© The Institution of Engineering and Technology
The results from experiments with a screen-printed piezoelectric sensor, mounted on an artificial finger-tip and including a cosmetic covering, are shown to detect surface information from regular texture patterns. For the automatic control of an artificial hand and to feedback information to the amputee, an algorithm has been developed based on the standard deviation (SD) of signal data from the sensor. The SD analysis for texture detection is novel as it uses a combination of arithmetic processes. It windows the data sequentially and calculates the SD of the data in the windows and then averages the SDs. The output from the algorithm is the frequency spectrum of a signal. Plots, from the output of the algorithm, show events that correspond to the cyclic waveforms produced from the regularity of object surface patterns. The results from the algorithm are confirmed with an analysis of the signals using fast Fourier transforms.
References
-
-
1)
-
26. Kandel, E., Schwartz, J., Jessell, T.: ‘Principles of neural science’ (McGraw Hill, 2000, 4th edn.), no. 1.
-
2)
-
13. Janney, P., Geers, G.: ‘Texture classification using invariant features of local textures’, IET Image Proc., 2008, 4, (3), pp. 158–171 (doi: 10.1049/iet-ipr.2008.0229).
-
3)
-
25. Vallbo, A.B., Johansson, R.S.: ‘Properties of cutaneous mechanoreceptors in the human hand related to touch sensation’, Hum. Neurobiol., 1984, 3, (1), pp. 3–14.
-
4)
-
22. Fishel, J.A., Loeb, G.E.: ‘Bayesian exploration for intelligent identification of textures’, Front Neurorobot., 2012, 6, p. 4: (doi: 10.3389/fnbot.2012.00004).
-
5)
-
4. Dahiya, R.S., Metta, G., Cannata, G., et al: ‘Guest editorial special issue on robotic sense of touch’, IEEE Trans. Robot., 2011, 27, (3), pp. 385–388 (doi: 10.1109/TRO.2011.2155830).
-
6)
-
30. Taylor, M.M., Lederman, S.J.: ‘Tactile roughness of grooved surfaces: a model and the effect of friction’, Percept Psychophys, 1975, 17, (1), pp. 23–36 (doi: 10.3758/BF03203993).
-
7)
-
33. FitzGerald, J.J., Lago, N., Benmerah, S., et al: ‘A regenerative microchannel neural interface for recording from and stimulating peripheral axons in vivo’, J. Neural Eng., 2012, 9, (1), pp. 1–13 (doi: 10.1088/1741-2560/9/1/016010).
-
8)
-
34. Tan, D.W., Schiefer, M.A., Keith, M.W., et al: ‘A neural interface provides long-term stable natural touch perception’, Sci. Transl. Med., 2104, 6, (257), pp. 1–15.
-
9)
-
7. Prescott, T.J., Daimond, M.E., Wing, A.M.: ‘Active touch sensing’, Phil. Trans. R. Soc. B, 2011, 366, pp. 2989–2995 (doi: 10.1098/rstb.2011.0167).
-
10)
-
15. Jamali, N., Sammut, C.: ‘Majority voting: material classification by tactile sensing using surface texture’, IEEE Trans. Robot., 2011, 27, (3), pp. 508–521 (doi: 10.1109/TRO.2011.2127110).
-
11)
-
16. Cotton, D.P.J., Chappell, P.H., Cranny, A., et al: ‘A new binderless thick-film piezoelectric paste’, J. Mater. Sci., Mater. Electron., 2007, 18, (10), pp. 1037–1044 (doi: 10.1007/s10854-007-9275-8).
-
12)
-
1. Biddiss, E.A., Chau, T.T.: ‘Upper limb prosthesis use and abandonment: a survey of the last 25 years’, Prosthet. Orthot. Int., 2007, 31, (3), pp. 236–257 (doi: 10.1080/03093640600994581).
-
13)
-
31. Lederman, S.J., Klatzky, R.L., Hamilton, C.L., et al: ‘Perceiving roughness via a rigid probe: psychophysical effects of exploration speed and mode of touch’, Haptics-e Electron. J. Haptic. Res., 1999, 1, pp. 1–21.
-
14)
-
2. Visell, Y.: ‘Tactile sensory substitution: models for enaction in HCI’, Interact. Comput., 2009, 21, (1–2), pp. 38–53 (doi: 10.1016/j.intcom.2008.08.004).
-
15)
-
17. Cotton, D.P.J., Cranny, A., White, N.M., et al: ‘A novel thick-film piezoelectric slip sensor for a prosthetic hand’, IEEE Sens. J: Spec. Issue Intel. Sens., 2007, 7, (5), pp. 752–761 (doi: 10.1109/JSEN.2007.894912).
-
16)
-
28. Bensmaïa, S.J., Hollins, M.: ‘The vibrations of texture’, Somatosens. Mot. Res., 2003, 20, (1), pp. 33–43 (doi: 10.1080/0899022031000083825).
-
17)
-
20. Cotton, D.P.J., Cranny, A., White, N.M., et al: ‘Design and development of integrated thick film sensors for prosthetic hands’. Proc. Seventh Biennial Conf. Engineering Systems Design Analysis, 2004, pp. 573–589.
