Bioinspired Engineering of Fillable Gradient Structure into Flexible Capacitive Pressure Sensor Toward Ultra-High Sensitivity and Wide Working Range.

Tactile sensing is required for electronic skin and intelligent robots to function properly. However, the dielectric layer's poor structural compressibility in conventional pressure sensors results in a limited pressure sensing range and low sensitivity. To solve this issue, a flexible pressure sensor with a crocodile-inspired fillable gradient structure is provided. The fillable gradient structure and grooves in the pressure sensor accommodate the deformed microstructure that permits the enhancement of the media layer compressibility via COMSOL finite element simulation and optimization. The pressure sensor exhibits a high sensitivity of up to 0.97 k Pa-1 (0-4 kPa), a wide pressure detection range (7 Pa-380 kPa), and outstanding repeatability. The sensor can detect Morse code, robotic grabbing, and human motion monitoring. As a result, flexible sensors with a bionic fillable gradient structure pave the way for wearable devices and offer a novel method for achieving highly precise tactile perception.

Stimuli-responsive composite biopolymer actuators with selective spatial deformation behavior.

Bioinspired actuators with stimuli-responsive and deformable properties are being pursued in fields such as artificial tissues, medical devices and diagnostics, and intelligent biosensors. These applications require that actuator systems have biocompatibility, controlled deformability, biodegradability, mechanical durability, and stable reversibility. Herein, we report a bionic actuator system consisting of stimuli-responsive genetically engineered silk-elastin-like protein (SELP) hydrogels and wood-derived cellulose nanofibers (CNFs), which respond to temperature and ionic strength underwater by ecofriendly methods. Programmed site-selective actuation can be predicted and folded into three-dimensional (3D) origami-like shapes. The reversible deformation performance of the SELP/CNF actuators was quantified, and complex spatial transformations of multilayer actuators were demonstrated, including a biomimetic flower design with selective petal movements. Such actuators consisting entirely of biocompatible and biodegradable materials will offer an option toward constructing stimuli-responsive systems for in vivo biomedicine soft robotics and bionic research.

Reducing the energy cost of human walking using an unpowered exoskeleton.

With efficiencies derived from evolution, growth and learning, humans are very well-tuned for locomotion. Metabolic energy used during walking can be partly replaced by power input from an exoskeleton, but is it possible to reduce metabolic rate without providing an additional energy source? This would require an improvement in the efficiency of the human-machine system as a whole, and would be remarkable given the apparent optimality of human gait. Here we show that the metabolic rate of human walking can be reduced by an unpowered ankle exoskeleton. We built a lightweight elastic device that acts in parallel with the user's calf muscles, off-loading muscle force and thereby reducing the metabolic energy consumed in contractions. The device uses a mechanical clutch to hold a spring as it is stretched and relaxed by ankle movements when the foot is on the ground, helping to fulfil one function of the calf muscles and Achilles tendon. Unlike muscles, however, the clutch sustains force passively. The exoskeleton consumes no chemical or electrical energy and delivers no net positive mechanical work, yet reduces the metabolic cost of walking by 7.2 ± 2.6% for healthy human users under natural conditions, comparable to savings with powered devices. Improving upon walking economy in this way is analogous to altering the structure of the body such that it is more energy-effective at walking. While strong natural pressures have already shaped human locomotion, improvements in efficiency are still possible. Much remains to be learned about this seemingly simple behaviour.

Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison.

