Next Article in Journal
Label-Free Electrochemical Detection of the Specific Oligonucleotide Sequence of Dengue Virus Type 1 on Pencil Graphite Electrodes
Next Article in Special Issue
Cytochrome C Biosensor—A Model for Gas Sensing
Previous Article in Journal / Special Issue
Wearable and Implantable Wireless Sensor Network Solutions for Healthcare Monitoring
Sensors 2011, 11(6), 5596-5615; doi:10.3390/s110605596
Article

Roughness Encoding in Human and Biomimetic Artificial Touch: Spatiotemporal Frequency Modulation and Structural Anisotropy of Fingerprints

1,* , 2
, 3
, 3
, 2
 and 1
1 The BioRobotics Institute, Scuola Superiore Sant’Anna, Polo Sant’Anna Valdera, Viale Rinaldo Piaggio 34, 56025 Pontedera, PI, Italy 2 Center for Micro-BioRobotics@SSSA, Istituto Italiano di Tecnologia (IIT), Viale Rinaldo Piaggio 34, 56025 Pontedera, PI, Italy 3 Department of Physiology, University of Gothenburg, Medicinaregatan 11, SE-40530 Goteborg, Sweden
* Author to whom correspondence should be addressed.
Received: 24 March 2011 / Revised: 28 April 2011 / Accepted: 16 May 2011 / Published: 26 May 2011
(This article belongs to the Special Issue Bioinspired Sensor Systems)
View Full-Text   |   Download PDF [3755 KB, uploaded 21 June 2014]   |   Browse Figures

Abstract

The influence of fingerprints and their curvature in tactile sensing performance is investigated by comparative analysis of different design parameters in a biomimetic artificial fingertip, having straight or curved fingerprints. The strength in the encoding of the principal spatial period of ridged tactile stimuli (gratings) is evaluated by indenting and sliding the surfaces at controlled normal contact force and tangential sliding velocity, as a function of fingertip rotation along the indentation axis. Curved fingerprints guaranteed higher directional isotropy than straight fingerprints in the encoding of the principal frequency resulting from the ratio between the sliding velocity and the spatial periodicity of the grating. In parallel, human microneurography experiments were performed and a selection of results is included in this work in order to support the significance of the biorobotic study with the artificial tactile system.
Keywords: MEMS tactile sensor array; fingerprints; biomimetic fingertip; roughness encoding; artificial touch; mechanoreceptors; microneurography; human touch; biorobotics MEMS tactile sensor array; fingerprints; biomimetic fingertip; roughness encoding; artificial touch; mechanoreceptors; microneurography; human touch; biorobotics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Export to BibTeX |
EndNote


MDPI and ACS Style

Oddo, C.M.; Beccai, L.; Wessberg, J.; Wasling, H.B.; Mattioli, F.; Carrozza, M.C. Roughness Encoding in Human and Biomimetic Artificial Touch: Spatiotemporal Frequency Modulation and Structural Anisotropy of Fingerprints. Sensors 2011, 11, 5596-5615.

View more citation formats

Related Articles

Article Metrics

Comments

Citing Articles

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert