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首页> 外文学位 >Adaptive Haptic Forces in a Virtual Environment Improve Fine Motor Skill Training.
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Adaptive Haptic Forces in a Virtual Environment Improve Fine Motor Skill Training.

机译：虚拟环境中的自适应触觉力可改善精细的运动技能训练。

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摘要

Investigations of technological interventions to retrain motor skills using haptic control have included techniques that guide the patient (e.g., virtual fixtures) or challenge the patient (e.g., error amplification). Virtual fixtures are force fields or channels presented by a haptic device that prevent participants from deviating from a defined path based on expert performance. Error amplification increases the magnitude of errors when participants deviate from the desired path; that is, haptic forces are applied away from the desired path when errors occur.;Other training systems have incorporated adaptive aiding with haptic guidance. With adaptive aiding the intensity of virtual fixtures is modified (decreased) as operator performance improves. There is evidence that providing guidance when needed is more effective than a constant or fixed amount of assistance. Although haptic guidance has been found to enhance performance when engaged, it may not accelerate learning. To date, studies on learning effects of haptic guidance have not included adaptive aiding and haptic control using error amplification.;This research prototyped and evaluated a system that combined error amplification with adaptive aiding to determine the extent to which performance in a progressive error amplification condition transfers to an unassisted condition (i.e., a measure of skill learning). Data collection included two phases, including: (1) unassisted drawing with a haptic device; and (2) drawing with a form of haptic guidance. In both phases participants were trained to draw a series of letter-like designs (letters from a foreign alphabet) with the non-dominant hand. Phase 1 was used to determine learning rates for participants drawing the letters without guidance in order to inform adaptive aiding schedules for Phase 2. In Phase 2, each participant received one of four forms of haptic guidance, including adaptive virtual fixtures, static virtual fixtures, adaptive error amplification or static error amplification (following a between-subjects experiment design). As participant performance improved under adaptive conditions, haptic aiding was modified; virtual fixtures were reduced and error amplification was increased. Improvements were measured objectively with comparisons of motion trajectories to a template (accuracy) and task time (speed). An unassisted test was presented after multiple training sessions. Performance was compared among the four guidance conditions to determine how training with virtual fixtures compared to error amplification with and without adaptive aiding, once haptic guidance is no longer engaged.;Results of the study were mixed. Task accuracy when training with virtual fixtures was greater than the error amplification condition, but improved virtual fixture accuracy did not transfer to the test scenario. Test accuracy following error amplification training was greater. However, task speed improvements were higher for virtual fixtures than error amplification. The error amplification condition provided more constant feedback, which caused participants to more frequently evaluate their progress, especially at greater difficulty levels.;These findings are expected to advance the design of VR systems for fine motor skill training. Future writing tutors as well as training programs for occupational domains where fine motor skills are required could benefit. Low level performance and learning data from the experiment could be used as a basis for developing a motor capability classification algorithm that could quickly assess a person's level of fine motor skill. This algorithm could be used in healthcare for determining appropriate therapy regimens for people recovering from impairment or in industry for identifying training levels for jobs requiring fine motor control.
机译：使用触觉控制来重新训练运动技能的技术干预措施的研究包括指导患者（例如虚拟设备）或挑战患者（例如错误放大）的技术。虚拟固定装置是触觉设备提供的力场或通道，可防止参与者基于专家的表现偏离定义的路径。当参与者偏离期望的路径时，误差放大会增加误差的幅度。也就是说，当发生错误时，触觉力会从所需的路径上移开。其他训练系统已将自适应辅助与触觉引导相结合。借助自适应辅助，随着操作员性能的提高，虚拟固定装置的强度得以修改（降低）。有证据表明，在需要时提供指导要比固定或固定数量的援助更为有效。尽管已经发现触觉指导可以提高参与时的表现，但它可能不会加速学习。迄今为止，关于触觉指导的学习效果的研究还没有包括使用误差放大的自适应辅助和触觉控制。;本研究对系统进行了原型设计和评估，该系统将误差放大与自适应辅助相结合来确定渐进误差放大条件下的表现程度转移到无助的状态（即某种程度的技能学习）。数据收集包括两个阶段，包括：（1）使用触觉设备进行辅助绘制； （2）以触觉引导的形式绘制。在两个阶段中，参与者都接受了用非优势手绘制一系列类似字母的设计（来自外国字母的字母）的培训。第1阶段用于确定没有指导的情况下绘制字母的参与者的学习率，以告知第2阶段的自适应帮助时间表。在第2阶段，每个参与者都收到了四种形式的触觉指导中的一种，包括自适应虚拟固定装置，静态虚拟固定装置，自适应误差放大或静态误差放大（遵循对象间实验设计）。随着参与者在适应性条件下的表现提高，触觉帮助也得到了改进；虚拟夹具减少了，误差放大增加了。通过比较运动轨迹与模板（准确性）和任务时间（速度）的比较来客观地衡量改善情况。经过多次培训后，提出了一项无辅助测试。在四个指导条件下的性能进行了比较，以确定一旦不再使用触觉指导时，使用虚拟固定装置进行的训练与有或没有自适应辅助的情况下的误差放大之间的关系。使用虚拟固定装置进行训练时的任务准确性高于误差放大条件，但提高的虚拟固定装置准确性并未转移到测试方案中。误差放大训练后的测试准确性更高。但是，虚拟设备的任务速度提高比错误放大更高。错误放大条件提供了更恒定的反馈，这使得参与者更加频繁地评估他们的进度，尤其是在更高的难度级别上。这些发现有望促进用于精细运动技能训练的VR系统的设计。将来的写作导师以及针对需要精细运动技能的职业领域的培训计划可能会有所帮助。低水平的性能和来自实验的学习数据可以用作开发运动能力分类算法的基础，该算法可以快速评估一个人的精细运动技能水平。该算法可用于医疗保健中，以确定适合从损伤中恢复的人们的治疗方案，或用于工业中，确定需要精细运动控制的工作的培训水平。

著录项

  • 作者

    Clamann, Michael.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Engineering Industrial.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 129 p.
  • 总页数 129
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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