by sliding indentation palpation is proposed, validated, and compared with force feedback involving human subjects. In an experimental tele-manipulation environment, a dynamically updated color map depicting the stiffness of probed soft tissue is presented via a graphical interface. The force feedback is provided, aided by a master haptic device. The haptic device uses data acquired from an F/T sensor attached to the end-effector of a tele-manipulated robot. Hard nodule detection performance is evaluated for 2 modes (force feedback and visual stiffness feedback) of stiffness feedback on an artificial organ containing buried stiff nodules. From this artificial organ, a virtual-environment tissue model is generated based on sliding indentation measurements. Employing this virtual-environment tissue model, we compare the performance of human participants in distinguishing differently sized hard nodules by force feedback and visual stiffness feedback. Results indicate that the proposed distributed visual representation of tissue stiffness can be used effectively for hard nodule identification. The representation can also be used as a sufficient substitute for force feedback in tissue palpation.
authors.affiliation: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.|State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
authors.forename: Min
authors.identifier: http://orcid.org/0000-0002-2959-9147
authors.initials: M
authors.lastname: Li
authors.affiliation: School of Engineering and Materials Science, Queen Mary University of London, London, United Kingdom.
authors.forename: Jelizaveta
authors.initials: J
authors.lastname: Konstantinova
authors.affiliation: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.|State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
authors.forename: Guanghua
authors.initials: G
authors.lastname: Xu
authors.affiliation: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
authors.forename: Bo
authors.initials: B
authors.lastname: He
authors.affiliation: De Beers Technologies, Maidenhead, United Kingdom.
authors.forename: Vahid
authors.initials: V
authors.lastname: Aminzadeh
authors.affiliation: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.|State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Xie
authors.affiliation: Department of Mechanical Engineering, University College London, London, United Kingdom.
authors.forename: Helge
authors.initials: H
authors.lastname: Wurdemann
authors.affiliation: Faculty of Science & Engineering, Queen Mary University of London, London, United Kingdom.
authors.forename: Kaspar
authors.initials: K
authors.lastname: Althoefer
mesh_terms: D004548:Elasticity; D006801:Humans; D008954:Models, Biological; D019047:Phantoms, Imaging; D065287:Robotic Surgical Procedures / Q000295:instrumentation / Q000379:methods; D012828:Silicones
chemical_list: D012828:Silicones