Stress Fluctuations in Sliding of Textured Objects and the Sense of Touch
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Stress Fluctuations in Sliding of Textured Objects and the Sense of Touch
Tribology Gordon Conference 2010
Georges Debrégeas - Alexis Prevost
R. Candelier, J. Scheibert, S. Leurent
Laboratoire de Physique Statistique – ENS Paris
Patrice Rey (CEA-LETI)Joël Frelat (LMM, Paris 6)
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Information transduction in tactile perception
Object + motion
SKIN DEFORMATIONS &VIBRATIONS
NERVOUSSIGNALS
REPRESENTATION
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Glabrous skin mechanoreceptors
Merkel's cellcomplex
Meissner'scorpuscule
Pacinian corpuscule
Ruffiniending
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Glabrous skin mechanoreceptors
Stimulus
t
Slow Adaptation
Fast Adaptation
Merkel's cellcomplex
Meissner'scorpuscule
Pacinian corpuscule
Ruffiniending
Stimulus
t
Bolanowski et al., 1988
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Roughness perception: the duplex theory
Coding of coarse roughness> ~200µm
SA I (Merkel) channel Resolution limited by the small receptive
field (few hundred µm) Spatial coding (static) Fairly independent of finger's motion
Coding of fine roughness< ~200µm
Mediated by Pacinian corpuscules exclusively
Requires active tactile exploration Intensity coding
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Hollins and Bensmaia, 2008
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Questions :
1 – How can one relate the physical properties of the object and exploratory conditions to the mechanical signals experienced by mechanoreceptive nerve endings.
2 – What are the consequences of this filtering process on the transduction and neural encoding of tactile information.
Outline
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1 – Biomimetic tactile sensing – design and calibration.
2 – Dynamic impulse response.
3 – Response to randomly rough substrates.
4 – A possible role for fingerprints.
5 – Conclusions and perspectives.
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The biomimetic approach
Realfinger
Artificial finger
Sensitive area Sensor deth
Contact diameter
Skin elastic modulus
Humanfingertip
0.5 -10 mm 2-3 mm ~13mm (P~0.5N)
1-4 MPa
Artificial fingertip
2 mm 2.5 mm ~6mm(P~1.5N)
2.2±0.1Mpa
MEMS sensor
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Response to a localized force
Indentation protocol:Apply a ponctualforce at on the surface with a rod.
Receptive fields measured by our MEMS sensorsPredicted receptive field for a ponctual sensor in a perfectly elastic material
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Response to a localized force
Indentation protocol:Apply a ponctualforce at on the surface with a rod.
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Response to a localized force
Indentation protocol:Apply a ponctualforce at on the surface with a rod.
Without exploration: roughly the same response for the 10 sensors
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A linear model for tactile transduction
+Coulomb law:
Green function for a ponctual force at the surface:
Hertz contact
+
The stress felt by the sensor is given by:
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A linear model for tactile transduction
+Coulomb law:
Green function for a ponctual force at the surface:
Hertz contact
+
The stress at the sensor location reads:
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Dynamic impulse response.
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Dynamic impulse response.
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Dynamic impulse response.
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Dynamic impulse response
Perturbation in force signal associated with a small, isolated defect :
The modification in stress profile at the interface reads
Perturbation in force signal for a sensor at :
The response highly depends on the sensor's position within the contact zone
)ux()x(ss
)ux()xx(G)x()u(s s 0
u
0xx
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Dynamic impulse response – normal stress
Experiment
Model
Middle RightLeft
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Dynamic impulse response – tangential stress
Experiment
Model
Middle RightLeft
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Midline profiles
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Experiment
Model
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Receptive field variability in cortical neurons
DiCarlo et. al., 1998The journal of Neuroscience
« The shape, area and strength of exitatory and inhibitory receptive fields regions ranged widely. »
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Response to randomly rough substrates
Scanning over a binary patterned substrate
?
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The Volterra kernels give a mapping from to .
The Volterra decomposition
The Volterra series is the analog of the Taylor series, but for functionals:
NB: it is hard to extract the Volterra kernels ...
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For Gaussian white noise inputs, the Wiener kernels are orthogonal.
The Wiener decomposition
They can be computed through correlations:
...
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Extracting the linear kernel
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1g
measured
Predicted
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Consequences of skin patterning (e.g. fingerprints)
Artificial fingerprintsSquare-wave gratings
(period 220mm)on the skin's surface
Smooth skinFingerprinted skin
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Linear model of mechanical transduction
dx)ux(T).xx(G)x(s)u(s s 0
)x(g1
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Square wave gratings:
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)ux(T).x()u( ss
1)x(T
Interfacial stress profile:
Force signal :
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Stimulus- signal response function
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Stimulus- signal response function
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Numerical illustration of the filtering process
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Numerical illustration of the filtering process
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Numerical illustration of the filtering process
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Numerical illustration of the filtering process
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Numerical illustration of the filtering process
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2 mm
• Typical inter-ridge distance l ~ 500 µm• « Natural » exploratory finger/substrate velocity V ~ 10 cm/s
• Frequency f = V / l ~ 200 Hz • Order of the best frequency of Pacinian fibers• Pacinian fibers = mediate the coding of fine texture
Scenario Fingerprints select one spatial frequency Velocity chosen to match Pacinian best response
Consequence of fingerprints for fine texture perception
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Conclusions
Tribology Gordon Conference 2010
Biomimetic approach allowed to characterize the linear mechanical transduction of texture information, and clarify the roles played by intrinsic sensor’s response, interfacial contact stress field and skin topography.
But :- Limited to binary topography.- Non-linear effects should be important (stress coupling within the contact zone, normal stress dependence of the friction coefficient, etc.) Reverse correlation should allow to probe that.
Important open question :How does the tactile system deal with such context dependent variability of
individual sensors’ response. What encoding strategies may yield a stable representation of the probed surface.
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Comparing biomimetic and human touch
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JP Roll - LNH – Marseille
Can one relate the subcutaneous stress field measured with the biomimetic sensor with actual neurographic data ?
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Comparing whisker and digital touch
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Dan Shulz – Yves BoubenecUNIC - Gif-sur-Yvette
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Daniel Shulz (Gif-CNRS)
A 1A 2A 3A 4
Rodents whisker touch
Wolfe & Feldman, ‘08
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Johnson & Phillips, 1981
F
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The cochlea
Georg von Békésy, ‘47
inner hair cellsouter hair cells
Nobili, Mammano and Ashmore, ‘98
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…Back to the actual finger
Can we see this effect on a real finger ?
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