Bending Sensor Research Articles

High-Resolution Femtosecond Laser-Induced Carbon and Ag Hybrid Structure for Bend Sensing.

Miniaturized resistance-based portable bending sensors have been widely used for human health monitoring in recent years. Their sensitivities are defined by their resistance variations (ΔR/R), which strongly rely on the conductivity and minimum line width of the sensing unit. Laser-induced carbonization is a fast and simple method to fabricate porous-sensing structures. However, the fabrication resolution of conductive and deformation-sensitive structures is limited by the thermal effect of commonly used laser sources. With the assistance of femtosecond laser temporal shaping, plasma ejection confinement, and silver nitrate doping, the sheet resistance of the sensing structure was improved from 15 to 0.0004 Ω/□. A thin line with a lateral resolution of 6.5 μm is fabricated as the sensing unit. The fFabricated structures are characterized by electron microscopy, Raman spectroscopy, energy-dispersive spectroscopy, X-ray scattering, and time-resolved images. The strain sensor demonstrates a ΔR/R of 25.8% with a rising edge of 109 ms in the cyclic bending test. The sensor is further applied for detecting human pulse and finger bending.

Two-dimensional vector bending sensor based on a hole-assisted three-core fiber coupler.

We demonstrate a two-dimensional vector bending sensor based on a hole-assisted three-core fiber (HATCF) coupler. The sensor is built by splicing a section of HATCF between two single-mode fibers (SMFs). The resonance couplings between the center core and the two suspended cores of the HATCF occur at different wavelengths. Two completely discrete resonance dips are observed. The bending response of the proposed sensor is investigated over a 360° range. The bending curvature and direction can be identified by interrogating the wavelengths of the two resonance dips, and a maximum curvature sensitivity of -50.62 nm/m-1 is achieved at 0° direction. Moreover temperature sensitivity of the sensor is less than -34.9 pm/°C.

Physics-Based Circuit Modeling of the Impedance Characteristics of a Smart Hydrogel-Actuated Bending Sensor.

Smart hydrogels are stimuli-responsive polymers which exhibit a volume-phase transition in response to external influences. This makes them promising candidates for sensing elements, especially in a biomedical context due to their easily achievable biocompatibility. The main challenge in harnessing the smart polymer's potential for sensor applications lies in a reliable transduction of the swelling change into an electrical signal. A novel platform approach is based on a bending sensor where the smart hydrogel acts as an actuator on a thin film with embedded metal traces. Mechanical deformation due to the hydrogel volume change alters the traces' electric impedance. However, besides deformation, the medium surrounding the sensor structure will also affect the impedance. For sensor design it is therefore crucial to understand the complex interdependencies between electric sensor properties, influences of the surrounding medium and mechanical deformation. Here, an electric circuit model is presented which considers all these contributions through a minimum number of lumped elements and is strictly based on physical considerations. By employing measured impedance spectra from an experimental sensor implementation subjected to different surrounding media and mechanical deformation, the validity of the simplified model is demonstrated. A detailed analysis and discussion give insights into the determination of the different model parameters and how external influences can clearly be attributed to specific circuit elements. This work provides a general approach for deducing minimalistic but strictly physics-based circuit models which can still adequately replicate the actual behavior of such types of impedance-based bending sensors.

Operation of Wireless Humanoid Robot using Graphene Embedded Bend Sensor and Internet of Things Technology

The use of Robots is a trending technology but automation and Artificial Intelligence are not fully achieved till date. This paper aims to propose an innovative system to integrate human intelligence with Robotics. The robots which have been designed to work in harsh conditions are controlled using graphene-based flexible bend sensors. These sensors are applied to the human body and are powered by solar energy. Here a flexible sensor is applied on each bend on the human body and respective data of bend angle is transmitted to the raspberry pi 3 model B kits which are programmed to act accordingly and the same bend is obtained in the Robot. The sensor which we have used in this project removes the messy wiring and there is no need to wear any kind of suit. The required movements for the robot are produced by a human after applying the sensors on each joint. It looks like a pasting that is pasted across the joint. These sensors are made from a biocompatible material, thus does not have any dermatological ill effect on the operator. The graphene-based sensor has a subsequent role in robotics as they develop position matrices that determine the current position of various members of the humanoid robot. Robotic application demands sensors with a higher degree of repeatability, precision, and reliability which is obtained using the Graphene-based bend sensors. Each sensor is self-capable to carry out motion of one degree of motion. The use of an accelerometer attached along with the sensor helps to control the speed of robotic operation. This system is suitable to control the robot from a distance and uses it in critical conditions with the intelligence of the human being who is operating it, the rise in temperature leads to an increase in the time-lapse in command and action. But still, it can be treated as the substitute for artificially intelligent robots as we have not reached the level of intelligence in human beings. This work is based on the combined concepts of mechanical, computer, and electronics engineering.