BACKGROUND: Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculature. Continuous decoders can provide more intuitive prosthesis control using multi-channel neural or electromyographic recordings. Three components influence continuous decoder performance: the data used to train the algorithm, the algorithm, and smoothing filters on the algorithm's output. Individual groups often focus on a single decoder, so very few studies compare different decoders using otherwise similar experimental conditions. METHODS: We completed a two-phase, head-to-head comparison of 12 continuous decoders using activities of daily living. In phase one, we compared two training types and a smoothing filter with three algorithms (modified Kalman filter, multi-layer perceptron, and convolutional neural network) in a clothespin relocation task. We compared training types that included only individual digit and wrist movements vs. combination movements (e.g., simultaneous grasp and wrist flexion). We also compared raw vs. nonlinearly smoothed algorithm outputs. In phase two, we compared the three algorithms in fragile egg, zipping, pouring, and folding tasks using the combination training and smoothing found beneficial in phase one. In both phases, we collected objective, performance-based (e.g., success rate), and subjective, user-focused (e.g., preference) measures. RESULTS: Phase one showed that combination training improved prosthesis control accuracy and speed, and that the nonlinear smoothing improved accuracy but generally reduced speed. Phase one importantly showed simultaneous movements were used in the task, and that the modified Kalman filter and multi-layer perceptron predicted more simultaneous movements than the convolutional neural network. In phase two, user-focused metrics favored the convolutional neural network and modified Kalman filter, whereas performance-based metrics were generally similar among all algorithms. CONCLUSIONS: These results confirm that state-of-the-art algorithms, whether linear or nonlinear in nature, functionally benefit from training on more complex data and from output smoothing. These studies will be used to select a decoder for a long-term take-home trial with implanted neuromyoelectric devices. Overall, clinical considerations may favor the mKF as it is similar in performance, faster to train, and computationally less expensive than neural networks.

Bionics and green technology in maritime shipping: an assessment of the effect of Salvinia air-layer hull coatings for drag and fuel reduction.

To save energy and reduce environmental impacts, new technologies towards a development of a sustainable 'greener' economy are needed. The main opportunity to improve sustainability by reducing emissions is within the transport sector. More than 90% of all goods worldwide are transported by ships. Particularly maritime ships using heavy fuel oil and marine gas oil play a major role. The total fuel consumption of shipping in 2016 was about 250 m t (domestic ca. 50 m t, international shipping ca. 200 m t). The vast portion of the energy consumption of a ship is the need to overcome the drag between ship hull and water-depending on the shape of the vessel and its size up to 90% of total fuel consumption. This means reducing drag helps to save fuel and reduces carbon emissions as well as pollution considerably. Different techniques for drag reduction are known, e.g. the micro-bubble technique or the bulbous bow. We investigated a novel bioinspired technique since 2002: the application of biomimetic surfaces with long-term stable air layers on ship hulls, serving as a slip agent. This technology is based on the Salvinia Effect, allowing a permanent stabilization of air layers under water. In this case study, we analysed the possible savings, which also could be combined with modified micro-bubble technologies. We calculated, based on a selection of five ship types, representing 75% of the world fleet, that air-layer hull coatings could lead to estimated savings of 32.5 million tons of fuel (meaning 13.0% of the worldwide shipping fuel consumption), equal to 18.5 billion US$ and 130.0 million tons of CO2e per year. The positive impacts on global temperature and other greenhouse gases are calculated and could be a contributing factor in accomplishing the UN Sustainable Development Goals and the Paris Agreement to the UN Framework Convention on Climate Change. The study is a contribution to enhance our patchy knowledge concerning the potential economic and ecological benefit of bionics and biomimetic technologies. This article is part of the theme issue 'Bioinspired materials and surfaces for green science and technology'.

Bacterial Nanobionics via 3D Printing.

Investigating the multidimensional integration between different microbiological kingdoms possesses potential toward engineering next-generation bionic architectures. Bacterial and fungal kingdom exhibits mutual symbiosis that can offer advanced functionalities to these bionic architectures. Moreover, functional nanomaterials can serve as probing agents for accessing newer information from microbial organisms due to their dimensional similarities. In this article, a bionic mushroom was created by intertwining cyanobacterial cells with graphene nanoribbons (GNRs) onto the umbrella-shaped pileus of mushroom for photosynthetic bioelectricity generation. These seamlessly merged GNRs function as agents for mediating extracellular electron transport from cyanobacteria resulting in photocurrent generation. Additionally, three-dimensional (3D) printing technique was used to assemble cyanobacterial cells in anisotropic, densely packed geometry resulting in adequate cell-population density for efficient collective behavior. These 3D printed cyanobacterial colonies resulted in comparatively higher photocurrent (almost 8-fold increase) than isotropically casted cyanobacteria of similar seeding density. An insight of the proposed integration between cyanobacteria and mushroom derives remarkable advantage that arises from symbiotic relationship, termed here as engineered bionic symbiosis. Existence of this engineered bionic symbiosis was confirmed by UV-visible spectroscopy and standard plate counting method. Taken together, the present study augments scientific understanding of multidimensional integration between the living biological microworld and functional abiotic nanomaterials to establish newer dimensionalities toward advancement of bacterial nanobionics.

