Analysis of Relevant Quality Metrics and Physical Parameters in Softness Perception and Assessment System
Many quality metrics have been proposed for the compliance perception to assess haptic device performance and perceived results. Perceived compliance may be influenced by factors such as object properties, experimental conditions and human perceptual habits. In this paper, analysis of softness perce...
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| Published in | IEICE Transactions on Information and Systems Vol. E102.D; no. 10; pp. 2013 - 2024 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Tokyo
The Institute of Electronics, Information and Communication Engineers
01.10.2019
Japan Science and Technology Agency |
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| Online Access | Get full text |
| ISSN | 0916-8532 1745-1361 1745-1361 |
| DOI | 10.1587/transinf.2018EDP7358 |
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| Abstract | Many quality metrics have been proposed for the compliance perception to assess haptic device performance and perceived results. Perceived compliance may be influenced by factors such as object properties, experimental conditions and human perceptual habits. In this paper, analysis of softness perception was conducted to find out relevant quality metrics dominating in the compliance perception system and their correlation with perception results, by expressing these metrics by basic physical parameters that characterizing these factors. Based on three psychophysical experiments, just noticeable differences (JNDs) for perceived softness of combination of different stiffness coefficients and damping levels rendered by haptic devices were analyzed. Interaction data during the interaction process were recorded and analyzed. Preliminary experimental results show that the discrimination ability of softness perception changes with the ratio of damping to stiffness when subjects exploring at their habitual speed. Analysis results indicate that quality metrics of Rate-hardness, Extended Rate-hardness and ratio of damping to stiffness have high correlation for perceived results. Further analysis results show that parameters that reflecting object properties (stiffness, damping), experimental conditions (force bandwidth) and human perceptual habits (initial speed, maximum force change rate) lead to the change of these quality metrics, which then bring different perceptual feeling and finally result in the change of discrimination ability. Findings in this paper may provide a better understanding of softness perception and useful guidance in improvement of haptic and teleoperation devices. |
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| AbstractList | Many quality metrics have been proposed for the compliance perception to assess haptic device performance and perceived results. Perceived compliance may be influenced by factors such as object properties, experimental conditions and human perceptual habits. In this paper, analysis of softness perception was conducted to find out relevant quality metrics dominating in the compliance perception system and their correlation with perception results, by expressing these metrics by basic physical parameters that characterizing these factors. Based on three psychophysical experiments, just noticeable differences (JNDs) for perceived softness of combination of different stiffness coefficients and damping levels rendered by haptic devices were analyzed. Interaction data during the interaction process were recorded and analyzed. Preliminary experimental results show that the discrimination ability of softness perception changes with the ratio of damping to stiffness when subjects exploring at their habitual speed. Analysis results indicate that quality metrics of Rate-hardness, Extended Rate-hardness