Seedless Hydrothermal Growth of ZnO Nanorods as a Promising Route for Flexible Tactile Sensors.

Hydrothermal growth of ZnO nanorods has been widely used for the development of tactile sensors, with the aid of ZnO seed layers, favoring the growth of dense and vertically aligned nanorods. However, seed layers represent an additional fabrication step in the sensor design. In this study, a seedless hydrothermal growth of ZnO nanorods was carried out on Au-coated Si and polyimide substrates. The effects of both the Au morphology and the growth temperature on the characteristics of the nanorods were investigated, finding that smaller Au grains produced tilted rods, while larger grains provided vertical rods. Highly dense and high-aspect-ratio nanorods with hexagonal prismatic shape were obtained at 75 °C and 85 °C, while pyramid-like rods were grown when the temperature was set to 95 °C. Finite-element simulations demonstrated that prismatic rods produce higher voltage responses than the pyramid-shaped ones. A tactile sensor, with an active area of 1 cm2, was fabricated on flexible polyimide substrate and embedding the nanorods forest in a polydimethylsiloxane matrix as a separation layer between the bottom and the top Au electrodes. The prototype showed clear responses upon applied loads of 2-4 N and vibrations over frequencies in the range of 20-800 Hz.

Morphological Neural Computation Restores Discrimination of Naturalistic Textures in Trans-radial Amputees.

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.

Tactile Decoding of Edge Orientation With Artificial Cuneate Neurons in Dynamic Conditions.

Generalization ability in tactile sensing for robotic manipulation is a prerequisite to effectively perform tasks in ever-changing environments. In particular, performing dynamic tactile perception is currently beyond the ability of robotic devices. A biomimetic approach to achieve this dexterity is to develop machines combining compliant robotic manipulators with neuroinspired architectures displaying computational adaptation. Here we demonstrate the feasibility of this approach for dynamic touch tasks experimented by integrating our sensing apparatus in a 6 degrees of freedom robotic arm via a soft wrist. We embodied in the system a model of spike-based neuromorphic encoding of tactile stimuli, emulating the discrimination properties of cuneate nucleus neurons based on pathways with differential delay lines. These strategies allowed the system to correctly perform a dynamic touch protocol of edge orientation recognition (ridges from 0 to 40°, with a step of 5°). Crucially, the task was robust to contact noise and was performed with high performance irrespectively of sensing conditions (sensing forces and velocities). These results are a step forward toward the development of robotic arms able to physically interact in real-world environments with tactile sensing.

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons.

Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.

Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans.

Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in the next generation of neuro-prosthetic hands.

Physical factors influencing pleasant touch during passive fingertip stimulation.

OBJECTIVE: Tactile explorations with the fingertips provide information regarding the physical properties of surfaces and their relative pleasantness. Previously, we performed an investigation in the active touch domain and linked several surface properties (i.e. frictional force fluctuations and net friction) with their pleasantness levels. The aim of the present study was to investigate physical factors being important for pleasantness perception during passive fingertip stimulation. Specifically we were interested to see whether factors, such as surfaces' topographies or their frictional characteristics could influence pleasantness. Furthermore, we ascertained how the stimulus pleasantness level was impacted by (i) the normal force of stimulus application (FN) and (ii) the stimulus temperature (TS). METHODS AND RESULTS: The right index fingertips of 22 blindfolded participants were stimulated using 27 different stimuli, which varied in average roughness (Ra) and TS. A 4-axis robot moved the stimuli horizontally under participants' fingertips with three levels of FN. The robot was equipped with force sensors, which recorded the FN and friction force (FT) during stimulation. Participants rated each stimulus according to a three-level pleasantness scale, as very pleasant (scored 0), pleasant (scored 1), or unpleasant (scored 2). These ordinal pleasantness ratings were logarithmically transformed into linear and unidimensional pleasantness measures with the Rasch model. Statistical analyses were conducted to investigate a possible link between the stimulus properties (i.e. Ra, FN, FT, and TS) and their respective pleasantness levels. Only the mean Ra and FT values were negatively correlated with pleasantness. No significant correlation was detected between FN or TS and pleasantness. CONCLUSION: Pleasantness perception, resulting from passive fingertip stimulation, seems to be influenced by the surfaces' average roughness levels and average FT occurring during fingertip stimulation.

Piezoelectric energy harvesting solutions.

This paper reviews the state of the art in piezoelectric energy harvesting. It presents the basics of piezoelectricity and discusses materials choice. The work places emphasis on material operating modes and device configurations, from resonant to non-resonant devices and also to rotational solutions. The reviewed literature is compared based on power density and bandwidth. Lastly, the question of power conversion is addressed by reviewing various circuit solutions.

A bio-hybrid tactile sensor incorporating living artificial skin and an impedance sensing array.

The development of a bio-hybrid tactile sensor array that incorporates a skin analogue comprised of alginate encapsulated fibroblasts is described. The electrical properties are modulated by mechanical stress induced during contact, and changes are detected by a ten-channel dual-electrode impedance sensing array. By continuously monitoring the impedance of the sensor array at a fixed frequency, whilst normal and tangential loads are applied to the skin surface, transient mechanotransduction has been observed. The results demonstrate the effectiveness and feasibility of the preliminary prototype bio-hybrid tactile sensor.