The role of auxiliary and referred haptic feedback in myoelectric control

Treadway, Emma; Gillespie, R. Brent; Bolger, Darren; Blank, Amy; O’Malley, Marcia K.; Davis, Alicia J.

doi:10.1109/whc.2015.7177684

Cited by 15 publications

(11 citation statements)

References 10 publications

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“…Given these drawbacks to kinesthetic type haptic feedback systems, our recent work has focused on the development of prototype wearable haptic feedback devices that could, for example, be used to provide sensory information to an amputee [85][86][87][88][89]. These devices use a variety of haptic feedback modalities, including vibration, skin stretch (resulting from shear force on the skin), and pressure to encode haptic information about the state of a prosthetic device.…”

Section: 1mentioning

confidence: 99%

“…In an effort to recreate natural touch sensations for amputees, many methods have been explored [100], ranging from invasive techniques (e.g., peripheral nerve stimulation [111,112]) to noninvasive sensory substitution methods (e.g., encoding grip force, hand/arm configuration, or other information in vibration patterns applied to a user's skin [92,[113][114][115][116][117], stretching of the user's skin [118,119], or pressure/shear forces [87,91,94,120], see Ref. [121] for a review).…”

Section: Conveying Environmentmentioning

confidence: 99%

“…Typically, haptic devices based on sensory substitution are designed as modular devices to be worn on other parts of the user's body [100]. Our own recent work includes several wearable devices, used to provide information about grip force, gripper aperture, and object slip to the user of a prosthesis performing a manipulation task [85][86][87][88][89]. Many of these devices have been shown to help users manipulate objects [85,88,89,100].…”

Section: Conveying Environmentmentioning

confidence: 99%

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A Review of Intent Detection, Arbitration, and Communication Aspects of Shared Control for Physical Human–Robot Interaction

Losey

McDonald

Battaglia

et al. 2018

Applied Mechanics Reviews

255

141

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As robotic devices are applied to problems beyond traditional manufacturing and industrial settings, we find that interaction between robots and humans, especially physical interaction, has become a fast developing field. Consider the application of robotics in healthcare, where we find telerobotic devices in the operating room facilitating dexterous surgical procedures, exoskeletons in the rehabilitation domain as walking aids and upper-limb movement assist devices, and even robotic limbs that are physically integrated with amputees who seek to restore their independence and mobility. In each of these scenarios, the physical coupling between human and robot, often termed physical human robot interaction (pHRI), facilitates new human performance capabilities and creates an opportunity to explore the sharing of task execution and control between humans and robots. In this review, we provide a unifying view of human and robot sharing task execution in scenarios where collaboration and cooperation between the two entities are necessary, and where the physical coupling of human and robot is a vital aspect. We define three key themes that emerge in these shared control scenarios, namely, intent detection, arbitration, and feedback. First, we explore methods for how the coupled pHRI system can detect what the human is trying to do, and how the physical coupling itself can be leveraged to detect intent. Second, once the human intent is known, we explore techniques for sharing and modulating control of the coupled system between robot and human operator. Finally, we survey methods for informing the human operator of the state of the coupled system, or the characteristics of the environment with which the pHRI system is interacting. At the conclusion of the survey, we present two case studies that exemplify shared control in pHRI systems, and specifically highlight the approaches used for the three key themes of intent detection, arbitration, and feedback for applications of upper limb robotic rehabilitation and haptic feedback from a robotic prosthesis for the upper limb.fields. Finally, two case studies from the authors' prior work are described, showing in detail how the framework can be applied in the design of two prototypical pHRI systems.

