Dynamic Lumped Element Response of the Human Fingerpad

Pawluk, Dianne T. V.; Howe, Robert D.

doi:10.1115/1.2835100

Cited by 133 publications

(91 citation statements)

References 8 publications

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“…The finger is a soft, highly deformable object which, besides its complex detailed geometry, exhibits several types of nonlinearities that are manifest at different length scales of interaction with surfaces [16], [17], [18], [19], [20]. Even under the extremely simplified assumption of linear viscoelasticity and perfectly clean contacts free of foreign bodies and liquids, the contact of deformable bodies with rough surfaces gives rise to theories of considerable complexity that are unlikely to yield simple interaction models [21].…”

Section: Introductionmentioning

confidence: 99%

The Spatial Spectrum of Tangential Skin Displacement Can Encode Tactual Texture

2011

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Abstract-The tactual scanning of five naturalistic textures was recorded with an apparatus capable of measuring the tangential interaction force with a high degree of temporal and spatial resolution. The resulting signal showed that the transformation from the geometry of a surface to the force of traction, and hence to the skin deformation experienced by a finger is a highly nonlinear process. Participants were asked to identify simulated textures reproduced by stimulating their fingers with rapid, imposed lateral skin displacements as a function of net position. They performed the identification task with a high degree of success, yet not perfectly. The fact that the experimental conditions eliminated many aspects of the interaction, including low-frequency finger deformation, distributed information, as well as normal skin movements, shows that the nervous system is able to rely on only two cues: amplitude and spectral information. The examination of the "spatial spectrograms" of the imposed lateral skin displacement revealed that texture could be represented spatially despite being sensed through time and that these spectrograms were distinctively organized into what could be called "spatial formants". This finding led us to speculate that the mechanical properties of the finger enables spatial information to be used for perceptual purposes in humans without any distributed sensing, a principle that could be applied to robots.

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Section: Introductionmentioning

confidence: 99%

The Spatial Spectrum of Tangential Skin Displacement Can Encode Tactual Texture

2011

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“…The springs were etched from copper-beryllium sheets 0.13-mm thick and have a combined spring constant of 0.306 N/mm. When the skin is indented over an area approximately equivalent to that of 300 probes, the measured skin stiffness is 3.5 N/mm (Pawluk and Howe, 1999). Thus, the springs of the motors are approximately 25 times stiffer than the skin (91.8 N/mm for 300 probes versus 3.5 N/mm for an equivalent area of skin).…”

Section: Motor Descriptionmentioning

confidence: 99%

A dense array stimulator to generate arbitrary spatio-temporal tactile stimuli

Killebrew

Bensmaı̈a

Dammann

et al. 2007

Journal of Neuroscience Methods

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The generation and presentation of tactile stimuli presents a unique challenge. Unlike vision and audition, in which standard equipment such as monitors and audio systems can be used for most experiments, tactile stimuli and/or stimulators often have to be tailor-made for a given study. Here, we present a novel tactile stimulator designed to present arbitrary spatio-temporal stimuli to the skin. The stimulator consists of 400 pins, arrayed over a 1 cm 2 area, each under independent computer control. The dense array allows for an unprecedented number of stimuli to be presented within an experimental session (e.g., up to 1200 stimuli per minute) and for stimuli to be generated adaptively. The stimulator can be used in a variety of modes and can deliver indented and scanned patterns as well as stimuli defined by mathematical spatio-temporal functions (e.g., drifting sinusoids). We describe the hardware and software of the system, and discuss previous and prospective applications.

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“…CT and MRI scans currently being collected will provide the necessary geometric detail to model the bones and soft tissue of the hand. We will also use published experimentally derived models of viscoelastic properties of the finger pads to accurately simulate these deformations [21,28].…”

Section: Modeling the Human Handmentioning

confidence: 99%

From robotic hands to human hands: a visualization and simulation engine for grasping research

Miller

Allen

Santos

et al. 2005

Industrial Robot: An International Journal

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Robotic hands are still a long way from matching the grasping and manipulation capability of their human counterparts. One way to push the research further along is to use computer modeling and simulation to learn more about human and robotic grasping. We have created a publicly available simulator to serve this purpose. It can accommodate a wide variety of hand designs, and it can evaluate grasps formed by these hands, as well as perform full dynamic simulation of the grasping process. In this paper, we present the various components of the system, and we describe two projects which use it as an integral part of larger grasp planning systems. We also discuss the development of a human hand model that uses accurate geometry and kinematics derived from experimental measurements. This is part of our current project to create a biomechanically realistic human hand model to better understand what features are most important to mimic in the designs of robotic hands.

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Dynamic Lumped Element Response of the Human Fingerpad

Cited by 133 publications

References 8 publications

The Spatial Spectrum of Tangential Skin Displacement Can Encode Tactual Texture

The Spatial Spectrum of Tangential Skin Displacement Can Encode Tactual Texture

A dense array stimulator to generate arbitrary spatio-temporal tactile stimuli

From robotic hands to human hands: a visualization and simulation engine for grasping research

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