Nitroaromatic detection and infrared communication from wild-type plants using plant nanobionics.

Plant nanobionics aims to embed non-native functions to plants by interfacing them with specifically designed nanoparticles. Here, we demonstrate that living spinach plants (Spinacia oleracea) can be engineered to serve as self-powered pre-concentrators and autosamplers of analytes in ambient groundwater and as infrared communication platforms that can send information to a smartphone. The plants employ a pair of near-infrared fluorescent nanosensors-single-walled carbon nanotubes (SWCNTs) conjugated to the peptide Bombolitin II to recognize nitroaromatics via infrared fluorescent emission, and polyvinyl-alcohol functionalized SWCNTs that act as an invariant reference signal-embedded within the plant leaf mesophyll. As contaminant nitroaromatics are transported up the roots and stem into leaf tissues, they accumulate in the mesophyll, resulting in relative changes in emission intensity. The real-time monitoring of embedded SWCNT sensors also allows residence times in the roots, stems and leaves to be estimated, calculated to be 8.3 min (combined residence times of root and stem) and 1.9 min mm-1 leaf, respectively. These results demonstrate the ability of living, wild-type plants to function as chemical monitors of groundwater and communication devices to external electronics at standoff distances.

Gait training after spinal cord injury: safety, feasibility and gait function following 8 weeks of training with the exoskeletons from Ekso Bionics.

STUDY DESIGN: Prospective quasi-experimental study, pre- and post-design. OBJECTIVES: Assess safety, feasibility, training characteristics and changes in gait function for persons with spinal cord injury (SCI) using the robotic exoskeletons from Ekso Bionics. SETTING: Nine European rehabilitation centres. METHODS: Robotic exoskeleton gait training, three times weekly over 8 weeks. Time upright, time walking and steps in the device (training characteristics) were recorded longitudinally. Gait and neurological function were measured by 10 Metre Walk Test (10 MWT), Timed Up and Go (TUG), Berg Balance Scale (BBS), Walking Index for Spinal Cord Injury (WISCI) II and Lower Extremity Motor Score (LEMS). RESULTS: Fifty-two participants completed the training protocol. Median age: 35.8 years (IQR 27.5-52.5), men/women: N = 36/16, neurological level of injury: C1-L2 and severity: AIS A-D (American Spinal Injury Association Impairment Scale). Time since injury (TSI) < 1 year, N = 25; > 1 year, N = 27. No serious adverse events occurred. Three participants dropped out following ankle swelling (overuse injury). Four participants sustained a Category II pressure ulcer at contact points with the device but completed the study and skin normalized. Training characteristics increased significantly for all subgroups. The number of participants with TSI < 1 year and gait function increased from 20 to 56% (P = 0.004) and 10MWT, TUG, BBS and LEMS results improved (P < 0.05). The number of participants with TSI > 1 year and gait function, increased from 41 to 44% and TUG and BBS results improved (P < 0.05). CONCLUSIONS: Exoskeleton training was generally safe and feasible in a heterogeneous sample of persons with SCI. Results indicate potential benefits on gait function and balance.

A Hybrid Bionic Image Sensor Achieving FOV Extension and Foveated Imaging.

Based on bionic compound eye and human foveated imaging mechanisms, a hybrid bionic image sensor (HBIS) is proposed in this paper to extend the field of view (FOV) with high resolution. First, the hybrid bionic imaging model was developed and the structure parameters of the HBIS were deduced. Second, the properties of the HBIS were simulated, including FOV extension, super-resolution imaging, foveal ratio and so on. Third, a prototype of the HBIS was developed to validate the theory. Imaging experiments were carried out, and the results are in accordance with the simulations, proving the potential of the HBIS for large FOV and high-resolution imaging with low cost.

Reducing the metabolic cost of walking with an ankle exoskeleton: interaction between actuation timing and power.

