RESUMEN

The research on proximity sensing electronic skin has garnered significant attention. This electronic skin technology enables detection without physical contact and holds vast application prospects in areas such as human-robot collaboration, human-machine interfaces, and remote monitoring. Especially in the context of the spread of infectious diseases like COVID-19, there is a pressing need for non-contact detection to ensure safe and hygienic operations. This article comprehensively reviews the significant advancements in the field of proximity sensing electronic skin technology in recent years. It covers the principles, as well as single-type proximity sensors with characteristics such as a large area, multifunctionality, strain, and self-healing capabilities. Additionally, it delves into the research progress of dual-type proximity sensors. Furthermore, the article places a special emphasis on the widespread applications of flexible proximity sensors in human-robot collaboration, human-machine interfaces, and remote monitoring, highlighting their importance and potential value across various domains. Finally, the paper provides insights into future advancements in flexible proximity sensor technology.

Asunto(s)

RESUMEN

Technologies for human-machine interactions are booming now. In order to achieve multifunctional sensing abilities of electronic skins, further developments of various sensors are in urgent demand. Herein, a dual-mode proximity sensor based on an oxide thin-film transistor (TFT) is reported. Although InSnO (ITO) is featured with high mobility, the inherent high carrier concentration limits its use as a channel material for thin-film transistors. Herein, the tungsten element was introduced as a carrier suppressor to develop ITO-based semiconducting materials and devices. TFTs with amorphous tungsten-doped ITO (ITWO) channel layers were fabricated. As for a flat panel display application, the TFT device from 250 °C-annealed ITWO layer with an atomic ratio of In/Sn/W = 86:9:5 presented the optimal device performance with carrier mobility of 11.53 cm2 V-1 s-1, swing subthreshold of 0.66 V dec-1, threshold voltage of -2.18 V, and Ion/Ioff ratio of 3.33 × 107 and much small hysteresis of transfer characteristic. ITWO TFT devices were further developed as dual-mode proximity sensors that could work with both extended-gate and compact configurations, where the drain current was directly related to the surface potential of a charged object and the distance between the sensing end and the object, enabling the proximity sensing of charged stimuli. For extended-gate-configured proximity sensing, a charged object modulated the formation of a conductive channel at the semiconductor/SiO2 interface, while this conductive channel occurred at the semiconductor/air interface for compact-configured sensing. Formation of the conductive channel of the compact transistor was modulated by the electric field component in the direction perpendicular to the interface, and the drain current was sensitive to the orientation of the approaching object, which implied the capacity of angle sensing to the approach of a charged object. This work further emphasizes that the basic device performance should be optimized according to its specific application scenarios rather than only considering the requirements of the panel display.

RESUMEN

Advancements in intelligent robots and human-machine interaction necessitate a shift in artificial skins toward multimodal perception. Dual-responsive skins that can detect proximity and pressure information are significant to establishing continuous sensing of interaction processes and extending interactive application scenarios. To address the current limitations of inadequate dual-mode performance, such as limited proximal response change and low tactile sensitivity, this paper presents a bioinspired complementary gradient architecture-enabled (CGA) transduction design and a high-performance dual-responsive skin based on coplanar square-loop electrodes. Through systematic investigation into the transduction of various electrode configurations, comparative results reveal the remarkable potential of coplanar electrodes to deliver superior dual-mode performance without compromise. Simulations and experiments prove that the proposed CGA response mechanism can capture local interface deformation and overall compression signals, further enhancing response sensitivity. The final developed artificial skin is sensitive to external pressure and the approach of objects simultaneously, exhibiting a long detection distance (∼40 mm), a high proximity response (>0.4), and outstanding touch sensitivity (0.131 kPa-1). Furthermore, we demonstrate proof-of-concept applications for the proposed sensing skin in a dual-mode teleoperation interface and adaptive grasping interactions.

Asunto(s)

RESUMEN

This work analyzes a built-in slider detection method for a charge-induction type electrostatic film actuator with a high surface-resistance slider. In the detection method, one stator electrode is detached from the parallel driving electrodes and is dedicated to sensing. When a slider with induced charges moves over the sensing electrode, electrostatic induction occurs in the sensing electrode, which causes an electric current. The current is converted to a voltage through a detection resistance, which will be an output of the sensing circuit. This paper provides a framework to analyze the output signal waveform and shows that the waveform consists of two components. One component is caused by driving voltage and appears regardless of the existence of a slider. The other component corresponds to the movement of a slider, which appears only when a slider is moving over the sensing electrode. Therefore, the slider can be detected by monitoring the latter component. The two components generally overlap, which makes the detection of the latter component difficult in some cases. This paper proposes a method to decouple the two components by switching the detection resistance at an appropriate time. These methods are verified using a prototype actuator that has an electrode pitch of 0.6 mm. The actuator was driven with a set of pulse voltages with an amplitude of 1000 V. The experimental results show similar waveforms to the analytical results, verifying the proposed analytical framework. The performance of the sensing method as a proximity sensor was verified in the experiments, and it was confirmed that the slider can be detected when it approaches the sensing electrode within about 3 mm.