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Section: 1mentioning

confidence: 99%

Section: Conveying Environmentmentioning

confidence: 99%

Section: Conveying Environmentmentioning

confidence: 99%

See 1 more Smart Citation

A Review of Intent Detection, Arbitration, and Communication Aspects of Shared Control for Physical Human–Robot Interaction

Losey

McDonald

Battaglia

et al. 2018

Applied Mechanics Reviews

255

141

View full text Add to dashboard Cite

show abstract

“…It is mounted on the Proximal Band of the MISSIVE, approximately half an inch above the Vibrotactor Band. The design of the Squeeze Band is based on a similar device developed in the MAHI Lab, the Rice Squeeze Band [21]. The servomotor (HS-485HB, Hitec RCD USA, Inc.) has a maximum torque output of 588 mNm.…”

Section: Radial Squeeze Bandmentioning

confidence: 99%

Conveying language through haptics

Dunkelberger

Sullivan

Bradley

et al. 2018

Proceedings of the 2018 ACM International Symposium on Wearable Computers

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In our daily lives, we rely heavily on our visual and auditory channels to receive information from others. In the case of impairment, or when large amounts of information are already transmitted visually or aurally, alternative methods of communication are needed. A haptic language offers the potential to provide information to a user when visual and auditory channels are unavailable. Previously created haptic languages include deconstructing acoustic signals into features and displaying them through a haptic device, and haptic adaptations of Braille or Morse code; however, these approaches are unintuitive, slow at presenting language, or require a large surface area. We propose using a multi-sensory haptic device called MISSIVE, which can be worn on the upper arm and is capable of producing brief cues, sufficient in quantity to encode the full English phoneme set. We evaluated our approach by teaching subjects a subset of 23 phonemes, and demonstrated an 86% accuracy in a 50 word identification task after 100 minutes of training.

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“…In previous research from members of this research group, Brown et al found no significant improvement with either jointtorque feedback or vibrotactile feedback over no feedback in a grasp-and-lift task with a myoelectric prosthesis [16]. Similarly, no significant improvement in myoelectric control was found for a compensatory tracking task with pressure feedback over visual feedback [17]. Markovic et al showed that there was no significant advantage with a vibrotactile bracelet in a box and blocks task [18].…”

Section: Introductionmentioning

confidence: 97%

Comparison of vibrotactile and joint-torque feedback in a myoelectric upper-limb prosthesis

Thomas

Ung

McGarvey

et al. 2019

Preprint

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Background: Despite the technological advancements in myoelectric prostheses, body-powered prostheses remain a popular choice for amputees, in part due to the natural sensory advantage they provide. Research on haptic feedback in myoelectric prostheses has delivered mixed results. Furthermore, there is limited research comparing various haptic feedback modalities in myoelectric prostheses. In this paper, we present a comparison of the feedback intrinsically present in body-powered prostheses (joint-torque feedback) to a commonly proposed feedback modality for myoelectric prostheses (vibrotactile feedback). In so doing, we seek to understand whether the advantages of kinesthetic feedback present in body-powered prostheses translate to myoelectric prostheses, and whether there are differences between kinesthetic and cutaneous feedback in prosthetic applications. Methods:We developed an experimental testbed that features a cable-driven, voluntary-closing 1-DoF prosthesis, a capstan-driven elbow exoskeleton, and a vibrotactile actuation unit. The system can present grip force to users as either a flexion moment about the elbow or vibration on the wrist. To provide an equal comparison of joint-torque and vibrotactile feedback, a stimulus intensity matching scheme was utilized. Non-amputee participants (n=12) were asked to discriminate objects of varying stiffness with the prosthesis in three conditions: no haptic feedback, vibrotactile feedback, and joint-torque feedback.Results: Results indicate that haptic feedback increased discrimination accuracy over no haptic feedback, but the difference between joint-torque feedback and vibrotactile feedback was not significant. In addition, our results highlight nuanced differences in performance depending on the objects' stiffness, and suggest that participants likely pay less attention to incidental cues with the addition of haptic feedback. Conclusion:Even when haptic feedback is not modality matched to the task, such as in the case of vibrotactile feedback, performance with a myoelectric prosthesis can improve significantly. This implies it is possible to achieve the same benefits with vibrotactile feedback, which is cheaper and easier to implement than other forms of feedback.

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The role of auxiliary and referred haptic feedback in myoelectric control

Cited by 15 publications

References 10 publications

A Review of Intent Detection, Arbitration, and Communication Aspects of Shared Control for Physical Human–Robot Interaction

A Review of Intent Detection, Arbitration, and Communication Aspects of Shared Control for Physical Human–Robot Interaction

Conveying language through haptics

Comparison of vibrotactile and joint-torque feedback in a myoelectric upper-limb prosthesis

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