Restoring Natural Sensory Feedback in Real-Time Bidirectional Hand Prostheses

Raspopović, Staniša; Capogrosso, Marco; Petrini, Francesco Maria; Bonizzato, Marco; Rigosa, Jacopo; Pino, Giovanni Di; Carpaneto, J.; Controzzi, Marco; Boretius, Tim; Fernández, Eduardo B.; Granata, Giuseppe; Oddo, Calogero Maria; Citi, Luca; Ciancio, Anna Lisa; Cipriani, Christian; Carrozza, Maria Chiara; Jensen, Winnie; Guglielmelli, Eugenio; Stieglitz, Thomas; Rossini, Paolo Maria; Micera, Silvestro

doi:10.1126/scitranslmed.3006820

Cited by 827 publications

(787 citation statements)

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“…57). Also, the model will be valuable in neuroprosthetic applications that aim to restore the sense of touch through peripheral nerve interfaces (58)(59)(60). Indeed, the output of sensors on the prosthesis during object contact can be used as input to the simulated afferents, which then provide an accurate representation of how the nerve from an intact hand would respond to object contact.…”

Section: Discussionmentioning

confidence: 99%

Simulating tactile signals from the whole hand with millisecond precision

Saal

Delhaye

Rayhaun

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

203

251

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When we grasp and manipulate an object, populations of tactile nerve fibers become activated and convey information about the shape, size, and texture of the object and its motion across the skin. The response properties of tactile fibers have been extensively characterized in single-unit recordings, yielding important insights into how individual fibers encode tactile information. A recurring finding in this extensive body of work is that stimulus information is distributed over many fibers. However, our understanding of population-level representations remains primitive. To fill this gap, we have developed a model to simulate the responses of all tactile fibers innervating the glabrous skin of the hand to any spatiotemporal stimulus applied to the skin. The model first reconstructs the stresses experienced by mechanoreceptors when the skin is deformed and then simulates the spiking response that would be produced in the nerve fiber innervating that receptor. By simulating skin deformations across the palmar surface of the hand and tiling it with receptors at their known densities, we reconstruct the responses of entire populations of nerve fibers. We show that the simulated responses closely match their measured counterparts, down to the precise timing of the evoked spikes, across a wide variety of experimental conditions sampled from the literature. We then conduct three virtual experiments to illustrate how the simulation can provide powerful insights into population coding in touch. Finally, we discuss how the model provides a means to establish naturalistic artificial touch in bionic hands.mechanoreceptor | tactile afferent | somatosensory periphery | skin mechanics | computational model T he human hand is endowed with thousands of mechanoreceptors of different types distributed across the skin, each innervated by one or more large myelinated nerve fibers (1). These fibers convey detailed information about contact events and provide us with an exquisite sensitivity to the form and surface properties of grasped objects (2, 3). During object manipulation and tactile exploration, the glabrous skin of the hand undergoes complex spatiotemporal mechanical deformations, which in turn, drive very precise spiking responses in individual afferents. Coarse object features, such as edges and corners, are reflected in spatial patterns of activation in slowly adapting type I (SA1) and rapidly adapting (RA) fibers, which are densely packed in the fingertip (3, 4). At the same time, interactions with objects and surfaces elicit high-frequency, low-amplitude surface waves that propagate across the skin of the finger and palm and excite vibration-sensitive Pacinian (PC) afferents all over the hand (5-8).Recording the activity of tactile nerve fibers in monkeys or humans is technically difficult, is slow, and generally yields responses from a single unit at a time (9, 10). Although such recordings have yielded powerful insights into the neural basis of touch, they provide a limited window into the information that the hand c...

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Section: Discussionmentioning

confidence: 99%

Simulating tactile signals from the whole hand with millisecond precision

Saal

Delhaye

Rayhaun

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

203

251

View full text Add to dashboard Cite

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“…As a result, many amputee patients wear prosthetic limbs for cosmetic utility 3 or as supplementary movement aids 4 rather than as a functional replacement for natural limbs. Recent advances in the design of prosthetic limbs integrated with rigid and/or semi-flexible tactile sensors provide sensory reception to enable feedback in response to variable environments 5 . However, there still exists a mechanical mismatch between conventional electronics in wearable prosthetics and soft biological tissues, which impede the utility and performance of prosthetics in amputee populations.…”

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confidence: 99%

Stretchable silicon nanoribbon electronics for skin prosthesis

et al. 2014

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Sensory receptors in human skin transmit a wealth of tactile and thermal signals from external environments to the brain. Despite advances in our understanding of mechano-and thermosensation, replication of these unique sensory characteristics in artificial skin and prosthetics remains challenging. Recent efforts to develop smart prosthetics, which exploit rigid and/or semi-flexible pressure, strain and temperature sensors, provide promising routes for sensor-laden bionic systems, but with limited stretchability, detection range and spatiotemporal resolution. Here we demonstrate smart prosthetic skin instrumented with ultrathin, single crystalline silicon nanoribbon strain, pressure and temperature sensor arrays as well as associated humidity sensors, electroresistive heaters and stretchable multi-electrode arrays for nerve stimulation. This collection of stretchable sensors and actuators facilitate highly localized mechanical and thermal skin-like perception in response to external stimuli, thus providing unique opportunities for emerging classes of prostheses and peripheral nervous system interface technologies.

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“…On the other hand, implant stability is also critical for providing long-term sensory feedback. While much higher selectivity can be obtained through intrafascicular implants (Davis et al, 2016;Dhillon and Horch, 2005;Raspopovic et al, 2014;Rossini et al, 2010), only extra-fascicular implants have exhibited stability for long periods of time (Tan et al, 2015;Tan et al, 2014).…”

Section: Hardware Considerationsmentioning

confidence: 99%

“…The other family of approaches consists of activating, using electrical stimulation, the neuronal populations that would be activated if the limb and nervous system were intact. For amputees, somatosensory restoration involves interfacing with the nerve using chronically implanted multi-electrode arrays (Clark et al, 2014;Dhillon and Horch, 2005;Raspopovic et al, 2014;Tan et al, 2014). For tetraplegic patients, somatosensory feedback is conveyed by directly stimulating the brain, somewhere along the neuraxis from the brain stem through the somatosensory cortex (Bensmaia and Miller, 2014;Cushing, 1909;Dadarlat et al, 2015;Davis et al, 1998;Fitzsimmons et al, 2007;Kim et al, 2015;O'Doherty et al, 2009;O'Doherty et al, 2011;O'Doherty et al, 2012;Penfield and Boldrey, 1937;Richardson et al, 2016;Romo et al, 1998;Tabot et al, 2013).…”

Section: Introductionmentioning

confidence: 99%