RESUMEN

Sensitive and flexible pressure sensors have invoked considerable interest for a broad range of applications in tactile sensing, physiological sensing, and flexible electronics. The barrier between high sensitivity and low fabrication cost needs to be addressed to commercialize such flexible pressure sensors. A low-cost sacrificial template-assisted method for the capacitive sensor has been reported herein, utilizing a porous Polydimethylsiloxane (PDMS) polymer and a multiwalled carbon nanotube (MWCNT) composite-based dielectric layer. The sensor shows high sensitivity of 2.42 kPa-1 along with a low limit of detection of 1.46 Pa. The high sensitivity originates from adding MWCNT to PDMS, increasing the composite polymer's dielectric constant. Besides this, the pressure sensor shows excellent stability at a cyclic loading of 9000 cycles, proving its reliability for long-lasting application in tactile and physiological sensing. The high sensitivity of the sensor is suitable for the detection of small deformations such as pulse waveforms as well as tactile pressure sensing. In addition, the paper demonstrates a simultaneous contact and non-contact sensing capability suitable for dual sensing (pressure and proximity) with a single data readout system. The dual-mode sensing capability may open opportunities for realizing compact systems in robotics, gesture control, contactless applications, and many more. The practicality of the sensor was shown in applications such as tactile sensing, Morse code generator, proximity sensing, and pulse wave sensing.

Asunto(s)

RESUMEN

Capacitive proximity sensing is widespread in our everyday life, but no sensor for biomedical optics takes advantage of this technology to monitor the probe attachment to the subject's skin. In particular, when using optical monitoring devices, the capability to quantitatively measure the probe contact can significantly improve data quality and ensure the subject's safety. We present a custom novel optical probe based on a flexible printed circuit board which integrates a capacitive contact sensor, 3D-printed optic fiber holders and an accelerometer sensor. The device can be effectively adopted during continuous monitoring optical measurements to detect contact quality, motion artifacts, probe detachment and ensure optimal signal quality.

Asunto(s)

RESUMEN

Most early Bluetooth-based exposure notification apps use three binary classifications to recommend quarantine following SARS-CoV-2 exposure: a window of infectiousness in the transmitter, ≥15 minutes duration, and Bluetooth attenuation below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. We model uncertainty in the shape and orientation of an exhaled virus-containing plume and in inhalation parameters, and measure uncertainty in distance as a function of Bluetooth attenuation. We calculate expected dose by combining this with estimated infectiousness based on timing relative to symptom onset. We calibrate an exponential dose-response curve based on infection probabilities of household contacts. The probability of current or future infectiousness, conditioned on how long postexposure an exposed individual has been symptom-free, decreases during quarantine, with shape determined by incubation periods, proportion of asymptomatic cases, and asymptomatic shedding durations. It can be adjusted for negative test results using Bayes' theorem. We capture a 10-fold range of risk using six infectiousness values, 11-fold range using three Bluetooth attenuation bins, ∼sixfold range from exposure duration given the 30 minute duration cap imposed by the Google/Apple v1.1, and ∼11-fold between the beginning and end of 14 day quarantine. Public health authorities can either set a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration.

Asunto(s)

RESUMEN

Robotics capable of human-like operations need to have electronic skin (e-skin) with not only tactile sensing functions but also proximity perception abilities. Especially, under the current widespread of COVID-19 pandemic, touchless interfaces are highly desirable. Magnetoreception, with inherent specificity for magnetic objects, is an effective approach to construct a non-contact sensing e-skin. In this work, we propose a new touchless sensing mechanism based on the magneto-piezoresistive effect. The substrate of the sensor is made of hierarchically microstructured ferromagnetic polydimethylsiloxane, coated with a three-dimensional (3D) piezoresistive network. The 3D network is constructed by stacked layers of reduced graphene oxide and carbon nanotubes through layer-by-layer deposition. With this integrated design, a magnetic force induced on the ferromagnetic substrate can seamlessly be applied to the piezoresistive layer of the sensor. Because the magnetic force relates strongly to the approaching distance, the position information can be transduced into the resistance change of the piezoresistive network. The flexible proximity sensor exhibits an ultrahigh spatial resolution of 60 µm, a sensitivity of 50.47 cm-1, a wide working range of 6 cm, and a fast response of 10 ms. The repeatable performance of the sensor is shown by over 5000 cycles of approaching-separation test. We also demonstrate successful application of the sensor in 3D positioning and motion tracking settings, which is critical for touchless tactile perception-based human-machine interactions.

