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Morphological Neural Computation Restores Discrimination of Naturalistic Textures in Trans-radial Amputees
Alberto Mazzoni
Calogero M. Oddo
Giacomo Valle
Domenico Camboni
Ivo Strauss
Massimo Barbaro
Gianluca Barabino
Roberto Puddu
Caterina Carboni
Lorenzo Bisoni
Jacopo Carpaneto
Fabrizio Vecchio
Francesco Maria Petrini
Simone Romeni
Tamas Czimmermann
Luca Massari
Riccardo Di Iorio
Francesca Miraglia
Giuseppe Granata
Danilo Pani
Thomas Stieglitz
Luigi Raffo
Paolo M. Rossini
Silvestro Micera
出版
Universität
, 2020
URL
http://books.google.com.hk/books?id=P4d9zgEACAAJ&hl=&source=gbs_api
註釋
Abstract: Humans rely on their sense of touch to interact with the environment. Thus, restoring lost tactile sensory capabilities in amputees would advance their quality of life. In particular, texture discrimination is an important component for the interaction with the environment, but its restoration in amputees has been so far limited to simplified gratings. Here we show that naturalistic textures can be discriminated by trans-radial amputees using intraneural peripheral stimulation and tactile sensors located close to the outer layer of the artificial skin. These sensors exploit the morphological neural computation (MNC) approach, i.e., the embodiment of neural computational functions into the physical structure of the device, encoding normal and shear stress to guarantee a faithful neural temporal representation of stimulus spatial structure. Two trans-radial amputees successfully discriminated naturalistic textures via the MNC-based tactile feedback. The results also allowed to shed light on the relevance of spike temporal encoding in the mechanisms used to discriminate naturalistic textures. Our findings pave the way to the development of more natural bionic limbs