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.
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References
Altman DG, Bland J (1994) Diagnostic test 1: sensitivity and specificity. BMJ 308:1552
Bibin L, Anatole L, Bonnet M, Delbos A, Dillon C (2008) SAILOR: a 3-D medical simulator of loco-regional anaesthesia based on desktop virtual reality and pseudo-haptic feedback. In: ACM symposium on virtual reality software and technology (VRST) 2008, pp 97–100
Conover WJ (1980) Practical nonparametric statistics, 2nd edn. Wiley, UK
De Gersem G (2005) Reliable and enhanced stiffness perception in soft-tissue telemanipulation. Int J Robot Res 24(10):805–822
Ernst MO, Banks MS (2002) Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415(6870):429–433
Fawcett T (2006) An introduction to ROC analysis. Pattern Recognit Lett 27(8):861–874
Gwilliam JC, Mahvash M, Vagvolgyi B, Vacharat A, Yuh DD, Okamura AM (2009) Effects of haptic and graphical force feedback on teleoperated palpation. In: Proceedings of IEEE international conference on robotics and automation 2009, pp 677–682
Hachisu T, Cirio G, Marchal M, Luyer A (2011) Pseudo-haptic feedback augmented with visual and tactile vibrations. IEEE international symposium on virtual reality innovation 2011, pp 327–328
Hayward V, Astley O, Cruz-Hernandez M, Grant D, Robles-De-La-Torre G (2004) Haptic interfaces and devices. Sens Rev 24(1):16–29
Hayward V (2008) A brief taxonomy of tactile illusions and demonstrations that can be done in a hardware store. Brain Res Bull 75(6):742–752
Kim SY, Kyung KU, Park J, Kwon DS (2007) Real-time area-based haptic rendering and the augmented tactile display device for a palpation simulator. Adv Robot 21(9):961–981
Kimura T, Nojima T (2012) Pseudo-haptic feedback on softness induced by grasping motion. In: Isokoski P, Springare J (eds): EuroHaptics 2012, pp 202–205
Klatzky RL, Lederman SJ, Langseth S (2003) Watching a cursor distorts haptically guided reproduction of mouse movement. J Exp Psychol Appl 9(4):228–235
Lecuyer A, Burkhardt JM, Tan CH (2008) A study of the modification of the speed and size of the cursor for simulating pseudo-haptic bumps and holes. ACM Trans Appl Percept 5(3):1–21
Lecuyer A, Burkhardt JM, Coquillart S, Coiffet P (2001) Boundary of illusion: an experiment of sensory integration with a pseudo-haptic system. In: Proceedings of the 2001 IEEE virtual reality conference, pp 115–122
Li M, Faragasso A, Konstantinova J, Aminzadeh V, Seneviratne LD, Dasgupta P, Althoefer K (2014) A novel tumor localization method using haptic palpation based on soft tissue probing data. In: Proceedings of IEEE international conference on robotics and automation 2014, pp 4188–4193
Li M, Liu H, Seneviratne LD, Althoefer K (2012) Tissue stiffness simulation and abnormality localization using pseudo-haptic feedback. In: Proceedings of IEEE international conference on robotics and automation 2012, pp 5359–5364
Liu H, Noonan DP, Challacombe BJ, Dasgupta P, Seneviratne LD, Althoefer K (2010) Rolling mechanical imaging for tissue abnormality localization during minimally invasive surgery. IEEE Trans Biomed Eng 57(2):404–414
Liu H, Li J, Song X, Seneviratne LD, Althoefer K (2011) Rolling indentation probe for tissue abnormality identification during minimally invasive surgery. IEEE Trans Robot 27(3):450–460
Liu H, Sangpradit K, Li M, Dasgupta P, Althoefer K, Seneviratne LD (2014) Inverse finite-element modeling for tissue parameter identification using a rolling indentation probe. Med Biol Eng Comput 52(1):17–28
Masuzaki R, Tateishi R, Yoshida H, Sato T, Ohki T, Goto T, Yoshida H, Sato S, Sugioka Y, Ikeda H, Shiina S, Kawabe T, Omata M (2007) Assessing liver tumor stiffness by transient elastography. Hepatol Int 1(3):394–397
Megumi N, Kuroda T, Komori M, Oyama H (2003) Evaluation and user study of haptic simulator for learning palpation in cardiovascular surgery. In: Proceedings of international conference on artificial reality and telexistence 2003.
Mensvoort K, Vos P, Hermes DJ, Liere RV (2010) Perception of mechanically and optically simulated bumps and holes. ACM Trans Appl Percept 7(2):10:1–24
Nedel LP, Thalmann D (1998) Real-time muscle deformations using mass-spring systems. In: Proceedings computer graphics international 1998, pp 156–165
Netti PA, Berk DA, Swartz MA, Grodzinsky AJ, Jain RK (2000) Role of extracellular matrix assembly in interstitial transport in solid tumors. Cancer Res 60(9):2497–2503
Salomon G, Kollerman J, Thederan I, Chun FKH, Budaus L, Schlomm T, Isbarn H, Heinzer H, Huland H, Graefen M (2008) Evaluation of prostate cancer detection with ultrasound real-time elastography: a comparison with step section pathological analysis after radical prostatectomy. Eur Urol 54(6):1354–1362
Sangpradit K, Liu H, Dasgupta P, Althoefer K, Seneviratne LD (2011) Finite-element modeling of soft tissue rolling indentation. IEEE Trans Biomed Eng 58(12):3319–3327
Venkatesh SK, Yin M, Glockner JF, Takahashi N, Araoz PA, Talwalkar JA, Ehman RL (2008) MR elastography of liver tumors: preliminary results. AJR Am J Roentgenol 190(6):1534–1540
Wallis S (2013) Binomial confidence intervals and contingency tests: mathematical fundamentals and the evaluation of alternative methods. J Quant Linguist 20(3):178–208
Wellman P, Howe R (1999) Breast tissue stiffness in compression is correlated to histological diagnosis. Harv BioRob Lab Tech Rep
Wilcoxon F (1946) Individual comparisons of grounded data by ranking methods. J Econ Entomol 39:269
Wilson EB (1927) Probable inference, the law of succession, and statistical inference. J Am Stat Assoc 22:209–212
Woodward W, Strom E, Tucker SL, McNeese MD, Perkins GH, Schechter NR, Singletary SE, Theriault RL, Hortobagyi GN, Hunt KK, Buchholz T (2003) Changes in the 2003 American joint committee on cancer staging for breast cancer dramatically affect stage-specific survival. J Clin Oncol 21(17):324–348
Yamamoto T, Abolhassani N (2012) Augmented reality and haptic interfaces for robot assisted surgery. Int J Med Robot Comput Assist Surg 8:45–56
Yau C (2009) R tutoral eBook. r-tutor.com. http://www.r-tutor.com/elementary-statistics/non-parametric-methods/wilcoxon-signed-rank-test Accessed 20 Mar 2014
Acknowledgments
The research leading to these results has received funding from the National Natural Science Foundation of China (Approval No. 51175412), the China Scholarship Council, the GSTT charity, the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, and the European Commission’s Seventh Framework Programme under grant agreement 287728 in the framework of EU project STIFF-FLOP. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health.
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Li, M., Konstantinova, J., Secco, E.L. et al. Using visual cues to enhance haptic feedback for palpation on virtual model of soft tissue. Med Biol Eng Comput 53, 1177–1186 (2015). https://doi.org/10.1007/s11517-015-1309-4
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DOI: https://doi.org/10.1007/s11517-015-1309-4