RESUMEN

The COVID-19 pandemic has significantly threatened the health and well-being of humanity. Contact tracing (CT) as an important non-pharmaceutical intervention is essential to containing the spread of such an infectious disease. However, current CT solutions are fragmented with limited use of sensing and computing technologies in a scalable framework. These issues can be well addressed with the use of the Internet of Things (IoT) technologies. Therefore, we need to overview the principle, motivation, and architecture for a generic IoT-based CT system (IoT-CTS). A novel architecture for IoT-CTS solutions is proposed with the consideration of peer-to-peer and object-to-peer contact events, as well as the discussion on key topics, such as an overview of applicable sensors for CT needs arising from the COVID-19 transmission methods. The proposed IoT-CTS architecture aims to holistically utilize essential sensing mechanisms with the analysis of widely adopted privacy-preserving techniques. With the use of generic peer-to-peer and object-to-peer sensors based on proximity and environment sensing mechanisms, the infectious cases with self-directed strategies can be effectively reduced. Some open research directions are presented in the end.

Asunto(s)

RESUMEN

Fiber-based sensors are desirable to provide an immersive experience for users in the human-computer interface. We report a hierarchically porous silver nanowire-bacterial cellulose fiber that can be utilized for sensitive detection of both pressure and proximity of human fingers. The conductive fiber was synthesized via continuous wet-spinning at a speed of 20 m/min, with a diameter of 53 µm, the electrical conductivity of 1.3 × 104 S/cm, a tensile strength of 198 MPa, and elongation strain of 3.0% at break. The fibers were coaxially coated with a 10 µm thick poly(dimethylsiloxane) dielectric elastomer to form the fiber sensor element which is thinner than a human hair. Two of the sensor fibers were laid diagonally, and the capacitance changes between the conductive cores were measured in response to pressure and proximity. In the touch mode, a fiber-based sensor experienced monotonic capacitance increase in the pressure range from 0 to 460 kPa, and a linear response with a high sensitivity of 5.49 kPa-1 was obtained in the low-pressure regime (<0.5 kPa). In touchless mode, the sensor is highly sensitive to objects at a distance of up to 30 cm. Also, the fiber can be easily stitched into garments as comfortable and fashionable sensors to detect heartbeat and vocal pulses. A fiber sensor array is able to serve as a touchless piano to play music and accurately determine the proximity of an object. A 2 × 2 array was further shown for two- and three-dimensional location detection of remote objects.

Asunto(s)

RESUMEN

Social distancing and contact/exposure tracing are accepted to be critical strategies in the fight against the COVID-19 epidemic. They are both closely connected to the ability to reliably establish the degree of proximity between people in real-world environments. We proposed, implemented, and evaluated a wearable proximity sensing system based on an oscillating magnetic field that overcomes many of the weaknesses of the current state of the art Bluetooth based proximity detection. In this paper, we first described the underlying physical principle, proposed a protocol for the identification and coordination of the transmitter (which is compatible with the current smartphone-based exposure tracing protocols). Subsequently, the system architecture and implementation were described, finally an elaborate characterization and evaluation of the performance (both in systematic lab experiments and in real-world settings) were performed. Our work demonstrated that the proposed system is much more reliable than the widely-used Bluetooth-based approach, particularly when it comes to distinguishing between distances above and below the 2.0 m threshold due to the magnetic field's physical properties.

