Pub Date : 2023-11-13DOI: 10.1109/TOH.2023.3332402
Qianqian Tian;Jixiao Liu;Kuo Liu;Shijie Guo
The human hand interacts with the environment via physical contact, and tactile information is closely associated with finger movement patterns. Studying the relationship between motor primitives of the finger and the corresponding tactile feedback provides valuable insight into the nature of touch and informs the simulation of humanoid tactile. This research decomposed finger contact into three fundamental motor primitives: contact-on, stick-to-slip, and full slip, then examined the tactile features associated with each motor primitive, including the center of mass (COM) and the centroid of the contact pressure distribution matrix and the total contact area. The change in fingertip contact area during contact-on was in accordance with a first-order kinetic model. In the stick-to-slip, there was a generalized linear relationship between the fingertip skin stretch and the magnitude of the tangential force. Moreover, the skin stretch of the fingertip mirrored the direction of the motion. During the full slip, the COM's movement effectively represented the direction of the tangential force, with an error margin of no more than five degrees. Experiments showed that certain fingertip motions can be portrayed, transmitted, and replicated using tactile information. This research opens potential avenues for remote immersive physical communication in robotics and other related fields.
{"title":"Tactile Features of Human Finger Contact Motor Primitives","authors":"Qianqian Tian;Jixiao Liu;Kuo Liu;Shijie Guo","doi":"10.1109/TOH.2023.3332402","DOIUrl":"10.1109/TOH.2023.3332402","url":null,"abstract":"The human hand interacts with the environment via physical contact, and tactile information is closely associated with finger movement patterns. Studying the relationship between motor primitives of the finger and the corresponding tactile feedback provides valuable insight into the nature of touch and informs the simulation of humanoid tactile. This research decomposed finger contact into three fundamental motor primitives: contact-on, stick-to-slip, and full slip, then examined the tactile features associated with each motor primitive, including the center of mass (COM) and the centroid of the contact pressure distribution matrix and the total contact area. The change in fingertip contact area during contact-on was in accordance with a first-order kinetic model. In the stick-to-slip, there was a generalized linear relationship between the fingertip skin stretch and the magnitude of the tangential force. Moreover, the skin stretch of the fingertip mirrored the direction of the motion. During the full slip, the COM's movement effectively represented the direction of the tangential force, with an error margin of no more than five degrees. Experiments showed that certain fingertip motions can be portrayed, transmitted, and replicated using tactile information. This research opens potential avenues for remote immersive physical communication in robotics and other related fields.","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"16 4","pages":"848-860"},"PeriodicalIF":2.9,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92153751","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 : 2023-11-10DOI: 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 $^circ$