Sensor For Detection Research Articles

Fe(OH)3/Ti3C2Tx nanocomposites for enhanced ammonia gas sensor at room temperature

Two-dimensional material (2D material) MXene has great application potential in gas sensors because of its excellent controllable performance and vast specific surface area. In this study, we used a straightforward in-situ electrostatic self-assembly technique to create Fe(OH)3/Ti3C2Tx nanocomposites, which were then used to fabricate gas sensors for ammonia detection at room temperature (25 ℃). Several characterization methods were performed aimed at determining the surface appearance and construction of the nanocomposites, and the sensing characteristics and mechanism were also systematically examined. The findings demonstrate the effective incorporation of amorphous Fe(OH)3 nanoparticles on the surface of Ti3C2Tx. Additionally the nanocomposites of Fe(OH)3/Ti3C2Tx have considerably higher specific surface area than pure Ti3C2Tx, hence offering more active NH3 adsorption sites. The response of the sensor to 100 ppm NH3 was 48.6% at room temperature, which was 9.3 times more higher than that of pure Ti3C2Tx. The sensors also have the advantages of long-term stability (33 days), low NH3 detection limit (500 ppb), and rapid recovery time (85 s) and response times (78 s). It is anticipated that this work will be helpful for developing the new generation of wearable ammonia sensors at room temperature.

Simple and rapid multicolor sensor for seminal plasma ROS detection based on synergistic catalytic etching of gold nanobipyramids dopped agarose composite gel

Excessive reactive oxygen species (ROS) in seminal plasma can trigger male infertility. Therefore, the development of simple and rapid ROS detection methods is urgently needed, particularly for the early self-screening of preconception couples. Herein, a gold nanobipyramid (Au NBP)-based colorimetric hydrogel for convenient and fast ROS detection is described. In the hydrogel, Au NBP is etched efficiently by ROS under the synergistic effect of Fe2+and I−, which finally causes color variations. Besides, agarose gel with the function of molecular sieve enables the separation of biomacromolecules, improving the interference resistance of the system and the stability of Au NBP. This chemical sensor can complete all the tests within 20 min, covering two detection range of 10–125 μM at relative low H2O2 concentration and 125–1000 μM at relative high H2O2 concentration, with the detection limits of 1.76 μM and 12.10 μM (S/N = 3) respectively. Furthermore, via visual observation of the color variations, it allows the initial interpretation of ROS concentration without any additional equipment. We applied this device to the detection of ROS in clinical seminal plasma samples and obtained promising results, demonstrating its potential for rapid and convenient detection in clinical applications.

A ring resonators optical sensor for multiple biomarkers detection

In the recent years, the number of Point-Of-Care-Tests (POCTs) available for clinical diagnostic has steadily increased. POCTs provide a near-patient testing with the potential to generate a result quickly so that appropriate treatment can be implemented, leading to improved clinical outcomes compared to traditional laboratory testing. Technological advances, such as miniaturization of sensors and improved instrumentation, have revolutionized POCTs, enabling the development of smaller and more accurate devices. In this context, it has also gained increasing importance the screening of various analytes simultaneously to increase specificity and improve the characterization of the disease. This study is aimed at developing and characterizing a photonic integrated circuit for multiple markers detection, which represents the functional core towards a full developed POCT device for clinical pathology applications. The photonic sensor, based on microring resonators (MRRs), is functionalized by immobilizing specific antibodies on a copolymer layer deposited on the MRR’s surfaces. Surface chemical techniques were employed to analyse the surface chemical characteristics while fluorescence microscopy was involved to analyse the resulting bioreceptor surface density. The photonic sensor is characterized for the parallel detection of two biomarkers, the C-Reactive Protein (CRP) and the Creatine-Kinase-MB (CK-MB). The analyte-antibody binding curves were obtained both in buffer and in filtered un-diluted artificial saliva showing promising results both in terms of sensitivity, with limit of detection (LOD) of 103 pM for CRP and 140 pM for CK-MB, and in terms of specificity. These encouraging results let the assembly of a highly sensitive POC device for molecular diagnostics.