BACKGROUND: Powered ankle-foot exoskeletons can reduce the metabolic cost of human walking to below normal levels, but optimal assistance properties remain unclear. The purpose of this study was to test the effects of different assistance timing and power characteristics in an experiment with a tethered ankle-foot exoskeleton. METHODS: Ten healthy female subjects walked on a treadmill with bilateral ankle-foot exoskeletons in 10 different assistance conditions. Artificial pneumatic muscles assisted plantarflexion during ankle push-off using one of four actuation onset timings (36, 42, 48 and 54% of the stride) and three power levels (average positive exoskeleton power over a stride, summed for both legs, of 0.2, 0.4 and 0.5 W∙kg-1). We compared metabolic rate, kinematics and electromyography (EMG) between conditions. RESULTS: Optimal assistance was achieved with an onset of 42% stride and average power of 0.4 W∙kg-1, leading to 21% reduction in metabolic cost compared to walking with the exoskeleton deactivated and 12% reduction compared to normal walking without the exoskeleton. With suboptimal timing or power, the exoskeleton still reduced metabolic cost, but substantially less so. The relationship between timing, power and metabolic rate was well-characterized by a two-dimensional quadratic function. The assistive mechanisms leading to these improvements included reducing muscular activity in the ankle plantarflexors and assisting leg swing initiation. CONCLUSIONS: These results emphasize the importance of optimizing exoskeleton actuation properties when assisting or augmenting human locomotion. Our optimal assistance onset timing and average power levels could be used for other exoskeletons to improve assistance and resulting benefits.

Mapping of bionic array electric field focusing in plasmid DNA-based gene electrotransfer.

Molecular medicine through gene therapy is challenged to achieve targeted action. This is now possible utilizing bionic electrode arrays for focal delivery of naked (plasmid) DNA via gene electrotransfer. Here, we establish the properties of array-based electroporation affecting targeted gene delivery. An array with eight 300 µm platinum ring electrodes configured as a cochlear implant bionic interface was used to transduce HEK293 cell monolayers with a plasmid-DNA green fluorescent protein (GFP) reporter gene construct. Electroporation parameters were pulse intensity, number, duration, separation and electrode configuration. The latter determined the shape of the electric fields, which were mapped using a voltage probe. Electrode array-based electroporation was found to require ~100 × lower applied voltages for cell transduction than conventional electroporation. This was found to be due to compression of the field lines orthogonal to the array. A circular area of GFP-positive cells was created when the electrodes were ganged together as four adjacent anodes and four cathodes, whereas alternating electrode polarity created a linear area of GFP-positive cells. The refinement of gene delivery parameters was validated in vivo in the guinea pig cochlea. These findings have significant clinical ramifications, where spatiotemporal control of gene expression can be predicted by manipulation of the electric field via current steering at a cellular level.

Bionic reconstruction to restore hand function after brachial plexus injury: a case series of three patients.

BACKGROUND: Brachial plexus injuries can permanently impair hand function, yet present surgical reconstruction provides only poor results. Here, we present for the first time bionic reconstruction; a combined technique of selective nerve and muscle transfers, elective amputation, and prosthetic rehabilitation to regain hand function. METHODS: Between April 2011, and May 2014, three patients with global brachial plexus injury including lower root avulsions underwent bionic reconstruction. Treatment occurred in two stages; first, to identify and create useful electromyographic signals for prosthetic control, and second, to amputate the hand and replace it with a mechatronic prosthesis. Before amputation, the patients had a specifically tailored rehabilitation programme to enhance electromyographic signals and cognitive control of the prosthesis. Final prosthetic fitting was applied as early as 6 weeks after amputation. FINDINGS: Bionic reconstruction successfully enabled prosthetic hand use in all three patients. After 3 months, mean Action Research Arm Test score increased from 5·3 (SD 4·73) to 30·7 (14·0). Mean Southampton Hand Assessment Procedure score improved from 9·3 (SD 1·5) to 65·3 (SD 19·4). Mean Disabilities of Arm, Shoulder and Hand score improved from 46·5 (SD 18·7) to 11·7 (SD 8·42). INTERPRETATION: For patients with global brachial plexus injury with lower root avulsions, who have no alternative treatment, bionic reconstruction offers a means to restore hand function. FUNDING: Austrian Council for Research and Technology Development, Austrian Federal Ministry of Science, Research & Economy, and European Research Council Advanced Grant DEMOVE.

Plant nanobionics approach to augment photosynthesis and biochemical sensing.