Noninvasive Evaluation of the Biomechanical Accommodations to Bolus Volume during Human Swallowing.

Bolus volume is very important in the biomechanics of swallowing. By noninvasively characterizing swallow responses to volume challenges, we can gain more knowledge on swallowing and evaluate swallowing behavior easily. This study aimed to evaluate the impact of bolus volume on the biomechanical characteristics of oropharyngeal swallowing events with a noninvasive sensing system. Fifteen healthy male subjects were recruited and instructed to swallow 5, 10, and 15 ml of water. The sensing system consisted of a tongue pressure sensor sheet, bend sensor, surface electrodes, and a microphone. They were used to monitor tongue pressure, hyoid activity, surface EMG of swallowing-related muscles, and swallowing sound, respectively. In addition to the onset, the peak time and offset of the above four structures, certain characteristics, such as the duration, peak value, and interval of the structure motions, were measured during the different drinking tasks. The coordination between the hyoid movement and tongue pressure was also assessed. Although no sequence of the structural events changed with volume, most of the timings of the structural events were significantly delayed, except for certain hyoid activities. The swallowing volume did not affect the active durations of the monitored structures, the peak values, or intervals of tongue pressure and supra- and infrahyoid muscle activity, but certain hyoid kinetic phases were prolonged when a larger volume was swallowed. Additionally, sequential coordination between hyoid movement and tongue pressure was confirmed among the three volumes. These findings suggest that oropharyngeal structural movements change in response to bolus volume to facilitate safe swallowing. The noninvasive and quantitative measurements taken with the sensing system provide essential information for understanding normal oropharyngeal swallowing.

Continuum-Body-Pose Estimation From Partial Sensor Information Using Recurrent Neural Networks

Soft continuum arms have significant potential for use in various applications due to their extremely high degrees of freedom. For example, these soft arms can be used for grasping and manipulating fragile materials in the deep sea or carrying a human to rescue in unstructured environments. However, in these situations, the environment is often dark and visual cues are not always usable. Therefore, these arms must estimate their pose from proprioceptive sensors to control their behavior and execute their tasks in dark places. Estimating the pose in a dynamic situation is still challenging because of the arms' high dimensionality and the complex structural changes in the body shape. Therefore, this study demonstrates a novel method for estimating the pose of proprioceptive bending sensors using recurrent neural networks (RNNs). In particular, an RNN framework known as deep reservoir computing was used for this purpose. Results from experiments using an octopus-inspired soft robotic arm clearly indicate that the proposed method significantly outperforms existing methods using long short-term memory models or linear models. We expect that our proposed method will enable behavioral control of these arms in dark places such as the deep sea, space, and inside the human body in future applications.

Direct ink writing of reinforced polydimethylsiloxane elastomer composites for flexure sensors

AbstractFlexible materials with ideally designed structures and properties through direct ink writing (DIW) offer vast potential for flexible wearable devices, sensors, soft robots, and so on. Despite its common use as a flexible material, Sylgard‐184's poor rheological properties restrict its ability of printing precision models by DIW. Herein, we have improved the viscosity of Sylgard‐184 by adding suitable crosslinkers and silica, which produce inks with high printing quality and a low slump rate (3.75%). In addition, the DIW printing process was investigated, and a theoretical model relating to the basic printing parameters was developed. With the model, it is possible to predict printing parameters for various elastomers. To further demonstrate the application of this strategy to flexible wearable devices, a sensor was printed. The sensor allowed real‐time monitoring of bending angles through bending angle tests. A change from 0 to 135° was detected using this bending sensor. We believe that the results of this research will provide ideas for the high‐quality printing of silicone elastomers.

Silver-Reduced Poly(Ethylene Glycol) Diacrylate Composites with Microline Arrays for Directional Bending Sensors.

