Toward Visualization of Skill in VR: Adaptive Real-Time Guidance for Learning Force Exertion through the "Shaping" Strategy

Rissanen, Mikko J.; Kuroda, Yoshihiro; Nakao, Megumi; Kume, Naoto; Kuroda, Tomohiro; Yoshihara, Hiroyuki

doi:10.1109/whc.2007.117

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…Another example is the haptic and visual playback of expert vertebral palpation by Williams, Srivastava, Conatser, and Howell (2004) where the trainee passively experiences the prerecorded positions of a tactile examination. In another case, Rissanen et al (2007) proposed to use the skills of an expert explicitly in a VTE for the purpose of training force exertion profiles. All of these examples provided to the novice some form of assistance or guidance based on expert performance, yet the expertise was not explicitly defined.…”

Section: Introductionmentioning

confidence: 99%

Expertise-Based Performance Measures in a Virtual Training Environment

Huegel

Çelik²,

Israr³

et al. 2009

Presence: Teleoperators and Virtual Environments

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This paper introduces and validates quantitative performance measures for a rhythmic target-hitting task. These performance measures are derived from a detailed analysis of human performance during a month-long training experiment where participants learned to operate a 2-DOF haptic interface in a virtual environment to execute a manual control task. The motivation for the analysis presented in this paper is to determine measures of participant performance that capture the key skills of the task. This analysis of performance indicates that two quantitative measures-trajectory error and input frequency-capture the key skills of the targethitting task, as the results show a strong correlation between the performance measures and the task objective of maximizing target hits. The performance trends were further explored by grouping the participants based on expertise and examining trends during training in terms of these measures. In future work, these measures will be used as inputs to a haptic guidance scheme that adjusts its control gains based on a real-time assessment of human performance of the task. Such guidance schemes will be incorporated into virtual training environments for humans to develop manual skills for domains such as surgery, physical therapy, and sports.

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Section: Introductionmentioning

confidence: 99%

Expertise-Based Performance Measures in a Virtual Training Environment

Huegel

Çelik²,

Israr³

et al. 2009

Presence: Teleoperators and Virtual Environments

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“…Here note that when many pieces of information are visually displayed to human beings, retention is not as good and the training is not effective. 33 In the proposed method (Method 2), the trainer's and trainee's hand motion images were used instead of the visual cues shown in Fig. 2(a), which shows the trainer's and trainee's fingertips (Method 1), and thus there was the possibility to increase the information displayed to the trainee.…”

Section: Resultsmentioning

confidence: 99%

A finger skill transfer system using a multi-fingered haptic interface robot and a hand motion image

2013

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The teaching of how to exert fingertip forces and how to move the fingers is essential for transferring skill using the fingers to perform fine motor tasks. In this paper we accomplish the transfer of fingertip forces and positions in three-dimensional space by combining a multi-fingered haptic interface robot, which can measure and present the three-dimensional forces and positions at five fingertips, and an image display system that records a trainer's hand image and displays it to a trainee. Several experimental results show a high fingertip force and position transferability and the great potential of our proposed transfer system.

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“…They observed that the users trained with the visuo-haptic modality obtained the best experimental results, and the users in the visual feedback group reproduced the force pattern better than the users of the haptic feedback group. Rissanen et al (2007) demonstrated the use of VR based on visual and haptic feedback to teach experts' force exertion to novices using the "shaping" strategy, which provides information about the power and duration of a force during the training stage.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…This decision was based on 1) previous studies (Hasan, Yano, and Buss, 2008;Morris et al, 2007;Rissanen et al, 2007) that have demonstrated that visual feedback may accelerate and improve the learning of force profiles, and 2) previous studies that have shown that visual feedback contributes to the formation of mental models because it can influence adaptation to a dynamic environment (Rosati et al, 2014).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Learning force patterns with a multimodal system using contextual cues

Rodríguez

Gutiérrez

Portillo

et al. 2018

International Journal of Human-Computer Studies

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Highlights  A new interaction technique based on contextual information using a multimodal system for force pattern learning is proposed. Using the contextual information approach, the trainees obtain information about the evolution of their performance along the time (helping to correct the errors). The findings suggest that the contextual information provides a better trainee's performance than the punctual information. One drawback of the training strategies based on punctual feedback is the difficulty that users have in interpreting the information. The contextual approach could be used to extend the capabilities of haptic training procedures based on haptic guidance to provide information about the level of force to be applied during the execution of a specific task.Abstract -Previous studies on learning force patterns (fine motor skills) have focused on providing "punctual information", which means users only receive information about their performance at the current time step. This work proposes a new approach based on "contextual information", in which users receive information not only about the current time step, but also about the past (how the target force has changed over time) and the future (how the target force will change). A test was run to compare the performance of the contextual approach in relation to the punctual information, in which each participant had to memorize and then reproduce a pattern of force after training with a multimodal system. The findings suggest that the contextual approach is a useful strategy for force pattern learning. The advantage of the contextual information approach over the punctual information approach is that users receive information about the evolution of their performance (helping to correct the errors), and they also receive information about the next forces to be exerted (providing them with a better understanding of the target force profile). Finally, the contextual approach could be implemented in medical training platforms or surgical robots to extend the capabilities of these systems.

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Toward Visualization of Skill in VR: Adaptive Real-Time Guidance for Learning Force Exertion through the "Shaping" Strategy

Cited by 4 publications

References 9 publications

Expertise-Based Performance Measures in a Virtual Training Environment

Expertise-Based Performance Measures in a Virtual Training Environment

A finger skill transfer system using a multi-fingered haptic interface robot and a hand motion image

Learning force patterns with a multimodal system using contextual cues

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