and ratio of damping to stiffness have high correlation for perceived results. Further analysis results show that parameters that reflecting object properties (stiffness, damping), experimental conditions (force bandwidth) and human perceptual habits (initial speed, maximum force change rate) lead to the change of these quality metrics, which then bring different perceptual feeling and finally result in the change of discrimination ability. Findings in this paper may provide a better understanding of softness perception and useful guidance in improvement of haptic and teleoperation devices. |
| Author | OUYANG, Qiangqiang WU, Juan SHAO, Zhiyu |
| Author_xml | – sequence: 1 fullname: SHAO, Zhiyu organization: State Key Laboratory for Bioelectronics, Robotic Sensor and Control Laboratory, School of Instrument Science and Engineering, Southeast University – sequence: 1 fullname: WU, Juan organization: State Key Laboratory for Bioelectronics, Robotic Sensor and Control Laboratory, School of Instrument Science and Engineering, Southeast University – sequence: 1 fullname: OUYANG, Qiangqiang organization: State Key Laboratory for Bioelectronics, Robotic Sensor and Control Laboratory, School of Instrument Science and Engineering, Southeast University |
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| Cites_doi | 10.1016/j.automatica.2006.06.027 10.1152/jn.2000.83.4.1777 10.1007/s00221-008-1507-5 10.1016/j.visres.2010.10.005 10.1016/j.arcontrol.2014.03.002 10.3758/BF03194544 10.1007/978-3-540-69057-3_30 10.1007/BF00228884 10.1109/TOH.2016.2567395 10.1007/978-3-642-22950-3_3 10.1109/70.864228 10.1109/TOH.2017.2715845 10.3758/BF03213075 10.1080/17470216408416370 10.1007/978-3-642-14064-8_18 10.1152/jn.1995.73.1.88 10.1109/TOH.2009.16 10.1016/j.automatica.2011.01.004 10.1007/978-3-319-93445-7_32 10.1109/TOH.2010.9 10.1097/SIH.0b013e3181e9e783 10.1177/0278364908099461 10.1038/415429a 10.1145/1643928.1643949 10.1109/VRAIS.1993.378264 |
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| References | [19] M.O. Ernst and M.S. Banks, “Humans integrate visual and haptic information in a statistically optimal fashion,” Nature, vol.415, no.6870, p.429, 2002. 10.1038/415429a [22] E. Karadogan, R.L. Williams, J.N. Howell, R.R. Conatser, Jr, et al., “A stiffness discrimination experiment including analysis of palpation forces and velocities,” Simulation in Healthcare, vol.5, no.5, pp.279-288, 2010. [5] D. Sun, F. Naghdy, and H. Du, “Application of wave-variable control to bilateral teleoperation systems: A survey,” Annual Reviews in Control, vol.38, no.1, pp.12-31, 2014. 10.1016/j.arcontrol.2014.03.002 [3] P.F. Hokayem and M.W. Spong, “Bilateral teleoperation: An historical survey,” Automatica, vol.42, no.12, pp.2035-2057, 2006. 10.1016/j.automatica.2006.06.027 [11] F.K. Freyberger and B. Färber, “Compliance discrimination of deformable objects by squeezing with one and two fingers,” Proc.EuroHaptics, pp.271-276, 2006. [1] W.M. Bergmann Tiest and A.M. Kappers, “Cues for haptic perception of compliance,” IEEE Transactions on Haptics, vol.2, no.4, pp.189-199, 2009. 10.1109/toh.2009.16 [2] W.M. Bergmann Tiest, “Tactual perception of material properties,” Vision research, vol.50, no.24, pp.2775-2782, 2010. 10.1016/j.visres.2010.10.005 [14] F.E. van Beek, D.J. Heck, H. Nijmeijer, W.M. Bergmann Tiest, and A.M. Kappers, “The effect of global and local damping on the perception of hardness,” IEEE Transactions on Haptics, no.3, pp.409-420, 2016. [8] H.Z. Tan, X.D. Pang, N.I. Durlach, et al., “Manual resolution of length, force, and compliance,” Advances in Robotics, vol.42, pp.13-18, 1992. [6] E. Nuño, L. Basañez, R. Ortega, and M.W. Spong, “Position tracking for non-linear teleoperators with variable time delay,” The International Journal of Robotics Research, vol.28, no.7, pp.895-910, 2009. 