Non-Invasive, Temporally Discrete Feedback of Object Contact and Release Improves Grasp Control of Closed-Loop Myoelectric Transradial Prostheses

Clemente, Francesco; D’Alonzo, Marco; Controzzi, Marco; Edin, Benoni B.; Cipriani, Christian

doi:10.1109/tnsre.2015.2500586

Cited by 186 publications

(208 citation statements)

References 34 publications

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“…Sensorised thimbles have been placed on the fingers of the upper limb myoelectric prosthesis to provide vibratory sensory feedback to a cuff on the arm, to inform the individual when contact with an object is made and then broken. Five amputees have trialled this, with resulting enhancement of their fine control and manipulation of objects, particularly for fragile objects 31 . Sensory feedback relayed to the peripheral nerves and ultimately to the sensory cortex may provide more precise prosthetic control 32 …”

Section: Applications For Brain–computer Interfacesmentioning

confidence: 99%

Neurobionics and the brain–computer interface: current applications and future horizons

Rosenfeld

Wong

2017

Medical Journal of Australia

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The brain-computer interface (BCI) is an exciting advance in neuroscience and engineering. In a motor BCI, electrical recordings from the motor cortex of paralysed humans are decoded by a computer and used to drive robotic arms or to restore movement in a paralysed hand by stimulating the muscles in the forearm. Simultaneously integrating a BCI with the sensory cortex will further enhance dexterity and fine control. BCIs are also being developed to: provide ambulation for paraplegic patients through controlling robotic exoskeletons; restore vision in people with acquired blindness; detect and control epileptic seizures; and improve control of movement disorders and memory enhancement. High-fidelity connectivity with small groups of neurons requires microelectrode placement in the cerebral cortex. Electrodes placed on the cortical surface are less invasive but produce inferior fidelity. Scalp surface recording using electroencephalography is much less precise. BCI technology is still in an early phase of development and awaits further technical improvements and larger multicentre clinical trials before wider clinical application and impact on the care of people with disabilities. There are also many ethical challenges to explore as this technology evolves.

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Section: Applications For Brain–computer Interfacesmentioning

confidence: 99%

Neurobionics and the brain–computer interface: current applications and future horizons

Rosenfeld

Wong

2017

Medical Journal of Australia

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“…Vibrotactile feedback has also been shown to be useful when operating a myoelectric prosthesis with limited or disturbed vision [11]. In a modified box and blocks task, contact cues displayed with vibration significantly reduced the number of broken blocks handled by transradial amputees [12]. In addition to vibrotactile feedback, other cutaneous haptic modalities such as electrotactile, pressure, and skin stretch have been shown to aid object manipulation performance with a myoelectric prosthesis [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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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“…Sensory feedback can be provided invasively by interfacing directly with the neural structures normally involved in the control (e.g., the afferent nerve fibers) [4]- [7] or noninvasively by stimulating body sites normally not involved in the motor task [8]- [13]. While the first approach holds a potential of eliciting close-to-natural tactile sensations, noninvasive stimulation usually relies on the ability of the individual to learn to correctly interpret the stimuli.…”

Section: Introductionmentioning

confidence: 99%

“…From an engineering perspective, there are two possible ways for addressing this limitation: exploiting a low-bandwidth feedback device [13], [19] or increasing the effective information throughput using multichannel configurations (which requires specific training of subjects to learn how to reinterpret the provided stimuli) [20]. In this work, we propose a new approach based on a simple and intuitive paradigm, which exploits the visual system.…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, because of the intuitiveness of the visual feedback provided, we expected that the participants would readily integrate it into their sensorimotor control of the robotic hand. To reveal such integration, we implemented a well-established protocol used in our previous studies [13], [19] as well as in the literature on adaptation in motor control [24]. We modified, unknowingly to the participants, the way we translated the GF or the GC into visual cues in blocks of catch trials after first training the participants.…”

Section: Introductionmentioning

confidence: 99%

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Humans Can Integrate Augmented Reality Feedback in Their Sensorimotor Control of a Robotic Hand

Clemente

Došen

Lonini

et al. 2017

IEEE Trans. Human-Mach. Syst.

Self Cite

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Abstract-Tactile feedback is pivotal for grasping and manipulation in humans. Providing functionally effective sensory feedback to prostheses users is an open challenge. Past paradigms were mostly based on vibroor electrotactile stimulations. However, the tactile sensitivity on the targeted body parts (usually the forearm) is greatly less than that of the hand/fingertips, restricting the amount of information that can be provided through this channel. Visual feedback is the most investigated technique in motor learning studies, where it showed positive effects in learning both simple and complex tasks; however, it was not exploited in prosthetics due to technological limitations. Here, we investigated if visual information provided in the form of augmented reality (AR) feedback can be integrated by able-bodied participants in their sensorimotor control of a pick-and-lift task while controlling a robotic hand. For this purpose, we provided visual continuous feedback related to grip force and hand closure to the participants. Each variable was mapped to the length of one of the two ellipse axes visualized on the screen of wearable single-eye display AR glasses. We observed changes in behavior when subtle (i.e., not announced to the participants) manipulation of the AR feedback was introduced, which indicated that the participants integrated the artificial feedback within the sensorimotor control of the task. These results demonstrate that it is possible to deliver effective information through AR feedback in a compact and wearable fashion. This feedback modality may be exploited for delivering sensory feedback to amputees in a clinical scenario.

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Non-Invasive, Temporally Discrete Feedback of Object Contact and Release Improves Grasp Control of Closed-Loop Myoelectric Transradial Prostheses

Cited by 186 publications

References 34 publications

Neurobionics and the brain–computer interface: current applications and future horizons

Neurobionics and the brain–computer interface: current applications and future horizons

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

Humans Can Integrate Augmented Reality Feedback in Their Sensorimotor Control of a Robotic Hand

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