Herein, a soft and flexible polymer composite sensor with a surface structure is manufactured that is sensitive to a wide range of mechanical stimuli, including small actions and large motions. A polymer sensor performing with a piezoresistive mechanism is proposed by synthesizing a new conductive polymer composite to fabricate a microline structure by itself, named Ag-reduced poly(ethylene glycol) diacrylate (PEGDA) composite directional bending sensor (ACBS). A simple but effective process of forming nanoparticles (NPs) and surface structures is a notable characteristic. High sensitivity to a small stimulus was achieved by forming Ag NPs within PEGDA, particularly concentrating on the surface and applying the microline structure. With the structural characteristics of a line structure, the ACBS achieved anisotropic sensitivity to bulk motion along the arranged line direction. The excellent sensitivity of this polymer sensor was experimentally demonstrated via water droplets, blowing, and breathing. Combining the advantages of a simple synthetic and simple fabrication process along with the fabrication ability of the microsurface structure with the material itself and the conductive Ag/PEGDA integrated layer, this ACBS is outstanding as a soft and flexible polymer composite sensor and has potential application in physical devices such as wearable devices and biosensors.

A novel method of elimination of light polarization cross sensitivity on tilted fiber Bragg grating bending sensor

A novel method of elimination of light polarization cross sensitivity on tilted fiber Bragg grating bending sensor

Vector bending sensor for measuring spine curvature

A three-core photonic crystal fiber (TCPCF) vector bending sensor for measuring spine curvature is proposed. Refractive index variations of the TCPCF due to the wavelength differences in the range of 1.25 to 1.85 μm are studied. We show a linear relation between refractive index and operating wavelength. The wavelength of 1.55 μm is chosen for simulation with high energy modules to compensate for bending loss. An asymmetrical fiber is designed to sense both the direction and magnitude of the curve. The asymmetrical geometry of fiber creates an asymmetrical refractive index profile that leads to shifts in light speed in different fiber sections. This geometry asymmetry, in turn, provides the information needed to calculate both variables. Bending effects on the TCPCF has been numerically studied by the finite element method. Data analysis shows that the proposed sensor is sensitive to bending with a sensitivity of 1.2199 pm.m. It also reveals high directional sensing.

Highly Sensitive Bending Sensor Based on Multicore Optical Fiber With Diagonal Cores Reflector at the Fiber Tip

A high-sensitivity bending sensor based on multi-core fiber Bragg gratings (MCFBGs) is presented and demonstrated. The bending sensor is based on FBGs fabricated on the symmetric distribution cores of seven-core fiber (SCF), where a 45-degree reflective cone frustum (RCF) is fabricated at the fiber end. The optical paths of two symmetric cores are connected by the 45-degree RCF. The wavelength drifts of the two FBGs on the symmetric cores caused by bending were similar in magnitude and opposite in direction, while the wavelength drifts of the two FBGs caused by temperature were similar in magnitude and direction. Therefore, the influence of temperature change on the curvature measurement can be automatically eliminated, and the bending sensitivity can be doubled by calculating the difference between the reflected wavelengths of the two FBGs. The sensor's spectral responses to the curvature at different bending directions are experimentally investigated. The maximum curvature sensitivity of the sensor is 225.9 pm/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> , within the curvature range from 0 to 6.9 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> .

Sawtooth Fiber MZ Vector Bending Sensor Available for Multi Parameter Measurement

In this paper, a fiber Mach Zehnder (MZ) interferometer based on sawtooth structure was proposed. It not only has the ability of bending sensing and bending direction recognition, but also can be applied to multi parameter sensing. Here we established the fiber hetero core structure with single mode fiber-multimode fiber-single mode fiber (MSM), and then fabricated the sawtooth structure on the single mode fiber in the middle by CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> laser. Since part of the cladding on the single-mode fiber was removed, the fiber core was no longer at the neutral plane. When the sensor is bent in the 0° direction or 180° direction, the effective refractive index and optical path length of the core mode will increase or decrease, resulting in the increase or decrease of the optical path difference between the core mode and the cladding mode. And then the interference wavelength will show a red shift or blue shift, so as to realize the curvature sensing with bending direction recognition. Meanwhile, due to the local stress of the sawtooth structure in the bending, the sensitivity of the bending sensor is improved. The testing results indicate that the sensitivity of 0° bending and 180° bending are −15.16 nm/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> and 8.32 nm/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> with the curvature range of 0–1 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> . Moreover, the sawtooth structure sensor has excellent performance in strain, temperature and torsion sensing. The torsional sensitivity of the sensor reaches −0.30 nm/(rad/m) with torsional range of 0–13.96 rad/m, the temperature sensitivity reaches 58.90 pm/°C, and the strain sensitivity reaches −3.62 pm/μϵ. In strain sensing, there are some interference valleys insensitive to strain, which can realize the simultaneous measurement of other parameters and strain.

