Pub Date : 2024-05-10DOI: 10.1109/TOH.2024.3399394
Elisabet Henell, Judith Weda, Sophia Cedermalm, Linnea Eklov, Marta Hakansson, Jesper Nordstrom, Marit Reibring, Jonas Stalhand, Nils-Krister Persson, Angelika Mader, Jan B F van Erp, Edwin W H Jager
To design complex wearable haptic interfaces using pressure, we have to explore how we can use pressure stimuli to their full potential. Haptic illusions, such as apparent motion and apparent location, can be a part of this. If these illusions can be evoked with pressure, haptic patterns can increase in complexity without increasing the number of actuators or combining different types of actuators. We did two psychophysical experiments with pressure stimuli on the forearm using a pneumatic sleeve with multiple, individually controlled McKibben actuators. In Experiment 1, we found that spatial integration of two simultaneously presented stimuli occurred for distances up to 61 mm. In Experiment 2, we found that apparent motion can be elicited with distinct pressure stimuli over a range of temporal parameters. These results clearly show spatio-temporal integration in the somatosensory system for pressure stimuli. We discuss these findings in relation to effects found for vibration and the mechanoreceptors in the glabrous skin.
{"title":"Pressure Stimuli and Spatiotemporal Illusions on the Forearm.","authors":"Elisabet Henell, Judith Weda, Sophia Cedermalm, Linnea Eklov, Marta Hakansson, Jesper Nordstrom, Marit Reibring, Jonas Stalhand, Nils-Krister Persson, Angelika Mader, Jan B F van Erp, Edwin W H Jager","doi":"10.1109/TOH.2024.3399394","DOIUrl":"https://doi.org/10.1109/TOH.2024.3399394","url":null,"abstract":"<p><p>To design complex wearable haptic interfaces using pressure, we have to explore how we can use pressure stimuli to their full potential. Haptic illusions, such as apparent motion and apparent location, can be a part of this. If these illusions can be evoked with pressure, haptic patterns can increase in complexity without increasing the number of actuators or combining different types of actuators. We did two psychophysical experiments with pressure stimuli on the forearm using a pneumatic sleeve with multiple, individually controlled McKibben actuators. In Experiment 1, we found that spatial integration of two simultaneously presented stimuli occurred for distances up to 61 mm. In Experiment 2, we found that apparent motion can be elicited with distinct pressure stimuli over a range of temporal parameters. These results clearly show spatio-temporal integration in the somatosensory system for pressure stimuli. We discuss these findings in relation to effects found for vibration and the mechanoreceptors in the glabrous skin.</p>","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"PP ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140903992","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 : 2024-04-08DOI: 10.1109/toh.2024.3385294
Astrid M. L. Kappers, Marloes P. A. van der Burgt, Savannah M. Nowak, Fabiènne P. van der Weide, Wouter K. Vos, Myrthe A. Plaisier
{"title":"Influence of Back Length on Vibrotactile Acuity in Vertical Direction","authors":"Astrid M. L. Kappers, Marloes P. A. van der Burgt, Savannah M. Nowak, Fabiènne P. van der Weide, Wouter K. Vos, Myrthe A. Plaisier","doi":"10.1109/toh.2024.3385294","DOIUrl":"https://doi.org/10.1109/toh.2024.3385294","url":null,"abstract":"","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"246 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140572828","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 : 2024-04-08DOI: 10.1109/toh.2024.3386199
Takuya Noto, Takuto Nakamura, Tomohiro Amemiya
{"title":"Synergistic Illusions: Enhancing Perceptual Effects of Pseudo-Attraction Force by Kinesthetic Illusory Hand Movement","authors":"Takuya Noto, Takuto Nakamura, Tomohiro Amemiya","doi":"10.1109/toh.2024.3386199","DOIUrl":"https://doi.org/10.1109/toh.2024.3386199","url":null,"abstract":"","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"21 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140572839","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 : 2024-04-03DOI: 10.1109/toh.2024.3384482
Catie Cuan, Allison Okamura, Mohi Khansari
{"title":"Leveraging Haptic Feedback to Improve Data Quality and Quantity for Deep Imitation Learning Models","authors":"Catie Cuan, Allison Okamura, Mohi Khansari","doi":"10.1109/toh.2024.3384482","DOIUrl":"https://doi.org/10.1109/toh.2024.3384482","url":null,"abstract":"","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"8 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140573009","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 : 2024-03-27DOI: 10.1109/TOH.2024.3382258
Negin Heravi, Heather Culbertson, Allison M Okamura, Jeannette Bohg
