An engineered tactile afferent modulation platform to elicit compound sensory nerve action potentials in response to force magnitude

Kim, E. K.; Sugg, KB; Langhals, Nicholas B.; Lightbody, Sarah M.; Baltrusaitis, M. E.; Urbanchek, Melanie G.; Cedema, P. S.; Gerling, Gregory J.

doi:10.1109/whc.2013.6548415

Cited by 11 publications

(12 citation statements)

References 11 publications

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“…If the tactile display can present virtual sensations at the finger pad while the device is located on a different part of the body, users can experience virtual sensations while exploring the texture of real materials. To this end, we focus on the electrotactile sensations evoked by a transcutaneous electrical stimulus [4], [27], [7]. Electrotactile sensations are perceived at the site of the mechanoreceptors rather than at the site of the stimulated nerves [28].…”

Section: Related Workmentioning

confidence: 99%

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Material Roughness Modulation via Electrotactile Augmentation

Yoshimoto

Kuroda

Imura

et al. 2015

IEEE Trans. Haptics

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Tactile exploration of a material's texture using a bare finger pad is a daily human activity. However, modern tactile displays do not allow users to experience the natural sensations of a material when artificial sensations are presented. We propose an electrotactile augmentation technique capable of superimposing vibrotactile sensations in a finger pad, thereby allowing the texture modulation of real materials. Users attach two stimulus electrodes to the middle phalanx of a finger and a grounded electrode at the base of the finger in order to evoke nerve activity. This paper evaluates the proposed electrotactile augmentation for roughness modulation of real materials. First, we introduce the principle of the electrotactile display, which presents artificial sensations at the finger pad. We then confirm that the perceived frequency of mechanical vibration at the finger pad can be shifted using electrotactile augmentation. Finally, we discuss a user study, wherein participants rated the roughness of real materials explored using the proposed system. Experimental results indicate that fine- and macro-roughness perceptions of real materials can be altered using electrotactile augmentation.

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Section: Related Workmentioning

confidence: 99%

“…To solve this problem, we introduce an electrotactile augmentation technique that does not constrain the finger or materials [3]. This technique enables users to experience the real texture and virtual tactile sensations at the finger pad based on transcutaneous electrical stimulation [4], [5], [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Material Roughness Modulation via Electrotactile Augmentation

Yoshimoto

Kuroda

Imura

et al. 2015

IEEE Trans. Haptics

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“…The starting condition, which is not neuromorphic at all but can still be sufficient to convey basic information, is to leave the sensors output unprocessed except for noise filtering and renormalization. Therefore, the neuromorphic approach creates the ground for a natural integration between the artificial sensing system and the natural neural afferent pathways (Kim et al, 2013) and can represent a further advancement of approaches targeting the restoration of a missing sense of touch via neuroprostheses (Raspopovic et al, 2014). Besides making the signal closer to real mechanoreceptors output, this operation drastically reduces the size of the signal at the price of small or no information loss.…”

Section: Neuromorphic Representation Of Tactile Information For Biomimentioning

confidence: 99%

Biomimetic tactile sensing

Dahiya¹,

Oddo²,

Mazzoni³

et al. 2015

Biomimetic Technologies

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What would happen if we had all sense modalities but the "touch?" A simple experiment of manipulating objects after putting hands on an ice block for a moment can probably provide an answer to this question. In one such experiment, the skin on a volunteer's hand was anesthetized so that tactile information from mechanoreceptors-the specialized nerve endings that respond to mechanical stimulation-was no longer available to the brain (Westling and Johannson, 1984). It was observed that even though volunteers could see what they were doing, they could no longer maintain a stable grasp of the objects. This indicates that the movements become inaccurate and unstable in the absence of "sense of touch." The difficulties that humans could face in the absence of sense of touch also point toward the importance of touch sense modality in robots, especially when they are expected to work in a human environment.The touch sensing allows us to assess the size, shape, softness, and texture of objects. It helps us understand the interaction behaviors of the real world objects-which depend on their weight; stiffness; on how their surface feels when touched; how they deform on contact; and how they move when pushed. In applications such as robotics, tactile information is useful in a number of ways. In manipulative tasks, the tactile data are used as a control parameter and the tactile information typically includes contact point estimation, surface normal and curvature measurement, and slip detection (Fearing, 1990;Howe, 1994). A measure of the contact forces (both magnitude and direction) allows the grasp force control-needed to maintain stable grasps. In a real world interaction that involves, both, manipulative and exploratory tasks, the tactile information such as hardness/softness (Shikida et al., 2003), temperature, and vibrations are needed to understand diverse properties of the contacted objects.The need for suitable tactile sensing system in robotics has resulted in a large number of touch sensors and tactile sensing arrays by exploring nearly all modes of transduction, viz., resistive, capacitive, piezoelectric, magnetic, quantum tunneling, etc. (Dahiya et al., 2010b;Lee and Nicholls, 1999;Dahiya and Valle, 2013). Currently, many research groups are also working toward developing skin-like artificial systems for large area tactile sensing. However, the touch sensor technology developed so far is largely insufficient for robotics, even if there is significant success in other areas such as mobile telephony. This could be attributed to a number of factors such as availability of less than satisfactory sensory skins, insufficient methods of processing tactile data, the lack of systems approach, and the lack of mechanical flexibility and robust sensory structures. Often, tactile data are processed with techniques adapted from visual data processing, which may not be a correct approach as the touch sensing is distributed over a much broader area than vision. As a Biomimetic Technologies. http://dx.

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“…This research shows that ad hoc stimulation (linearly relating force magnitude to pulse frequency [9]) can elicit a sensory percept that aligns with the subjective experience of increasing pressure. That said, moving toward a regime of better controlled stimulation is a goal, and there are three practical limitations in electrically stimulating the peripheral nervous system, the: 1) restriction to stimulating the whole nerve (or partial, at least 10 fibers) instead of single fibers due to the nature of nerve to electrode interfaces [16], 2) infeasibility of a long-term closed loop system, whereby one might be able to stimulate and record from the same nerve, which limits validation, and 3) critical need to limit electrical current delivered to the nerve to avoid permanent damage, yet be sufficient to elicit a response. We suggest herein that the next step is to better align both the algorithms and their parameters with neurophysiological processes.…”

Section: Introductionmentioning

confidence: 99%

“…Until recently, electrical stimulation and afferent modeling efforts have traveled parallel, but not intersecting, paths. Works of E. K. Kim and S. Bensmaia both provide a system to transform controlled ramp and hold forces into the timings of when to stimulate the nerve [12,16]. Although this work bridges the gap between electrical stimulation and modeling, the algorithm of Kim is essentially a linear relationship between force and pulse frequency, akin to the ad hoc model of Dhillon.…”

Section: Introductionmentioning

confidence: 99%

An Engineered Tactile Modulation Platform to Recreate Tactile Feedback in Upper-Limb Prostheses

Lightbody

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An engineered tactile afferent modulation platform to elicit compound sensory nerve action potentials in response to force magnitude

Cited by 11 publications

References 11 publications

Material Roughness Modulation via Electrotactile Augmentation

Material Roughness Modulation via Electrotactile Augmentation

Biomimetic tactile sensing

An Engineered Tactile Modulation Platform to Recreate Tactile Feedback in Upper-Limb Prostheses

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