Flexible unimodal strain sensors for human motion detection and differentiation

Multiple strain sensors are required to identify individual forces/stresses on human joints and recognize how they work together in order to determine the motion’s direction and trajectory. However, current sensors cannot detect and differentiate the individual forces/stresses and their contributions to the motion from the sensors’ electrical signals. To address this critical issue, we propose a concept of unimodal tension, bend, shear, and twist strain sensors with piezoelectric poly L-lactic acid films. We then construct an integrated unimodal sensor (i-US) using the unimodal sensors and prove that the i-US can detect and differentiate individual strain modes, such as tensioning, bending, shearing, and twisting in complex motion. To demonstrate the potential impact of unimodal sensors, we design a sleeve and a glove with the i-US that can capture wrist motions and finger movements. Therefore, we expect unimodal strain sensors to provide a turning point in developing motion recognition and control systems.

Mach-Zehnder-Sagnac interferometric curvature sensor based on polarization-maintaining multi-mode fiber using a specified core offset.

An interferometric bending sensor based on polarization-maintaining fiber (PMF) in combination with multi-mode fiber (MMF) is proposed and demonstrated experimentally. One end of MMF was fusion spliced to PMF, and the other was fusion spliced to the single mode fiber (SMF) pigtail of a 3 dB optical fiber coupler with a core offset. One stress zone in lead-out Panda type PMF was intentionally aligned and fusion spliced to the core of SMF to enhance mode coupling. A pronounced interference pattern with a fringe contrast of 28.1 dB was obtained, and a bending sensitivity of 18.66nm/m-1 was achieved experimentally. Such a bending sensor with easy fabrication could be a potential candidate for curvature measurements.

Bending sensor based on flexible spin valve

Flexible spin valves were prepared by magnetron sputtering on polyimide substrates. The buffer layer that reduces significantly the effect of the polymer substrate on the spin valve microstructure and magnetoresistive properties was revealed. Bending deformation was applied to the microobjects based on the flexible spin valves in parallel to anisotropy axes. It was revealed that during the bend the magnetoresistance changes due to the joint impact of both the change of the magnetic field projection on the film plane and the change of the magnetic properties of the ferromagnetic layers. The obtained dependences have been used in construction of bending sensor, in which the flexible spin valve microstripes were united into the Wheatstone bridge.

Recent Progress in Development and Applications of Ionic Polymer-Metal Composite.

Electroactive polymer (EAP) is a polymer that reacts to electrical stimuli, such as voltage, and can be divided into electronic and ionic EAP by an electrical energy transfer mechanism within the polymer. The mechanism of ionic EAP is the movement of the positive ions inducing voltage change in the polymer membrane. Among the ionic EAPs, an ionic polymer–metal composite (IPMC) is composed of a metal electrode on the surface of the polymer membrane. A common material for the polymer membrane of IPMC is Nafion containing hydrogen ions, and platinum, gold, and silver are commonly used for the electrode. As a result, IPMC has advantages, such as low voltage requirements, large bending displacement, and bidirectional actuation. Manufacturing of IPMC is composed of preparing the polymer membrane and plating electrode. Preparation methods for the membrane include solution casting, hot pressing, and 3D printing. Meanwhile, electrode formation methods include electroless plating, electroplating, direct assembly process, and sputtering deposition. The manufactured IPMC is widely demonstrated in applications such as grippers, micro-pumps, biomedical, biomimetics, bending sensors, flow sensors, energy harvesters, biosensors, and humidity sensors. This paper will review the overall field of IPMC by demonstrating the categorization, principle, materials, and manufacturing method of IPMC and its applications.