Current Virtual Reality (VR) environments lack the haptic signals that humans experience during real-life interactions, such as the sensation of texture during lateral movement on a surface. Adding realistic haptic textures to VR environments requires a model that generalizes to variations of a user's interaction and to the wide variety of existing textures in the world. Current methodologies for haptic texture rendering exist, but they usually develop one model per texture, resulting in low scalability. We present a deep learning-based action-conditional model for haptic texture rendering and evaluate its perceptual performance in rendering realistic texture vibrations through a multi-part human user study. This model is unified over all materials and uses data from a vision-based tactile sensor (GelSight) to render the appropriate surface conditioned on the user's action in real-time. For rendering texture, we use a high-bandwidth vibrotactile transducer attached to a 3D Systems Touch device. The results of our user study shows that our learning-based method creates high-frequency texture renderings with comparable or better quality than state-of-the-art methods without the need to learn a separate model per texture. Furthermore, we show that the method is capable of rendering previously unseen textures using a single GelSight image of their surface.
当前的虚拟现实(VR)环境缺乏人类在现实生活交互过程中体验到的触觉信号,例如在表面上横向移动时的纹理感。要在 VR 环境中添加逼真的触觉纹理,就需要建立一个模型,以适应用户交互的各种变化和世界上现有的各种纹理。目前已有用于触觉纹理渲染的方法,但它们通常为每种纹理开发一个模型,导致可扩展性较低。我们为触觉纹理渲染提出了一种基于深度学习的动作条件模型,并通过多部分人类用户研究评估了该模型在渲染逼真纹理振动时的感知性能。该模型对所有材料进行了统一,并使用来自视觉触觉传感器(GelSight)的数据,根据用户的动作实时渲染适当的表面。为了渲染纹理,我们使用了一个连接在 3D Systems Touch 设备上的高带宽振动触觉传感器。用户研究结果表明,我们基于学习的方法创建的高频纹理渲染质量可与最先进的方法媲美,甚至更好,而无需为每种纹理学习单独的模型。此外,我们还展示了该方法能够使用单一的 GelSight 纹理表面图像渲染以前未见过的纹理。
{"title":"Development and Evaluation of a Learning-based Model for Real-time Haptic Texture Rendering.","authors":"Negin Heravi, Heather Culbertson, Allison M Okamura, Jeannette Bohg","doi":"10.1109/TOH.2024.3382258","DOIUrl":"https://doi.org/10.1109/TOH.2024.3382258","url":null,"abstract":"<p><p>Current Virtual Reality (VR) environments lack the haptic signals that humans experience during real-life interactions, such as the sensation of texture during lateral movement on a surface. Adding realistic haptic textures to VR environments requires a model that generalizes to variations of a user's interaction and to the wide variety of existing textures in the world. Current methodologies for haptic texture rendering exist, but they usually develop one model per texture, resulting in low scalability. We present a deep learning-based action-conditional model for haptic texture rendering and evaluate its perceptual performance in rendering realistic texture vibrations through a multi-part human user study. This model is unified over all materials and uses data from a vision-based tactile sensor (GelSight) to render the appropriate surface conditioned on the user's action in real-time. For rendering texture, we use a high-bandwidth vibrotactile transducer attached to a 3D Systems Touch device. The results of our user study shows that our learning-based method creates high-frequency texture renderings with comparable or better quality than state-of-the-art methods without the need to learn a separate model per texture. Furthermore, we show that the method is capable of rendering previously unseen textures using a single GelSight image of their surface.</p>","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"PP ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140305448","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}
Auditory and visual cues have been efficacious in laboratory-based freezing of gait (FoG) mitigation in Parkinson's disease (PD). However, real-life applications of these cues are restricted due to inconvenience to the users. Closed-loop vibrotactile cues based on temporal gait events have overcome the shortcomings of auditory and visual cueing. However, kinematic gait parameter-driven vibrotactile cueing has not been explored yet. Kinematic gait parameter-driven cueing is more effective than temporal cueing, according to FoG pathophysiology studies. Therefore, we developed and pilot-tested a novel cueing scheme in which the foot-to-ground angle at heel strike (FGA_HS) is estimated using indigenous instrumented shoes to drive vibrotactile cueing. Ten PD freezers underwent a 6-meter timed walk test in the off-medication state with and without the cue and after medication without the cue. The proposed system potentially mitigated FoG, quantified by a reduction in the ratio of time spent freezing to the total walking time and the number of FoGs. The FoG mitigation potential of the cue was further supported by increased anteroposterior center of pressure progression and FGA_HS. With a future comprehensive validation in a larger number of participants, the novel cue could likely be used in practice and commercialized.