10.1177/0278364908099461 [9] H.Z. Tan, N.I. Durlach, Y. Shao, and M. Wei, “Manual resolution of compliance when work and force cues are minimized,” ASME Dyn. Syst. Contr. Div. Publ. DSC, vol.49, pp.99-104, 1993. [18] K. Higashi, S. Okamoto, Y. Yamada, H. Nagano, and M. Konyo, “Hardness perception through tapping: peak and impulse of the reaction force reflect the subjective hardness,” International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, pp.366-375, 2018. [21] M. Kuschel, M. Di Luca, M. Buss, and R.L. Klatzky, “Combination and integration in the perception of visual-haptic compliance information,” IEEE Transactions on Haptics, vol.3, no.4, pp.234-244, 2010. 10.1109/toh.2010.9 [24] H.Z. Tan, N.I. Durlach, G.L. Beauregard, and M.A. Srinivasan, “Manual discrimination of compliance using active pinch grasp: The roles of force and work cues,” Perception & psychophysics, vol.57, no.4, pp.495-510, 1995. 10.3758/bf03213075 [17] S.C. Hauser and G.J. Gerling, “Force-rate cues reduce object deformation necessary to discriminate compliances harder than the skin,” IEEE Transactions on Haptics, vol.11, no.2, pp.232-240, 2018. [23] R.H. LaMotte, “Softness discrimination with a tool,” Journal of Neurophysiology, vol.83, no.4, pp.1777-1786, 2000. 10.1152/jn.2000.83.4.1777 [25] L.A. Jones and I.W. Hunter, “A perceptual analysis of stiffness,” Experimental Brain Research, vol.79, no.1, pp.150-156, 1990. 10.1007/bf00228884 [7] R. Harper and S. Stevens, “Subjective hardness of compliant materials,” Quarterly Journal of Experimental Psychology, vol.16, no.3, pp.204-215, 1964. [20] F.A. Wichmann and N.J. Hill, “The psychometric function: I. fitting, sampling, and goodness of fit,” Perception & psychophysics, vol.63, no.8, pp.1293-1313, 2001. 10.3758/bf03194544 [16] G. Han and S. Choi, “Extended rate-hardness: A measure for perceived hardness,” International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, pp.117-124, 2010. [15] D.A. Lawrence, L.Y. Pao, A.M. Dougherty, M.A. Salada, and Y. Pavlou, “Rate-hardness: A new performance metric for haptic interfaces,” IEEE Trans. Robot. Autom., vol.16, no.4, pp.357-371, 2000. 10.1109/70.864228 [29] R.M. Friedman, K.D. Hester, B.G. Green, and R.H. LaMotte, “Magnitude estimation of softness,” Experimental brain research, vol.191, no.2, pp.133-142, 2008. 10.1007/s00221-008-1507-5 [13] W.M. Bergmann Tiest and A.M. Kappers, “Kinaesthetic and cutaneous contributions to the perception of compressibility,” International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, pp.255-264, 2008. [10] U. Koçak, K.L. Palmerius, C. Forsell, A. Ynnerman, and M. Cooper, “Analysis of the jnd of stiffness in three modes of comparison,” International Workshop on Haptic and Audio Interaction Design, pp.22-31, Springer, 2011. 10.1007/978-3-642-22950-3_3 [27] G. Han, S. Jeon, and S. Choi, “Improving perceived hardness of haptic rendering via stiffness shifting: an initial study,” Proc. 16th ACM Symposium on Virtual Reality Software and Technology, pp.87-90, ACM, 2009. 10.1145/1643928.1643949 [4] E. Nuño, L. Basañez, and R. Ortega, “Passivity-based control for bilateral teleoperation: A tutorial,” Automatica, vol.47, no.3, pp.485-495, 2011. 10.1016/j.automatica.2011.01.004 [12] M.A. Srinivasan and R.H. LaMotte, “Tactual discrimination of softness,” Journal of Neurophysiology, vol.73, no.1, pp.88-101, 1995. 10.1152/jn.1995.73.1.88 [28] L.B. Rosenberg and B.D. Adelstein, “Perceptual decomposition of virtual haptic surfaces,” Virtual Reality, 1993. Proceedings., IEEE 1993 Symposium on Research Frontiers in, pp.46-53, IEEE, 1993. 10.1109/vrais.1993.378264 [26] F.K. Freyberger and B. Farber, “Psychophysics and perceiving granularity,” 2006 14th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, pp.387-393, IEEE, 2006. 10.1109/haptic.2006.1627105 22 23 24 25 26 27 28 29 10 11 12 13 14 15 16 17 18 19 1 2 3 4 5 6 7 8 9 20 21 |