The interface between plant organelles and non-biological nanostructures has the potential to impart organelles with new and enhanced functions. Here, we show that single-walled carbon nanotubes (SWNTs) passively transport and irreversibly localize within the lipid envelope of extracted plant chloroplasts, promote over three times higher photosynthetic activity than that of controls, and enhance maximum electron transport rates. The SWNT-chloroplast assemblies also enable higher rates of leaf electron transport in vivo through a mechanism consistent with augmented photoabsorption. Concentrations of reactive oxygen species inside extracted chloroplasts are significantly suppressed by delivering poly(acrylic acid)-nanoceria or SWNT-nanoceria complexes. Moreover, we show that SWNTs enable near-infrared fluorescence monitoring of nitric oxide both ex vivo and in vivo, thus demonstrating that a plant can be augmented to function as a photonic chemical sensor. Nanobionics engineering of plant function may contribute to the development of biomimetic materials for light-harvesting and biochemical detection with regenerative properties and enhanced efficiency.

Results of total hip arthroplasty using a bionic hip stem.

PURPOSE: The trabecular-orientated bionic hip stem was designed to mimic the natural force transmission through the femur in total hip arthroplasty, resulting in supposedly longer prosthesis survivability. The aim of this study was to compare the second-generation bionic hip stem to a standard uncemented hip stem. METHODS: A group of 18 patients (21 hips) who underwent total hip arthroplasty with a bionic stem (bionic group) was compared with a historic group of 12 patients (12 hips) treated with standard anatomic hip stem (control group). During the first year after the procedure, the densitometric measurements of the bone around the prosthesis were taken. Radiographic and clinical assessments were additionally performed preoperatively and at the three month, six month, one year and three year follow-ups in the bionic group. RESULTS: In the bionic group, one patient was revised for aseptic loosening and 16 patients (19 hips) were available to the final follow-up. A significant decrease of bone mineral density was found in Gruen zones 3, 4 and 5 in the bionic group, and in zone 7 in both groups. The bionic group had a significantly higher bone mineral density in Gruen zone 1 at the one year follow-up. At the final follow-up, all prostheses were radiologically stable in both groups. CONCLUSIONS: Provided that a good implant position is achieved, comparable short-term results can be obtained using a bionic stem. Still, a decrease of bone mineral density in Gruen zone 7 occurred in both groups. Further studies are required to determine survivability of the bionic stem.

Improved algorithms for the classification of rough rice using a bionic electronic nose based on PCA and the Wilks distribution.

Principal Component Analysis (PCA) is one of the main methods used for electronic nose pattern recognition. However, poor classification performance is common in classification and recognition when using regular PCA. This paper aims to improve the classification performance of regular PCA based on the existing Wilks Λ-statistic (i.e., combined PCA with the Wilks distribution). The improved algorithms, which combine regular PCA with the Wilks Λ-statistic, were developed after analysing the functionality and defects of PCA. Verification tests were conducted using a PEN3 electronic nose. The collected samples consisted of the volatiles of six varieties of rough rice (Zhongxiang1, Xiangwan13, Yaopingxiang, WufengyouT025, Pin 36, and Youyou122), grown in same area and season. The first two principal components used as analysis vectors cannot perform the rough rice varieties classification task based on a regular PCA. Using the improved algorithms, which combine the regular PCA with the Wilks Λ-statistic, many different principal components were selected as analysis vectors. The set of data points of the Mahalanobis distance between each of the varieties of rough rice was selected to estimate the performance of the classification. The result illustrates that the rough rice varieties classification task is achieved well using the improved algorithm. A Probabilistic Neural Networks (PNN) was also established to test the effectiveness of the improved algorithms. The first two principal components (namely PC1 and PC2) and the first and fifth principal component (namely PC1 and PC5) were selected as the inputs of PNN for the classification of the six rough rice varieties. The results indicate that the classification accuracy based on the improved algorithm was improved by 6.67% compared to the results of the regular method. These results prove the effectiveness of using the Wilks Λ-statistic to improve the classification accuracy of the regular PCA approach. The results also indicate that the electronic nose provides a non-destructive and rapid classification method for rough rice.

A bionic camera-based polarization navigation sensor.