在基于实验室的帕金森病(PD)步态冻结(FoG)缓解中,听觉和视觉提示非常有效。然而,由于给使用者带来不便,这些提示在现实生活中的应用受到了限制。基于时间步态事件的闭环振动触觉线索克服了听觉和视觉线索的缺点。然而,运动步态参数驱动的振动触觉提示尚未得到探索。根据 FoG 病理生理学研究,运动步态参数驱动的提示比时间提示更有效。因此,我们开发并试点测试了一种新颖的提示方案,即使用本土仪器鞋估算脚跟着地时的脚与地夹角(FGA_HS)来驱动振动触觉提示。十名患有帕金森氏症的冷冻患者在未服药状态下接受了 6 米定时步行测试,在服药后有无提示,以及服药后有无提示。所提议的系统可减轻 FoG,具体表现为减少冻结时间与总步行时间的比率以及 FoG 的次数。前胸中心压力进展和 FGA_HS 的增加进一步证明了该提示系统具有减轻 FoG 的潜力。如果将来在更多参与者中进行全面验证,这种新型提示很可能会被用于实践并实现商业化。
{"title":"A Novel Kinematic Gait Parameter-Based Vibrotactile Cue for Freezing of Gait Mitigation among Parkinson's Patients: A Pilot Study.","authors":"Rohan Khatavkar, Ashutosh Tiwari, Priyanka Bhat, Achal Kumar Srivastava, S Senthil Kumaran, Deepak Joshi","doi":"10.1109/TOH.2024.3378917","DOIUrl":"https://doi.org/10.1109/TOH.2024.3378917","url":null,"abstract":"<p><p>Auditory and visual cues have been efficacious in laboratory-based freezing of gait (FoG) mitigation in Parkinson's disease (PD). However, real-life applications of these cues are restricted due to inconvenience to the users. Closed-loop vibrotactile cues based on temporal gait events have overcome the shortcomings of auditory and visual cueing. However, kinematic gait parameter-driven vibrotactile cueing has not been explored yet. Kinematic gait parameter-driven cueing is more effective than temporal cueing, according to FoG pathophysiology studies. Therefore, we developed and pilot-tested a novel cueing scheme in which the foot-to-ground angle at heel strike (FGA_HS) is estimated using indigenous instrumented shoes to drive vibrotactile cueing. Ten PD freezers underwent a 6-meter timed walk test in the off-medication state with and without the cue and after medication without the cue. The proposed system potentially mitigated FoG, quantified by a reduction in the ratio of time spent freezing to the total walking time and the number of FoGs. The FoG mitigation potential of the cue was further supported by increased anteroposterior center of pressure progression and FGA_HS. With a future comprehensive validation in a larger number of participants, the novel cue could likely be used in practice and commercialized.</p>","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"PP ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140287335","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 : 2024-03-25DOI: 10.1109/TOH.2024.3381336
Erick Jimenez-Gonzalez, Chen Avraham, Asya Mikhaylov, Simona Bar-Haim, Ilana Nisky
Haptic devices are becoming popular in many applications, including medical, gaming, and consumer devices. Yet, the majority of studies focus on the use of haptics for the upper limbs, with much less attention to the stimulation of other regions of the body such as the lower back. In this study, we designed three types of skin stretch stimulation devices that can be placed on a belt and apply tactile stimulation on the lower back. We present these devices that apply lateral, longitudinal, and rotational skin stretch stimulation on the lower back, and evaluate their effectiveness in providing haptic commands for the lower limbs of healthy participants. We designed psychophysical experiments that quantify the discrimination accuracy of participants with a stepping task. The results demonstrate the ability of participants to discriminate two out of three features of stimulation provided on the lower back. These results demonstrate that skin stretch on the lower back can effectively transmit haptic signals and elicit responses in the lower limb for various applications. Future studies are needed to optimize providing skin stretch on the lower back to benefit various applications such as training, rehabilitation, gaming, and assistive devices.
