Pub Date : 2023-11-10DOI: 10.1109/TOH.2023.3331032
Yan Zhang;Riting Xia;Xiaoying Sun
Tactile rendering in virtual interactive scenes plays an important role in improving the quality of user experience. The subjective rating is currently the mainstream measurement to assess haptic rendering realism, which ignores various subjective and objective uncertainties in the evaluation process and also neglects the mutual influence among tactile renderings. In this paper, we extend the existing subjective evaluation and systematically propose a fuzzy evaluation method of haptic rendering realism. Hierarchical fuzzy scoring based on confidence interval is introduced to reduce the difficulty of expressing tactile feeling with deterministic rating. After the fuzzy statistics based on the membership function, we further use close-degree and transitive closure to calculate the fuzzy equivalence matrix between different tactile renderings. Fuzzy clustering is carried out to complete the comprehensive evaluation in the case of multiple indicators. Five tactile objects are used to simulate various situations of tactile rendering. The experimental results of haptic perceptual similarity evaluation show the existence of fuzziness in the subjective evaluation and verify the feasibility of the proposed method applied to multi-indicator evaluation. We also conclude that the proposed method outperforms the existing methods in terms of time cost and labor cost.
{"title":"Fuzzy Evaluation Method for Haptic Perceptual Similarity","authors":"Yan Zhang;Riting Xia;Xiaoying Sun","doi":"10.1109/TOH.2023.3331032","DOIUrl":"10.1109/TOH.2023.3331032","url":null,"abstract":"Tactile rendering in virtual interactive scenes plays an important role in improving the quality of user experience. The subjective rating is currently the mainstream measurement to assess haptic rendering realism, which ignores various subjective and objective uncertainties in the evaluation process and also neglects the mutual influence among tactile renderings. In this paper, we extend the existing subjective evaluation and systematically propose a fuzzy evaluation method of haptic rendering realism. Hierarchical fuzzy scoring based on confidence interval is introduced to reduce the difficulty of expressing tactile feeling with deterministic rating. After the fuzzy statistics based on the membership function, we further use close-degree and transitive closure to calculate the fuzzy equivalence matrix between different tactile renderings. Fuzzy clustering is carried out to complete the comprehensive evaluation in the case of multiple indicators. Five tactile objects are used to simulate various situations of tactile rendering. The experimental results of haptic perceptual similarity evaluation show the existence of fuzziness in the subjective evaluation and verify the feasibility of the proposed method applied to multi-indicator evaluation. We also conclude that the proposed method outperforms the existing methods in terms of time cost and labor cost.","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"16 4","pages":"826-835"},"PeriodicalIF":2.9,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72209146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.1109/TOH.2023.3330368
Thomas E. Augenstein;C. David Remy;Edward S. Claflin;Rajiv Ranganathan;Chandramouli Krishnan
Semi-passive rehabilitation robots resist and steer a patient's motion using only controllable passive force elements (e.g., controllable brakes). Contrarily, passive robots use uncontrollable passive force elements (e.g., springs), while active robots use controllable active force elements (e.g., motors). Semi-passive robots can address cost and safety limitations of active robots, but it is unclear if they have utility in rehabilitation. Here, we assessed if a semi-passive robot could provide haptic guidance to facilitate motor learning. We first performed a theoretical analysis of the robot's ability to provide haptic guidance, and then used a prototype to perform a motor learning experiment that tested if the guidance helped participants learn to trace a shape. Unlike prior studies, we minimized the confounding effects of visual feedback during motor learning. Our theoretical analysis showed that our robot produced guidance forces that were, on average, 54 $^circ$