| References_xml | – reference: [3] P.F. Hokayem and M.W. Spong, “Bilateral teleoperation: An historical survey,” Automatica, vol.42, no.12, pp.2035-2057, 2006. 10.1016/j.automatica.2006.06.027 – reference: [9] H.Z. Tan, N.I. Durlach, Y. Shao, and M. Wei, “Manual resolution of compliance when work and force cues are minimized,” ASME Dyn. Syst. Contr. Div. Publ. DSC, vol.49, pp.99-104, 1993. – reference: [15] D.A. Lawrence, L.Y. Pao, A.M. Dougherty, M.A. Salada, and Y. Pavlou, “Rate-hardness: A new performance metric for haptic interfaces,” IEEE Trans. Robot. Autom., vol.16, no.4, pp.357-371, 2000. 10.1109/70.864228 – reference: [1] W.M. Bergmann Tiest and A.M. Kappers, “Cues for haptic perception of compliance,” IEEE Transactions on Haptics, vol.2, no.4, pp.189-199, 2009. 10.1109/toh.2009.16 – reference: [16] G. Han and S. Choi, “Extended rate-hardness: A measure for perceived hardness,” International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, pp.117-124, 2010. – reference: [29] R.M. Friedman, K.D. Hester, B.G. Green, and R.H. LaMotte, “Magnitude estimation of softness,” Experimental brain research, vol.191, no.2, pp.133-142, 2008. 10.1007/s00221-008-1507-5 – reference: [22] E. Karadogan, R.L. Williams, J.N. Howell, R.R. Conatser, Jr, et al., “A stiffness discrimination experiment including analysis of palpation forces and velocities,” Simulation in Healthcare, vol.5, no.5, pp.279-288, 2010. – reference: [13] W.M. Bergmann Tiest and A.M. Kappers, “Kinaesthetic and cutaneous contributions to the perception of compressibility,” International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, pp.255-264, 2008. – reference: [11] F.K. Freyberger and B. Färber, “Compliance discrimination of deformable objects by squeezing with one and two fingers,” Proc.EuroHaptics, pp.271-276, 2006. – reference: [18] K. Higashi, S. Okamoto, Y. Yamada, H. Nagano, and M. Konyo, “Hardness perception through tapping: peak and impulse of the reaction force reflect the subjective hardness,” International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, pp.366-375, 2018. – reference: [20] F.A. Wichmann and N.J. Hill, “The psychometric function: I. fitting, sampling, and goodness of fit,” Perception & psychophysics, vol.63, no.8, pp.1293-1313, 2001. 10.3758/bf03194544 – reference: [10] U. Koçak, K.L. Palmerius, C. Forsell, A. Ynnerman, and M. Cooper, “Analysis of the jnd of stiffness in three modes of comparison,” International Workshop on Haptic and Audio Interaction Design, pp.22-31, Springer, 2011. 10.1007/978-3-642-22950-3_3 – reference: [21] M. Kuschel, M. Di Luca, M. Buss, and R.L. Klatzky, “Combination and integration in the perception of visual-haptic compliance information,” IEEE Transactions on Haptics, vol.3, no.4, pp.234-244, 2010. 10.1109/toh.2010.9 – reference: [27] G. Han, S. Jeon, and S. Choi, “Improving perceived hardness of haptic rendering via stiffness shifting: an initial study,” Proc. 16th ACM Symposium on Virtual Reality Software and Technology, pp.87-90, ACM, 2009. 10.1145/1643928.1643949 – reference: [12] M.A. Srinivasan and R.H. LaMotte, “Tactual discrimination of softness,” Journal of Neurophysiology, vol.73, no.1, pp.88-101, 1995. 10.1152/jn.1995.73.1.88 – reference: [4] E. Nuño, L. Basañez, and R. Ortega, “Passivity-based control for bilateral teleoperation: A tutorial,” Automatica, vol.47, no.3, pp.485-495, 2011. 10.1016/j.automatica.2011.01.004 – reference: [8] H.Z. Tan, X.D. Pang, N.I. Durlach, et al., “Manual resolution of length, force, and compliance,” Advances in Robotics, vol.42, pp.13-18, 1992. – reference: [14] F.E. van Beek, D.J. Heck, H. Nijmeijer, W.M. Bergmann Tiest, and A.M. Kappers, “The effect of global and local damping on the perception of hardness,” IEEE Transactions on Haptics, no.3, pp.409-420, 2016. – reference: [5] D. Sun, F. Naghdy, and H. Du, “Application of wave-variable control to bilateral teleoperation systems: A survey,” Annual Reviews in Control, vol.38, no.1, pp.12-31, 2014. 