-
18)
-
12. Grollius, S., Kuhbauch, B., Gauterin, F.: ‘Development of a three-dimensional road texture measurement as a first step towards tyre road contact simulation’. Proc. IMEchE Part D Journal of Automobile Engineering, 2012, pp. 1–9.
-
19)
-
24. Scheibert, J., Leurent, S., Prevost, A., et al: ‘The role of fingerprints in the coding of tactile information probed with a biomimetic sensor’, Science, 2009, 323, pp. 1503–1506 (doi: 10.1126/science.1166467).
-
20)
-
18. Carrozza, M.C., Cappiello, G., Micera, S., et al: ‘Design of a cybernetic hand for perception and action’, Biol. Cybern., 2006, 95, pp. 629–644 (doi: 10.1007/s00422-006-0124-2).
-
21)
-
23. Jamali, N., Sammut, C.: ‘Material classification by tactile sensing using surface textures’. IEEE Int. Conf. Robot Auto, Anchorage Alaska, 2010, pp. 2336–2341.
-
22)
-
19. Khodambashi, R., Najarian, S., Golpaygani, A.T., et al: ‘A tactile sensor for detection of skin morphology and its application in telemedicine systems’, Am. J. Appl. Sci., 2008, 5, pp. 633–638 (doi: 10.3844/ajassp.2008.633.638).
-
23)
-
8. Kroemer, O., Lampert, C.H., Peters, J.: ‘Learning dynamic tactile sensing with robust vision-based training’, IEEE Trans. Robot., 2011, 27, (3), pp. 545–557 (doi: 10.1109/TRO.2011.2121130).
-
24)
-
10. Oddo, C.M., Controzzi, M., Beccai, L., et al: ‘Roughness encoding for discrimination of surfaces in artificial active-touch’, IEEE Trans. Robot., 2011, 27, (3), pp. 522–533 (doi: 10.1109/TRO.2011.2116930).
-
25)
-
35. Vega-Bermudez, F., Johnson, K.O.: ‘SA1 and RA receptive fields, response variability, and population responses mapped with a probe array’, J. Neurophysiol., 1999, 81, pp. 2701–2710.
-
26)
-
9. Pearson, M.J., Mitchinson, B., Sullivan, J.C., et al: ‘Biomimetic vibrissal sensing for robots’, Phil. Trans. R. Soc. B, 2011, 366, pp. 3085–3096 (doi: 10.1098/rstb.2011.0164).
-
27)
-
14. Haopeng, L., Flierl, M.: ‘Sift-based improvement of depth imagery’. IEEE Int. Conf. Multmedia Expo ICME, 2011, pp. 1–6.
-
28)
-
6. Giguere, P., Dudek, G.: ‘A simple tactile probe for surface identification by mobile robots 2011’, IEEE Trans. Robot., 2011, 27, (3), pp. 534–544 (doi: 10.1109/TRO.2011.2119910).
-
29)
-
32. Wodlinger, B., Downey, J.E., Tyler-Kabara, E.C., et al: ‘Ten-dimensional anthropomorphic arm control in a human brain-machine interface: difficulties, solutions, and limitations’, J. Neural Eng., 2015, 12, pp. 1–17 (doi: 10.1088/1741-2560/12/1/016011).
-
30)
-
5. De Maria, G., Natale, C., Pirozzi, S.: ‘Force/tactile sensor for robotic applications’, Sens. Actuators A, Phys., 2012, 175, pp. 60–72 (doi: 10.1016/j.sna.2011.12.042).
-
31)
-
29. Mano, T., Ohka, M.: ‘Mechanisms of fine-surface-texture discrimination in human’, J. Accoust. Soc. Am., 1999, 105, (4), pp. 2485–2492 (doi: 10.1121/1.426852).
-
32)
-
21. Muridan, N., Chappell, P.H., Cotton, D.P.J., et al: ‘Detection of slip from multiple sites in an artificial finger’, Sens. Appl. XV, Heriot Watt University, Edinburgh, Scotland, 05–07 Oct 2009, IOP Publishing, pp. 1–6.
-
33)
-
11. Harun, S.W., Yasin, M., Yang, H.Z., et al: ‘Estimation of metal surface roughness using fibre optic displacement sensor’, Laser Phys., 2010, 20, (4), pp. 904–909 (doi: 10.1134/S1054660X10070091).
-
34)
-
26. Kandel, E., Schwartz, J., Jessell, T.: ‘Principles of neural science’ (McGraw Hill, 2000, 4th edn.), no. 1.
-
35)
-
27. Kim, K., Colgate, J.: ‘On the design of miniature haptic devices for upper extremity prosthetics’, IEEE/ASME Trans. Mechatronics, 2010, 15, (1), pp. 27–39 (doi: 10.1109/TMECH.2009.2013944).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-smt.2015.0003
Related content
content/journals/10.1049/iet-smt.2015.0003
pub_keyword,iet_inspecKeyword,pub_concept
6
6