Convolutional variational autoencoder and multi-scale attention convolutional neural network based diagnostics on filament current sensors for mass spectrometers

Fault detection of the filament current sensor of the spaceborne mass spectrometer is of great significance to the safe operation of the mass spectrometer. Neglecting sensor failures may affect the normal operation of the mass spectrometer, which in turn affects the health of the astronauts and the space missions. This paper proposes an enhanced intelligent diagnosis method based on filament current sensor for mass spectrometer via improved deep learning network, aiming to improve the accuracy and reliability of the filament current sensor when the fault samples are insufficient. The improved convolutional variational autoencoder (CVAE) model not only enhances the data for four typical sensor fault signals, namely bias, drift, missing and random, but also solves the problem of insufficient samples when spike, Precision degradation and stuck fault occur in sensors. Short-time Fourier transform (STFT) is utilized to transform one-dimensional data into two-dimensional spectrograms, which gives more fault characteristics to the data set. The improved multi-scale attention mechanism convolutional neural network (MSAM-CNN) model is constructed to perform fault diagnosis on the generated spectrogram, which solves the problem of low accuracy of fault identification in traditional convolutional neural network (CNN) models. The results of ablation and comparison experiments show that the samples generated by CVAE have smaller Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE), the enhanced samples improve the classification and clustering of MSAM-CNN, and compared to other diagnostic models, MSAM-CNN achieves the highest accuracy, precision, recall, and F1-score of 99.2%, 99.3%, 98.8%, and 0.991.

Environmentally friendly screen-printed electrodes for the selective detection of 4-bromo-2,5-dimethoxyphenethylamine (2C-B) in forensic analysis.

In response to the growing need for sustainable analytical methods, this study explores the repurposing of screen-printed electrodes (SPEs) that would otherwise be discarded. This involves recoating the working electrode surface with a graphite (Gr) and chitosan (CTS) dispersion, creating a reusable SPE (SPE-Gr/CTS). Demonstrating its utility, SPE-Gr/CTS was employed for the detection of 4-bromo-2,5-dimethoxyphenethylamine (2C-B), a phenylethylamine commonly used for recreational proposes. Identifying 2C-B in fluid oral and seized samples is of great interest for forensic and toxicological applications. The 2C-B detection using SPE-Gr/CTS was optimized in Britton-Robinson buffer solution (0.1 mol L-1) at pH 2.0, employing square-wave adsorptive stripping voltammetry. The electrochemical behavior of 2C-B on SPE-Gr/CTS exhibited one irreversible oxidation and a reversible redox process. The proposed method presented a dynamic linear range for 2C-B determination (0.05 to 7.5 μmol L-1) with a low LOD (0.015 μmol L-1). Moreover, the stability of 2C-B electrochemical responses on SPE-Gr/CTS was confirmed using the same or different electrodes (N = 3), with a relative standard deviation of less than 5.0%. Interference studies with seventeen other illicit drugs and adulterants demonstrated that the proposed method is selective for 2C-B detection even in the presence of these substances. Real seized and oral fluid samples containing 2C-B were analyzed using this method, and the results were confirmed by LC-MS. The proposed device demonstrates to be an environmentally friendly and selective sensor for 2C-B detection in forensic analysis, offering a rapid and straightforward screening method for seized and biological samples. In addition, a portable and sensitive determination of 2C-B in forensic samples is presented with minimal sample consumption (50 μL).

Highly sensitive and selective rGO-LaFeO3 nanocomposite based formaldehyde sensors towards air quality monitoring