Navigation and positioning technology is closely related to our routine life activities, from travel to aerospace. Recently it has been found that Cataglyphis (a kind of desert ant) is able to detect the polarization direction of skylight and navigate according to this information. This paper presents a real-time bionic camera-based polarization navigation sensor. This sensor has two work modes: one is a single-point measurement mode and the other is a multi-point measurement mode. An indoor calibration experiment of the sensor has been done under a beam of standard polarized light. The experiment results show that after noise reduction the accuracy of the sensor can reach up to 0.3256°. It is also compared with GPS and INS (Inertial Navigation System) in the single-point measurement mode through an outdoor experiment. Through time compensation and location compensation, the sensor can be a useful alternative to GPS and INS. In addition, the sensor also can measure the polarization distribution pattern when it works in multi-point measurement mode.

Polymer Bioelectronics: A Solution for Both Stimulating and Recording Electrodes.

The advent of closed-loop bionics has created a demand for electrode materials that are ideal for both stimulating and recording applications. The growing complexity and diminishing size of implantable devices for neural interfaces have moved beyond what can be achieved with conventional metallic electrode materials. Polymeric electrode materials are a recent development based on polymer composites of organic conductors such as conductive polymers. These materials present exciting new opportunities in the design and fabrication of next-generation electrode arrays which can overcome the electrochemical and mechanical limitations of conventional electrode materials. This review will examine the recent developments in polymeric electrode materials, their application as stimulating and recording electrodes in bionic devices, and their impact on the development of soft, conformal, and high-density neural interfaces.

Affective computing for human-machine interaction via a bionic organic memristor exhibiting selective in situ activation.

Affective computing, representing the forefront of human-machine interaction, is confronted with the pressing challenges of the execution speed and power consumption brought by the transmission of massive data. Herein, we introduce a bionic organic memristor inspired by the ligand-gated ion channels (LGICs) to facilitate near-sensor affective computing based on electroencephalography (EEG). It is constructed from a coordination polymer comprising Co ions and benzothiadiazole (Co-BTA), featuring multiple switching sites for redox reactions. Through advanced characterizations and theoretical calculations, we demonstrate that when subjected to a bias voltage, only the site where Co ions bind with N atoms from four BTA molecules becomes activated, while others remain inert. This remarkable phenomenon resembles the selective in situ activation of LGICs on the postsynaptic membrane for neural signal regulation. Consequently, the bionic organic memristor network exhibits outstanding reliability (200 000 cycles), exceptional integration level (210 pixels), ultra-low energy consumption (4.05 pJ), and fast switching speed (94 ns). Moreover, the built near-sensor system based on it achieves emotion recognition with an accuracy exceeding 95%. This research substantively adds to the ambition of realizing empathetic interaction and presents an appealing bionic approach for the development of novel electronic devices.

A Flexible Skin Bionic Thermally Comfortable Wearable for Machine Learning-Facilitated Ultrasensitive Sensing.

Tremendous popularity is observed for multifunctional flexible electronics with appealing applications in intelligent electronic skins, human-machine interfaces, and healthcare sensing. However, the reported sensing electronics, mostly can hardly provide ultrasensitive sensing sensitivity, wider sensing range, and robust cycling stability simultaneously, and are limited of efficient heat conduction out from the contacted skin interface after wearing flexible electronics on human skin to satisfy thermal comfort of human skin. Inspired from the ultrasensitive tactile perception microstructure (epidermis/spinosum/signal transmission) of human skin, a flexible comfortably wearable ultrasensitive electronics is hereby prepared from thermal conductive boron nitride nanosheets-incorporated polyurethane elastomer matrix with MXene nanosheets-coated surface microdomes as epidermis/spinosum layers assembled with interdigitated electrode as sensing signal transmission layer. It demonstrates appealing sensing performance with ultrasensitive sensitivity (≈288.95 kPa-1), up to 300 kPa sensing range, and up to 20 000 sensing cycles from obvious contact area variation between microdome microstructures and the contact electrode under external compression. Furthermore, the bioinspired electronics present advanced thermal management by timely efficient thermal dissipation out from the contacted skin surface to meet human skin thermal comfort with the incorporated thermal conductive boron nitride nanosheets. Thus, it is vitally promising in wearable artificial electronic skins, intelligent human-interactive sensing, and personal health management.