Fiber-optic amplitude bend direction and magnitude sensor

A variant of the implementation of a fiber-optic sensor for the direction and magnitude of the bend is proposed. Unlike existing spectral measuring systems, the solution under consideration involves the use of an amplitude polling technique which makes it possible to increase the speed of the sensor when using simpler and more affordable components. A sensitive element based on special diffraction structures consisting of pairs of chirped fiber Bragg gratings has been studied. The sensing elements are mounted on a tooling — a steel rod subjected to bending. The ability of the sensor to determine the magnitude and direction of bending in the deviation range from 0 to 30 mm was demonstrated with a standard deviation of the measured values from the real values of 0.536 mm. This measurement result is achieved by processing data obtained from three measuring devices and by the neural network with a hidden layer of 10 neurons and the sigmoid as the activation function. The research results are essential for modern monitoring systems. The implementation of the direction and magnitude of the bend sensor in the format of a fiber-optic device allows you to overcome the limitations of piezoelectric sensors, due to high noise immunity and resistance to environmental influences. The proposed technological solution makes it possible to avoid the spectral measurement technique that has become widely used in fiber-optic sensor systems. The use of an amplitude sensor for the magnitude and direction of bending will allow its use in devices where there is a need for precise positioning of control elements or structural components subjected to bending. Also, due to the measurement of the desired bending effect by estimating the optical power of the signal, the design of the sensor does not require the presence of a complex measuring device, and the sensor’s performance can be ensured using a cascade of inexpensive, but at the same time high-speed and durable photodetectors.

Temperature-Insensitive Two-Dimensional Vector Bending Sensor Based on Fabry-Pérot Interferometer Incorporating a Seven-Core Fiber

We proposed and experimentally demonstrated a temperature-insensitive two-dimensional (2D) vector bending sensor on the basis of Fabry-Pérot Interferometer (FPI). The sensor is fabricated by splicing a section of silica capillary optical fiber (COF) between a trench-assisted seven-core fiber (SCF) and a multimode fiber (MMF). For orientation angle from 0° to 360°, the vector bending responses of six outer-core FPIs were studied at a step of 30°. From experimental results, the proposed sensor exhibits strong bending-direction dependence, and the maximum sensitivity is 200.6 pm/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> . The curvature magnitude and orientation angle can be reconstructed through the dip wavelength shifts of any two off-diagonal outer-core FPIs. Hence, there are 12 various combinations from six outer-core FPIs, and the average value can be taken in multiple reconstructions to develop exact 2D vector bending measurement. For curvature magnitude and orientation angle reconstructed, the average relative error is 6.2% and 3.3%, respectively. In addition, experiments verified the proposed sensor is insensitive to ambient temperature changes.

Multicore Fiber Bending Sensors with High Sensitivity Based on Asymmetric Excitation Scheme.

Bending sensing was realized by constructing a tapered four-core optical fiber (TFCF) sensor. The four-core fiber (FCF) between the fan-in and fan-out couplers was tapered and the diameter became smaller, so that the distance between the four cores arranged in a square became gradually smaller to produce supermodes. The two ends of the TFCF were respectively connected to the fan-in and fan-out couplers so that the individual cores in the FCF could link to the separate single-mode fibers. A broadband light source (superluminescent diodes (SLD)) spanning 1250–1650 nm was injected into any one of the four cores, and the orientation was thus determined. In the tapering process, the remaining three cores gradually approached the excitation core in space to excite several supermodes based on the tri-core structure first, and then transited to the quadruple-core structure. The field distributions of the excited supermodes were asymmetric due to the corner-core excitation scheme, and the interference thus resulted in a higher measurement sensitivity. When the diameter of the TFCF was 7.5 μm and the tapered length was 2.21 mm, the sensitivity of the bending sensor could reach 16.12 nm/m−1.

Learning to sense three-dimensional shape deformation of a single multimode fiber

Optical fiber bending, deformation or shape sensing are important measurement technologies and have been widely deployed in various applications including healthcare, structural monitoring and robotics. However, existing optical fiber bending sensors require complex sensor structures and interrogation systems. Here, inspired by the recent renewed interest in information-rich multimode optical fibers, we show that the multimode fiber (MMF) output speckles contain the three-dimensional (3D) geometric shape information of the MMF itself. We demonstrate proof-of-concept 3D multi-point deformation sensing via a single multimode fiber by using k-nearest neighbor (KNN) machine learning algorithm, and achieve a classification accuracy close to 100%. Our results show that a single MMF based deformation sensor is excellent in terms of system simplicity, resolution and sensitivity, and can be a promising candidate in deformation monitoring or shape-sensing applications.