Asunto(s)

RESUMEN

Crop mixtures are often beneficial in crop rotations to enhance resource utilization and yield stability. While targeted management, dependent on the local species composition, has the potential to increase the crop value, it comes at a higher expense in terms of field surveys. As fine-grained species distribution mapping of within-field variation is typically unfeasible, the potential of targeted management remains an open research area. In this work, we propose a new method for determining the biomass species composition from high resolution color images using a DeepLabv3+ based convolutional neural network. Data collection has been performed at four separate experimental plot trial sites over three growing seasons. The method is thoroughly evaluated by predicting the biomass composition of different grass clover mixtures using only an image of the canopy. With a relative biomass clover content prediction of R2 = 0.91, we present new state-of-the-art results across the largely varying sites. Combining the algorithm with an all terrain vehicle (ATV)-mounted image acquisition system, we demonstrate a feasible method for robust coverage and species distribution mapping of 225 ha of mixed crops at a median capacity of 17 ha per hour at 173 images per hectare.

RESUMEN

Social bonds, maintained by mutual investments of time and energy, have greatly influenced the evolution of social cognition and cooperation in many species [e.g., 1-8]. However, there are two pitfalls regarding "social bonds" as an explanation for social structure and cooperation [1, 9-11]. First, studies often incorrectly assume that frequent association implies partner fidelity based on mutual social preference, but even seemingly complex nonrandom interaction networks can emerge solely from habitat or spatial structure [12-16]. Second, the false appearance of partner fidelity can result from stable options in the "partner market" [1, 9-11, 17]. For instance, individuals might preferentially groom the same partner, even if the decision depends entirely on the immediate costs and benefits rather than relationship history. Given these issues, a key challenge has been testing the extent to which social structure is driven by the intrinsic relationship history versus the extrinsic physical and social environment. If stable bonds exist, they should persist even if the individuals are moved to a dramatically different physical and social environment. We tested this prediction by tracking social relationships among common vampire bats (Desmodus rotundus) moved from the lab to the wild. We show that allogrooming and food sharing among female vampire bats induced in captivity over 22 months predicted their assortativity and association rates when we subsequently tracked them in the wild with custom-made high-resolution proximity sensors. The persistence of many relationships across different physical and social environments suggests that social structure is caused by both extrinsic constraints and intrinsic partner fidelity.

Asunto(s)

RESUMEN

Optimal fertilization of clover-grass fields relies on knowledge of the clover and grass fractions. This study shows how knowledge can be obtained by analyzing images collected in fields automatically. A fully convolutional neural network was trained to create a pixel-wise classification of clover, grass, and weeds in red, green, and blue (RGB) images of clover-grass mixtures. The estimated clover fractions of the dry matter from the images were found to be highly correlated with the real clover fractions of the dry matter, making this a cheap and non-destructive way of monitoring clover-grass fields. The network was trained solely on simulated top-down images of clover-grass fields. This enables the network to distinguish clover, grass, and weed pixels in real images. The use of simulated images for training reduces the manual labor to a few hours, as compared to more than 3000 h when all the real images are annotated for training. The network was tested on images with varied clover/grass ratios and achieved an overall pixel classification accuracy of 83.4%, while estimating the dry matter clover fraction with a standard deviation of 7.8%.

RESUMEN

In this paper, we present a tiny networked mobile platform, termed Tiny-Web-Thing (T-Wing), which allows the sharing of data-intensive content among objects in cyber physical systems. The object includes mobile platforms like a smartphone, and Internet of Things (IoT) platforms for Human-to-Human (H2H), Human-to-Machine (H2M), Machine-to-Human (M2H), and Machine-to-Machine (M2M) communications. T-Wing makes it possible to host rich web content directly on their objects, which nearby objects can access instantaneously. Using a new mechanism that allows the Wi-Fi interface of the object to be turned on purely on-demand, T-Wing achieves very high energy efficiency. We have implemented T-Wing on an embedded board, and present evaluation results from our testbed. From the evaluation result of T-Wing, we compare our system against alternative approaches to implement this functionality using only the cellular or Wi-Fi (but not both), and show that in typical usage, T-Wing consumes less than 15× the energy and is faster by an order of magnitude.

RESUMEN

Electronic skins need to be versatile and able to detect multiple inputs beyond simple pressure and touch while having attributes of transparency and facile manufacturability. Herein, we demonstrate a versatile nanostructured transparent sensor capable of detecting wide range of pressures and proximity as well as novel nonoptical detection of printed patterns. The architecture and fabrication processes are straightforward and show robustness to repeated cycling and testing. The sensor displays good sensitivity and stability from 30 Pa to 5 kPa without the use of microstructuration and is conformal and sensitive to be utilized as a wrist-based heart-rate monitor. Highly sensitive proximity detection is shown from a distance of 9 cm. Finally, a unique nonoptical pattern recognition dependent on the difference in the dielectric constant between ink and paper is also demonstrated, indicating the multifunctionality of this simple architecture.