Formaldehyde (HCHO), a ubiquitous volatile organic compound and recognized human carcinogen, is extensively used in industrial applications such as resin and adhesive production. Even minimal exposure to HCHO can induce serious health effects, including respiratory distress and dermal irritation. Thus, the advancement of highly sensitive and selective sensors for HCHO detection is imperative for safeguarding environmental and indoor air quality. Herein, we report the development of a very sensitive, highly selective, and stable HCHO sensor based on reduced graphene oxide (rGO) and lanthanum ferrite (LaFeO3). LaFeO3 and rGO-LaFeO3 nanocomposites with different compositions were synthesized through an affordable and straightforward sol-gel process. Among them, the LFGO(50:1) sensor demonstrated the highest response and selectivity towards HCHO, with a detection limit (theoretically) as low as 19 ppb (1.5 fold). Notably, it exhibited approximately 15-fold p-type response to 1 ppm of HCHO, while operating at 260°C. The sensor also showed quick response and recovery times of around 1.5 seconds and 36 seconds, respectively while having negligible response to other VOCs, including ethanol, methanol, and NH3. A synergistic effect of rGO and LaFeO3 is attributed to this improved sensing behavior. rGO offers a large surface area that facilitates the adsorption of HCHO molecules, while LaFeO3 acts as a catalyst for the oxidation of HCHO. The sensor also showed good selectivity, stability, and reproducibility, making the material a promising candidate for practical applications towards environment monitoring, indoor air quality control, and industrial safety.

An In2O3/In2S3 photoanode-driven whole-cell biocathode sensor for sensitive detection of nitrate

Whole-cell biocathode sensor is a new form of self-regenerable biosensor and promising for environmental monitoring especially in the scenario with low organic substrate. However, external power supply such as electrochemical workstation is required to drive the biocathode reaction, which greatly limits its application. Herein, a new strategy based on the visible-light-driven whole-cell biocathode was proposed and validated for self-powered sensitive detections. To be specific, 1-OH phenazine was selected as the optimal electron shuttle for a Shewanella oneidensis MR-1 inoculated biocathode, which efficiently mediate the cathodic reaction at an electrode potential below −0.6 V (vs. SCE). Meanwhile, an In2O3/In2S3 photoanode with nanoflower-like structure was fabricated to match the kinetic of the biocathode. The photo-driven biocathode reduction was convinced by comparing with the performance of biocathode in the conventional three-electrode system. With this basis, a self-powered whole-cell biocathode sensor was developed for nitrate detection. An extreme low limit of detection of 0.028 μM (S/N=3) and linear detection range of 0.1–20 μM was achieved. Moreover, this biocathode sensor also exhibited excellent selectivity, reusability, accuracy, stability and was reliable for the detection of complex environmental samples. Therefore, this work developed a new photo-driven whole-cell biocathode sensor with excellent detection capacity of nitrate, which opens up new prospects for the development of high-performance biosensors.

Surface Roughness Evaluation of Blast-Cleaned Structural Steel Plates Considering Measurement Deviation

AbstractSurface roughness is an important characteristic of blast-cleaned structural steel plates. This is because the adhesion of the coating and the frictional grip of the bolted connections are related to surface roughness. Surface roughness is usually measured using a surface roughness meter. Because the roughness of blast-cleaned surfaces is not uniform, it varies from position to position. The surface roughness test results obtained from a broad area are more valuable than those obtained from a narrow area. Because the measured values contain deviations, they are measured multiple times and averaged to reduce the influence of deviations. However, to evaluate roughness, it is necessary to clarify the measurement conditions to obtain accurate results. Consider combining these sentences as follows: In this study, the surface roughness of the blast-cleaned structural steel sample was measured at multiple locations to obtain its distribution characteristics. During each sample measurement, the detection sensor of the surface roughness meter was lifted and placed on the steel sample to determine deviations from the actual results. The surface roughness distributions of five blast-cleaned samples were the same under the identical measurement conditions. This indicates that accurate results can be obtained by measuring representative samples, without the need for measuring all samples; actually, 17 measurements were adequate to obtain a mean surface roughness value with a 95% confidence level and a 5% acceptable error rate.

