Thomas E. Augenstein;C. David Remy;Edward S. Claflin;Rajiv Ranganathan;Chandramouli Krishnan
{"title":"Teaching Motor Skills Without a Motor: A Semi-Passive Robot to Facilitate Learning","authors":"Thomas E. Augenstein;C. David Remy;Edward S. Claflin;Rajiv Ranganathan;Chandramouli Krishnan","doi":"10.1109/TOH.2023.3330368","DOIUrl":null,"url":null,"abstract":"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\n<inline-formula><tex-math>$^\\circ$</tex-math></inline-formula>\n from the current velocity (active devices achieve 90\n<inline-formula><tex-math>$^\\circ$</tex-math></inline-formula>\n). Our motor learning experiment showed, for the first time, that participants who received haptic guidance during training learned to trace the shape more accurately (97.57% error to 52.69%) than those who did not receive guidance (81.83% to 78.18%). These results support the utility of semi-passive robots in rehabilitation.","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"17 3","pages":"346-359"},"PeriodicalIF":2.4000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Haptics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10313077/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 0
Abstract
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
$^\circ$
from the current velocity (active devices achieve 90
$^\circ$
). Our motor learning experiment showed, for the first time, that participants who received haptic guidance during training learned to trace the shape more accurately (97.57% error to 52.69%) than those who did not receive guidance (81.83% to 78.18%). These results support the utility of semi-passive robots in rehabilitation.
期刊介绍:
IEEE Transactions on Haptics (ToH) is a scholarly archival journal that addresses the science, technology, and applications associated with information acquisition and object manipulation through touch. Haptic interactions relevant to this journal include all aspects of manual exploration and manipulation of objects by humans, machines and interactions between the two, performed in real, virtual, teleoperated or networked environments. Research areas of relevance to this publication include, but are not limited to, the following topics: Human haptic and multi-sensory perception and action, Aspects of motor control that explicitly pertain to human haptics, Haptic interactions via passive or active tools and machines, Devices that sense, enable, or create haptic interactions locally or at a distance, Haptic rendering and its association with graphic and auditory rendering in virtual reality, Algorithms, controls, and dynamics of haptic devices, users, and interactions between the two, Human-machine performance and safety with haptic feedback, Haptics in the context of human-computer interactions, Systems and networks using haptic devices and interactions, including multi-modal feedback, Application of the above, for example in areas such as education, rehabilitation, medicine, computer-aided design, skills training, computer games, driver controls, simulation, and visualization.