{"title":"Providing Skin Stretch On The Lower Back - Design And Psychophysical Evaluation With A Stepping Task.","authors":"Erick Jimenez-Gonzalez, Chen Avraham, Asya Mikhaylov, Simona Bar-Haim, Ilana Nisky","doi":"10.1109/TOH.2024.3381336","DOIUrl":"https://doi.org/10.1109/TOH.2024.3381336","url":null,"abstract":"<p><p>Haptic devices are becoming popular in many applications, including medical, gaming, and consumer devices. Yet, the majority of studies focus on the use of haptics for the upper limbs, with much less attention to the stimulation of other regions of the body such as the lower back. In this study, we designed three types of skin stretch stimulation devices that can be placed on a belt and apply tactile stimulation on the lower back. We present these devices that apply lateral, longitudinal, and rotational skin stretch stimulation on the lower back, and evaluate their effectiveness in providing haptic commands for the lower limbs of healthy participants. We designed psychophysical experiments that quantify the discrimination accuracy of participants with a stepping task. The results demonstrate the ability of participants to discriminate two out of three features of stimulation provided on the lower back. These results demonstrate that skin stretch on the lower back can effectively transmit haptic signals and elicit responses in the lower limb for various applications. Future studies are needed to optimize providing skin stretch on the lower back to benefit various applications such as training, rehabilitation, gaming, and assistive devices.</p>","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"PP ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140287336","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 : 2024-03-20DOI: 10.1109/TOH.2024.3375295
Cheng Huang, Shuang Ji, Zhenlei Chen, Tianyi Sun, Qing Guo, Yao Yan
This paper proposed linear and non-linear models for predicting human-exoskeleton coupling forces to enhance the studies of human-exoskeleton coupling dynamics. Then the parameters of these models were identified with a newly designed platform and the help of ten adult male and ten adult female volunteers (Age: 23.65 ±4.03 years, Height: 165.60 ±8.32 mm, Weight: 62.35 ±14.09 kg). Comparing the coupling force error predicted by the models with experimental measurements, one obtained a more accurate and robust prediction of the coupling forces with the non-linear model. Moreover, statistical analysis of the experimental data was performed to reveal the correlation between the coupling parameters and coupling positions and looseness. Finally, backpropagation (BP) neural network and Gaussian Process Regression (GPR) were used to predict the human-exoskeleton coupling parameters. The significance of each input parameter to the human-exoskeleton coupling parameters was assessed by analyzing the sensitivity of GPR performance to its inputs. The novelty and contribution are the establishment of the non-linear coupling model, the design of the coupling experimental platform and a regression model which provides a possibility to obtain human-exoskeleton without experimental measurement and identification. Based on this work, one can optimize control algorithm and design comfortable human-exoskeleton interaction.