IoT Based Precision Farming

This project focuses on leveraging drone images of the pests equipped with advanced sensors for pest detection in crops, combined with methods for image processing to identify diseases. The ultimate goal is to enhance crop health and productivity through timely and targeted pesticide application. Image processing techniques are used to detect signs of diseases and pests in the captured images. The use of machine learning CNN algorithm enhances the system’s ability to accurately classify and diagnose crop heath issues. Upon detection of pests, the IOT platform triggers a response mechanism to deploy a precision pesticide spraying system. This ensures targeted and localized treatment, reducing the overall use of pesticides and minimizing environmental impact. This project involves capturing images of pests using a camera, followed by processing these images to extract key features using various image processing techniques. The extracted features are analyzed using algorithms, primarily Convolutional Neural Networks (CNNs), to detect variations in color and other dominant characteristics in the images. By comparing these features across samples, the system can identify pests and plant diseases more efficiently. This approach aims to provide a quicker and more cost-effective solution for pest detection and disease management.

Highly fluorescent nitrogen doped carbon dots as analytical probe for sensitive detection of curcumin through smartphone integrated 3D-printed platform: A new horizon in food safety

COVID-19 pandemic has significantly influenced the dietary habits of humans, emphasizing the incorporation of natural ingredients to enhance immunity towards viral and bacterial infections. Curcumin (Cur), a widely used traditional medicine in various Asian countries and a natural coloring agent, has gained popularity, leading to surge in its usage specially in post COVID-19 era. This surge has led to increased scrutiny of the potential side effects of excessive Cur use, with recent reports suggesting it may result in inactivation of DNA and reduce adenosine triphosphate levels, leading to health risks. In this work, we synthesized highly fluorescent nitrogen-doped carbon dots with a photoluminescence quantum yield of 72.9 % for the sensitive and selective detection of Cur. The developed fluorescent probe exhibits excellent sensory response towards Cur within a concentration range of 0.081–51.45 µM, achieving an ultra-low detection limit of 15.91 nM. The sensor was successfully tested on real food samples like ginger powder, turmeric powder, and curry powder, demonstrating good recovery rates. To assess the practicality of the sensor system, we developed a 3D-printed smartphone-integrated device platform for curcumin detection through fluorescence image analysis. This developed platform exhibited promising results, achieving a limit of detection (LoD) of 132.28 nM across a curcumin concentration range of 0.13–54.00 µM. This device platform holds significant potential for the development of efficient sensors for real-time detection of Cur in food samples.

Fano mode based plasmonic sensor for temperature and chemical pollutant detection

Plasmonic sensors provide great sensitivity to minute quantities of analytes and provide excellent detection. In present context of environmental monitoring, plasmonic sensor can prove to be an excellent choice in chemical pollutant and temperature detection. Plasmonic sensors can provide immediate results, allowing for monitoring temperature changes in ecosystems or climate studies and quick decision-making in emergency situations related chemical pollution incidents. They are compact and can be integrated into portable devices for on-site analysis. In this investigation, a plasmonic refractive index sensor based on key ring shaped resonator consisting of a microring resonator and two rectangular resonator is proposed. Finite-Difference Time-Domain (FDTD) method is used to study the transmittance characteristics of the sensor. The device exhibits quadruple Fano resonance with highest sensitivity of 2521.7 nm/RIU. Other performance parameters such as figure of Merit (FOM), Quality (Q) factor and Detection limit (DL) are also been calculated, with values 98.8 RIU−1, 99.6 and 0.01 respectively. Additionally, the effects of different geometrical configurations is also studied, providing insights into the design principles in context of potential fabrication complexities. Further, the simulated Fano characteristic is validated against the theoretical value. The application of the proposed sensor is investigated for different types of analyte such as chemical pollutants and temperature sensing.

