Stress Fluctuations in Sliding of Textured Objects and the Sense of Touch 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) Tribology Gordon Conference 2010 1 Information transduction in tactile perception Object + motion SKIN DEFORMATIONS & VIBRATIONS NERVOUS SIGNALS REPRESENTATION Tribology Gordon Conference 2010 2 Glabrous skin mechanoreceptors Merkel's cell complex Ruffini ending Meissner's corpuscule Pacinian corpuscule Tribology Gordon Conference 2010 3 Glabrous skin mechanoreceptors Stimulus Stimulus t t Slow Adaptation Merkel's cell complex Ruffini ending Meissner's corpuscule Bolanowski et al., 1988 Fast Adaptation Tribology Gordon Conference 2010 Pacinian corpuscule 4 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 Hollins and Bensmaia, 2008 Tribology Gordon Conference 2010 5 Outline 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. 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. Tribology Gordon Conference 2010 6 The biomimetic approach Real finger Artificial finger MEMS sensor Sensitive area Sensor deth Contact diameter Skin elastic modulus Human fingertip 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 Tribology Gordon Conference 2010 7 Response to a localized force Indentation protocol: Apply a ponctual force at on the surface with a rod. Receptive fields measured by our MEMS sensors Predicted receptive field for a ponctual sensor in a perfectly elastic material Tribology Gordon Conference 2010 8 Response to a localized force Indentation protocol: Apply a ponctual force at on the surface with a rod. Tribology Gordon Conference 2010 9 Response to a localized force Indentation protocol: Apply a ponctual force at on the surface with a rod. Without exploration: roughly the same response for the 10 sensors Tribology Gordon Conference 2010 10 A linear model for tactile transduction Hertz contact The stress felt by the sensor is given by: + Coulomb law: + Green function for a ponctual force at the surface: Tribology Gordon Conference 2010 11 A linear model for tactile transduction Hertz contact The stress at the sensor location reads: + Coulomb law: + Green function for a ponctual force at the surface: Tribology Gordon Conference 2010 12 Dynamic impulse response. Tribology Gordon Conference 2010 13 Dynamic impulse response. Tribology Gordon Conference 2010 14 Dynamic impulse response. Tribology Gordon Conference 2010 15 Dynamic impulse response u Perturbation in force signal associated with a small, isolated defect : The modification in stress profile at the interface reads s s ( x ) ( x u ) Perturbation in force signal for a sensor at x x0 : s( u ) s ( x ) G( x x0 ) ( x u ) The response highly depends on the sensor's position within the contact zone Tribology Gordon Conference 2010 16 Dynamic impulse response – normal stress Left Middle Right Experiment Model Tribology Gordon Conference 2010 17 Dynamic impulse response – tangential stress Left Middle Right Experiment Model Tribology Gordon Conference 2010 18 Midline profiles Experiment Model Tribology Gordon Conference 2010 19 Receptive field variability in cortical neurons DiCarlo et. al., 1998 The journal of Neuroscience « The shape, area and strength of exitatory and inhibitory receptive fields regions ranged widely. » Tribology Gordon Conference 2010 20 Response to randomly rough substrates Scanning over a binary patterned substrate Tribology Gordon Conference 2010 21 The Volterra decomposition The Volterra series is the analog of the Taylor series, but for functionals: The Volterra kernels give a mapping from to . NB: it is hard to extract the Volterra kernels ... Tribology Gordon Conference 2010 22 The Wiener decomposition For Gaussian white noise inputs, the Wiener kernels are orthogonal. They can be computed through correlations: ... Tribology Gordon Conference 2010 23 Extracting the linear kernel g1 measured Predicted Tribology Gordon Conference 2010 24 Consequences of skin patterning (e.g. fingerprints) Artificial fingerprints Square-wave gratings (period 220mm) on the skin's surface Tribology Gordon Conference 2010 Smooth skin Fingerprinted skin 25 Linear model of mechanical transduction Square wave gratings: T ( x ) 1 Interfacial stress profile: s ( u ) s ( x ).T ( x u ) Force signal : s( u ) s s ( x ) G( x x0 ).T ( x u )dx g1( x ) Tribology Gordon Conference 2010 26 Stimulus- signal response function 27 Tribology Gordon Conference 2010 Stimulus- signal response function 28 Tribology Gordon Conference 2010 Numerical illustration of the filtering process Tribology Gordon Conference 2010 29 Numerical illustration of the filtering process Tribology Gordon Conference 2010 30 Numerical illustration of the filtering process Tribology Gordon Conference 2010 31 Numerical illustration of the filtering process Tribology Gordon Conference 2010 32 Numerical illustration of the filtering process Tribology Gordon Conference 2010 33 Consequence of fingerprints for fine texture perception • Typical inter-ridge distance l ~ 500 µm • « Natural » exploratory finger/substrate velocity V ~ 10 cm/s 2 mm • 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 Tribology Gordon Conference 2010 34 Conclusions 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. Tribology Gordon Conference 2010 35 Comparing biomimetic and human touch Can one relate the subcutaneous stress field measured with the biomimetic sensor with actual neurographic data ? JP Roll - LNH – Marseille Tribology Gordon Conference 2010 36 Comparing whisker and digital touch Dan Shulz – Yves Boubenec UNIC - Gif-sur-Yvette Tribology Gordon Conference 2010 37 Rodents whisker touch A4 A1 A3 A2 Daniel Shulz (Gif-CNRS) Wolfe & Feldman, ‘08 Tribology 38 Gordon Tribology 39 Gordon F Johnson & Phillips, 1981 Tribology 40 Gordon Tribology 41 Gordon The cochlea Georg von Békésy, ‘47 inner hair cells outer hair cells Nobili, Mammano and Ashmore, ‘98 Tribology 42 Gordon …Back to the actual finger 10 0.1 C 0.1 0.001 -5 0.001 10 -5 -7 10 10 -7 -9 10 10 -9 -11 10 0.01 0.1 -1 1 10 10 Normalized power spectrum Normalized power spectrum Can we see this effect on a real finger ? -5 5 10 0.001 D -5 4 10 0.0001 -5 10 -5 10 -6 -5 -5 10 0 3 10 2 10 -7 1 10 0 0.5 1 1.5 2 <F> (N) 0 1 2 1/u (mm ) 3 -1 4 5 6 1/u (mm ) Communicative & Integrative Biology, Tribology Gordon Conference 2010 2009 43