10.1016/j.arcontrol.2014.03.002 – reference: [19] M.O. Ernst and M.S. Banks, “Humans integrate visual and haptic information in a statistically optimal fashion,” Nature, vol.415, no.6870, p.429, 2002. 10.1038/415429a – reference: [7] R. Harper and S. Stevens, “Subjective hardness of compliant materials,” Quarterly Journal of Experimental Psychology, vol.16, no.3, pp.204-215, 1964. – reference: [23] R.H. LaMotte, “Softness discrimination with a tool,” Journal of Neurophysiology, vol.83, no.4, pp.1777-1786, 2000. 10.1152/jn.2000.83.4.1777 – reference: [26] F.K. Freyberger and B. Farber, “Psychophysics and perceiving granularity,” 2006 14th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, pp.387-393, IEEE, 2006. 10.1109/haptic.2006.1627105 – reference: [6] E. Nuño, L. Basañez, R. Ortega, and M.W. Spong, “Position tracking for non-linear teleoperators with variable time delay,” The International Journal of Robotics Research, vol.28, no.7, pp.895-910, 2009. 10.1177/0278364908099461 – reference: [2] W.M. Bergmann Tiest, “Tactual perception of material properties,” Vision research, vol.50, no.24, pp.2775-2782, 2010. 10.1016/j.visres.2010.10.005 – reference: [28] L.B. Rosenberg and B.D. Adelstein, “Perceptual decomposition of virtual haptic surfaces,” Virtual Reality, 1993. Proceedings., IEEE 1993 Symposium on Research Frontiers in, pp.46-53, IEEE, 1993. 10.1109/vrais.1993.378264 – reference: [17] S.C. Hauser and G.J. Gerling, “Force-rate cues reduce object deformation necessary to discriminate compliances harder than the skin,” IEEE Transactions on Haptics, vol.11, no.2, pp.232-240, 2018. – reference: [24] H.Z. Tan, N.I. Durlach, G.L. Beauregard, and M.A. Srinivasan, “Manual discrimination of compliance using active pinch grasp: The roles of force and work cues,” Perception & psychophysics, vol.57, no.4, pp.495-510, 1995. 10.3758/bf03213075 – reference: [25] L.A. Jones and I.W. Hunter, “A perceptual analysis of stiffness,” Experimental Brain Research, vol.79, no.1, pp.150-156, 1990. 10.1007/bf00228884 – ident: 3 doi: 10.1016/j.automatica.2006.06.027 – ident: 23 doi: 10.1152/jn.2000.83.4.1777 – ident: 29 doi: 10.1007/s00221-008-1507-5 – ident: 2 doi: 10.1016/j.visres.2010.10.005 – ident: 5 doi: 10.1016/j.arcontrol.2014.03.002 – ident: 20 doi: 10.3758/BF03194544 – ident: 13 doi: 10.1007/978-3-540-69057-3_30 – ident: 25 doi: 10.1007/BF00228884 – ident: 14 doi: 10.1109/TOH.2016.2567395 – ident: 10 doi: 10.1007/978-3-642-22950-3_3 – ident: 9 – ident: 15 doi: 10.1109/70.864228 – ident: 17 doi: 10.1109/TOH.2017.2715845 – ident: 24 doi: 10.3758/BF03213075 – ident: 7 doi: 10.1080/17470216408416370 – ident: 26 – ident: 16 doi: 10.1007/978-3-642-14064-8_18 – ident: 12 doi: 10.1152/jn.1995.73.1.88 – ident: 1 doi: 10.1109/TOH.2009.16 – ident: 11 – ident: 4 doi: 10.1016/j.automatica.2011.01.004 – ident: 18 doi: 10.1007/978-3-319-93445-7_32 – ident: 21 doi: 10.1109/TOH.2010.9 – ident: 22 doi: 10.1097/SIH.0b013e3181e9e783 – ident: 6 doi: 10.1177/0278364908099461 – ident: 19 doi: 10.1038/415429a – ident: 27 doi: 10.1145/1643928.1643949 – ident: 8 – ident: 28 doi: 10.1109/VRAIS.1993.378264 |
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| SubjectTerms | Compliance Correlation analysis Damping Discrimination Electronic devices haptic rendering device Hardness human-computer interaction Parameters Perception perception model Perceptions physical parameters Physical properties Quality Quality assessment quality metrics Softness softness perception Stiffness coefficients |
| Title | Analysis of Relevant Quality Metrics and Physical Parameters in Softness Perception and Assessment System |
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