Abstract
Adjustments to friction are crucial for precision object handling in both humans and robotic manipulators. The aim of this work was to investigate the ability of machine learning to disentangle concurrent stimulus parameters, such as normal force ramp rate, texture and friction, from the responses of tactile afferents at the point of initial contact with the human finger pad. Three textured stimulation surfaces were tested under two frictional conditions each, with a 4 N normal force applied at three ramp rates. During stimulation, the responses of fourteen afferents (5 SA-I, 2 SA-II, 5 FA-I, 2 FA-II) were recorded. A Parzen window classifier was used to classify ramp rate, texture and frictional condition using spike count, first spike latency or peak frequency from each afferent. This is the first study to show that ramp rate, texture and frictional condition could be classified concurrently with over 90 % accuracy using a small number of tactile sensory units.
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Vallbo, A.B., Johansson, R.S.: Properties of cutaneous mechanoreceptors in the human hand related to touch sensation. Hum. Neurobiol. 3, 11 (1984)
Macefield, V.G., Birznieks, I.: Cutaneous mechanoreceptors, functional behavior. In: Binder, M.D., Hirokawa, N., Windhorst, U. (eds.) Encyclopedia of Neuroscience, pp. 914–922. Springer, Heidelberg (2009)
Goodwin, A.W., Jenmalm, P., Johansson, R.S.: Control of grip force when tilting objects: effect of curvature of grasped surfaces and applied tangential torque. J. Neurosci. 18, 10724–10734 (1998)
Birznieks, I., Wheat, H.E., Redmond, S.J., Salo, L.M., Lovell, N.H., Goodwin, A.W.: Encoding of tangential torque in responses of tactile afferent fibres innervating the fingerpad of the monkey. J. Physiol. 588, 1057–1072 (2010)
Redmond, S.J., Birznieks, I., Lovell, N.H., Goodwin, A.W.: Classifying torque, normal force and direction using monkey afferent nerve spike rates. In: Kappers, A.M., van Erp, J.B., Bergmann Tiest, W.M., van der Helm, F.C. (eds.) EuroHaptics 2010, Part I. LNCS, vol. 6191, pp. 43–50. Springer, Heidelberg (2010)
Birznieks, I., Jenmalm, P., Goodwin, A.W., Johansson, R.S.: Encoding of direction of fingertip forces by human tactile afferents. J. Neurosci. 21, 8222–8237 (2001)
Westling, G., Johansson, R.S.: Factors influencing the force control during precision grip. Exp. Brain Res. 53, 277–284 (1984)
Johansson, R., Westling, G.: Signals in tactile afferents from the fingers eliciting adaptive motor responses during precision grip. Exp. Brain Res. 66, 141–154 (1987)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. Wiley, New York (2001)
Fu, J., Birznieks, I., Goodwin, A., Khamis, H., Redmond, S.: Decoding our sense of touch: multiple regression analysis of monkey fingertip afferent mechanoreceptor population responses. Presented at the 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), San Diego, CA, USA (2012)
Johansson, R.S., Westling, G.: Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects. Exp. Brain Res. 56, 5 (1984)
Pubols, B.: Factors affecting cutaneous mechanoreceptor response. II. Changes in mechanical properties of skin with repeated stimulation. J. Neurophysiol. 47, 530–542 (1982)
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Khamis, H., Redmond, S.J., Macefield, V., Birznieks, I. (2014). Classification of Texture and Frictional Condition at Initial Contact by Tactile Afferent Responses. In: Auvray, M., Duriez, C. (eds) Haptics: Neuroscience, Devices, Modeling, and Applications. EuroHaptics 2014. Lecture Notes in Computer Science(), vol 8618. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44193-0_58
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DOI: https://doi.org/10.1007/978-3-662-44193-0_58
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