{"title":"Identification and Analysis of Human-Exoskeleton Coupling Parameters in Lower Extremities.","authors":"Cheng Huang, Shuang Ji, Zhenlei Chen, Tianyi Sun, Qing Guo, Yao Yan","doi":"10.1109/TOH.2024.3375295","DOIUrl":"10.1109/TOH.2024.3375295","url":null,"abstract":"<p><p>This paper proposed linear and non-linear models for predicting human-exoskeleton coupling forces to enhance the studies of human-exoskeleton coupling dynamics. Then the parameters of these models were identified with a newly designed platform and the help of ten adult male and ten adult female volunteers (Age: 23.65 ±4.03 years, Height: 165.60 ±8.32 mm, Weight: 62.35 ±14.09 kg). Comparing the coupling force error predicted by the models with experimental measurements, one obtained a more accurate and robust prediction of the coupling forces with the non-linear model. Moreover, statistical analysis of the experimental data was performed to reveal the correlation between the coupling parameters and coupling positions and looseness. Finally, backpropagation (BP) neural network and Gaussian Process Regression (GPR) were used to predict the human-exoskeleton coupling parameters. The significance of each input parameter to the human-exoskeleton coupling parameters was assessed by analyzing the sensitivity of GPR performance to its inputs. The novelty and contribution are the establishment of the non-linear coupling model, the design of the coupling experimental platform and a regression model which provides a possibility to obtain human-exoskeleton without experimental measurement and identification. Based on this work, one can optimize control algorithm and design comfortable human-exoskeleton interaction.</p>","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"PP ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140174499","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 : 2024-03-19DOI: 10.1109/toh.2024.3379035
Erica L. Waters, Michelle J. Johnson
{"title":"Motor Learning in Robot-Based Haptic Dyads: A Review","authors":"Erica L. Waters, Michelle J. Johnson","doi":"10.1109/toh.2024.3379035","DOIUrl":"https://doi.org/10.1109/toh.2024.3379035","url":null,"abstract":"","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"51 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168231","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 : 2024-03-13DOI: 10.1109/TOH.2024.3375010
Barontini F, Catalano M G, Fani S, Grioli G, Bianchi M, Bicchi A
This paper outlines the design, characterization, and validation of a novel wearable haptic device capable of delivering skin stretch, force feedback, or a combination of both, to the user's arm. In this study, we conducted physical and perceptual characterization with eleven able-bodied participants, and two separate experiments involving discrimination and manipulation tasks, encompassing a total of 32 participants. In both experiments, we used the CUFF device in conjunction with the Pisa/IIT SoftHand. The first experiment was a discrimination task in which participants were required to differentiate between pairs of cylinders based on their dimensions and perceived softness. The second experiment called for participants to control the robotic hand in order to grasp objects. Following the experiments, participants provided a subjective evaluation of the device. The results from the experiments and the participants' feedback underscored the effectiveness of the proposed device. Thanks to its versatility and structural design, the device shows promise as a viable solution for a variety of applications, including teleoperation, guidance, rehabilitation tasks, and prosthetic applications.
{"title":"The CUFF, Clenching Upper-Limb Force Feedback Wearable Device: Design, Characterization and Validation.","authors":"Barontini F, Catalano M G, Fani S, Grioli G, Bianchi M, Bicchi A","doi":"10.1109/TOH.2024.3375010","DOIUrl":"https://doi.org/10.1109/TOH.2024.3375010","url":null,"abstract":"<p><p>This paper outlines the design, characterization, and validation of a novel wearable haptic device capable of delivering skin stretch, force feedback, or a combination of both, to the user's arm. In this study, we conducted physical and perceptual characterization with eleven able-bodied participants, and two separate experiments involving discrimination and manipulation tasks, encompassing a total of 32 participants. In both experiments, we used the CUFF device in conjunction with the Pisa/IIT SoftHand. The first experiment was a discrimination task in which participants were required to differentiate between pairs of cylinders based on their dimensions and perceived softness. The second experiment called for participants to control the robotic hand in order to grasp objects. Following the experiments, participants provided a subjective evaluation of the device. The results from the experiments and the participants' feedback underscored the effectiveness of the proposed device. Thanks to its versatility and structural design, the device shows promise as a viable solution for a variety of applications, including teleoperation, guidance, rehabilitation tasks, and prosthetic applications.</p>","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"PP ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140119345","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}