Texture recognition based on multi-sensory integration of proprioceptive and tactile signals.

Autor: Rostamian B; Medical Biology Research Center, Institute of Health Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran., Koolani M; Medical Biology Research Center, Institute of Health Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran., Abdollahzade P; Medical Biology Research Center, Institute of Health Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran., Lankarany M; Krembil Research Institute, University Health Network (UHN), Toronto, ON, Canada.; Institute of Biomedical Engineering and Department of Physiology, University of Toronto, Toronto, Canada., Falotico E; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy., Amiri M; Medical Technology Research Center, Institute of Health Technology, Kermanshah University of Medical Sciences, Parastar Ave., Kermanshah, Iran. ma_amiri_bme@yahoo.com., V Thakor N; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.; Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2022 Dec 15; Vol. 12 (1), pp. 21690. Date of Electronic Publication: 2022 Dec 15.
DOI: 10.1038/s41598-022-24640-5
Abstrakt: The sense of touch plays a fundamental role in enabling us to interact with our surrounding environment. Indeed, the presence of tactile feedback in prostheses greatly assists amputees in doing daily tasks. In this line, the present study proposes an integration of artificial tactile and proprioception receptors for texture discrimination under varying scanning speeds. Here, we fabricated a soft biomimetic fingertip including an 8 × 8 array tactile sensor and a piezoelectric sensor to mimic Merkel, Meissner, and Pacinian mechanoreceptors in glabrous skin, respectively. A hydro-elastomer sensor was fabricated as an artificial proprioception sensor (muscle spindles) to assess the instantaneous speed of the biomimetic fingertip. In this study, we investigated the concept of the complex receptive field of RA-I and SA-I afferents for naturalistic textures. Next, to evaluate the synergy between the mechanoreceptors and muscle spindle afferents, ten naturalistic textures were manipulated by a soft biomimetic fingertip at six different speeds. The sensors' outputs were converted into neuromorphic spike trains to mimic the firing pattern of biological mechanoreceptors. These spike responses are then analyzed using machine learning classifiers and neural coding paradigms to explore the multi-sensory integration in real experiments. This synergy between muscle spindle and mechanoreceptors in the proposed neuromorphic system represents a generalized texture discrimination scheme and interestingly irrespective of the scanning speed.
(© 2022. The Author(s).)
Databáze: MEDLINE
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