Using visual cues to enhance haptic feedback for palpation on virtual model of soft tissue.
Identifieur interne : 000335 ( PubMed/Corpus ); précédent : 000334; suivant : 000336Using visual cues to enhance haptic feedback for palpation on virtual model of soft tissue.
Auteurs : Min Li ; Jelizaveta Konstantinova ; Emanuele L. Secco ; Allen Jiang ; Hongbin Liu ; Thrishantha Nanayakkara ; Lakmal D. Seneviratne ; Prokar Dasgupta ; Kaspar Althoefer ; Helge A. WurdemannSource :
- Medical & biological engineering & computing [ 1741-0444 ] ; 2015.
Abstract
This paper explores methods that make use of visual cues aimed at generating actual haptic sensation to the user, namely pseudo-haptics. We propose a new pseudo-haptic feedback-based method capable of conveying 3D haptic information and combining visual haptics with force feedback to enhance the user's haptic experience. We focused on an application related to tumor identification during palpation and evaluated the proposed method in an experimental study where users interacted with a haptic device and graphical interface while exploring a virtual model of soft tissue, which represented stiffness distribution of a silicone phantom tissue with embedded hard inclusions. The performance of hard inclusion detection using force feedback only, pseudo-haptic feedback only, and the combination of the two feedbacks was compared with the direct hand touch. The combination method and direct hand touch had no significant difference in the detection results. Compared with the force feedback alone, our method increased the sensitivity by 5%, the positive predictive value by 4%, and decreased detection time by 48.7%. The proposed methodology has great potential for robot-assisted minimally invasive surgery and in all applications where remote haptic feedback is needed.
DOI: 10.1007/s11517-015-1309-4
PubMed: 26018755
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pubmed:26018755Le document en format XML
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<front><div type="abstract" xml:lang="en">This paper explores methods that make use of visual cues aimed at generating actual haptic sensation to the user, namely pseudo-haptics. We propose a new pseudo-haptic feedback-based method capable of conveying 3D haptic information and combining visual haptics with force feedback to enhance the user's haptic experience. We focused on an application related to tumor identification during palpation and evaluated the proposed method in an experimental study where users interacted with a haptic device and graphical interface while exploring a virtual model of soft tissue, which represented stiffness distribution of a silicone phantom tissue with embedded hard inclusions. The performance of hard inclusion detection using force feedback only, pseudo-haptic feedback only, and the combination of the two feedbacks was compared with the direct hand touch. The combination method and direct hand touch had no significant difference in the detection results. Compared with the force feedback alone, our method increased the sensitivity by 5%, the positive predictive value by 4%, and decreased detection time by 48.7%. The proposed methodology has great potential for robot-assisted minimally invasive surgery and in all applications where remote haptic feedback is needed.</div>
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<Abstract><AbstractText>This paper explores methods that make use of visual cues aimed at generating actual haptic sensation to the user, namely pseudo-haptics. We propose a new pseudo-haptic feedback-based method capable of conveying 3D haptic information and combining visual haptics with force feedback to enhance the user's haptic experience. We focused on an application related to tumor identification during palpation and evaluated the proposed method in an experimental study where users interacted with a haptic device and graphical interface while exploring a virtual model of soft tissue, which represented stiffness distribution of a silicone phantom tissue with embedded hard inclusions. The performance of hard inclusion detection using force feedback only, pseudo-haptic feedback only, and the combination of the two feedbacks was compared with the direct hand touch. The combination method and direct hand touch had no significant difference in the detection results. Compared with the force feedback alone, our method increased the sensitivity by 5%, the positive predictive value by 4%, and decreased detection time by 48.7%. The proposed methodology has great potential for robot-assisted minimally invasive surgery and in all applications where remote haptic feedback is needed.</AbstractText>
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