Electrochemical detection of lead ions using carbon nanotube post electrodes

Heavy metal ions above their recommended limits are highly toxic to human health. Even at low levels, contaminants such as Pb in drinking water can severely affect vulnerable population of the society. Therefore, developing rapid, effective, stable, and convenient sensors for Pb detection has gained significant attention. In this study, considering the excellent properties of carbon nanotubes (CNTs), CNT post electrodes were fabricated by embedding them in a nonconducting polymer. The CNT posts were derived from a closely packed CNT forest with a diameter of 0.3 mm containing millions of vertically aligned pillars. The highly stable CNT post electrodes were employed for the electrochemical sensing of heavy metal ions in 0.1 M citric acid. A linear range of 9.64–168.7 nM (2–35 ppb) was observed for Pb ions. Further, linear ranges of 0.0786–7.86 μM (5–500 ppb) and 15.73–157.36 μM (1000–10000 ppb) were also obtained for Cu ions. Notably, the electrode containing a single CNT post was capable of the electrochemical detection of Pb ions at the ppb level. With this electrode, the sensitivity and limit of detection were 0.5095nA/nM and 2 nM (0.5 ppb) for Pb ions, and 24.53 μA/ppb and 41.67 nM (2.64 ppb) for Cu ions, respectively. The limit of detection for Pb ions is lower than the maximum permissible limit in drinking water set by the World Health Organization. Due the electrochemical method employed on its detection, the reported sensor can simultaneously detect Pb, Cu and Zn ions in tap water.

An ultrasensitive and visual ratio fluorescence sensing platform for tannic acid in water based on boric acid functionalized lanthanide MOF

Tannic acid (TA) is a natural polyphenol that is widely used as a preservative and antioxidant in foods, beverages, health products and pharmaceuticals. In this study, a novel Eu-MOF skeleton was prepared using a simple solvothermal strategy and used as a ratio-metric fluorescence sensor for the ultra-sensitive detection of TA. The constructed Eu-MOF has excellent fluorescence properties and high stability in the aqueous phase. With the introduction of TA, a special covalent structure is formed between the o-diphenol group of TA and the boric acid hydroxyl group in ligand of the MOF, resulting in a gradual decrease in the red emission of Eu-MOF at 614 nm and a basically invariable blue emission at 420 nm. As the concentration of TA increased, the color of the system also changes from red to blue, thus achieving rapid and sensitive detection with a low limit of detection (LOD) of 75.6 nM through a ratiometric fluorescence strategy. What is more, Eu-MOF fluorescent probe combined with smart phone color detector is used to visually detect TA. The propose method is successfully applied in the target analysis in tea and beverage samples and the recovery is 95.6∼110.0 %, which is proved to be an effective strategy for the food safety and healthy monitoring.

Two-dimensional photonic crystal acetylcholinesterase hydrogel and organohydrogel sensors for efficient detection of organophosphorus compounds

Sensors capable of detecting organophosphorus (OP) compounds have attracted the most attention owing to severe OP contamination worldwide. Despite many years of research, the developed OP sensors mainly focused on detecting water-soluble OPs in proper environments and the exploration of OP sensors suitable in resource-limited areas is extremely challenging. Here, a simple two-dimensional photonic crystal (2D PC) hydrogel featuring capabilities of effectively quantitative determination of OP compounds is facilely constructed by immobilizing the enzyme acetylcholinesterase (AChE) onto a bovine serum albumin (BSA) protein hydrogel. Owing to the specific interaction between AChE and OP compounds, the OP compounds are easily bound to the hydrogel, triggering volume phase transition and resulting in apparent Debye diffraction ring variations. The resulting hydrogel sensors show a limit of detection (LoD) of 2.23 nM for trichlorfon and 0.07 nM for diethyl methylphosphonate (DMPP), respectively. On the basis of the hydrogel, a responsive organohydrogel is facilely fabricated utilizing a solvent exchange strategy to meet the requirements of applications in harsh environments and detection of the non-water-soluble OP compounds. The organohydrogel sensors, however, demonstrated a LoD of 0.70 μM for trichlorfon and 4.46 μM for DMPP, respectively. This work provides new light on the development of next-generation stable, low-cost, and portable field sensing devices.

Design and Simulation of a Microcantilever Sensor for Precise Detection of Volatile Organic Compounds

Design and Simulation of a Microcantilever Sensor for Precise Detection of Volatile Organic Compounds

Towards multimodal visualization of esophageal motility: fusion of manometry, impedance, and videofluoroscopic image sequences.

Dysphagia is the inability or difficulty to swallow normally. Standard procedures for diagnosing the exact disease are, among others, X-ray videofluoroscopy, manometry and impedance examinations, usually performed consecutively. In order to gain more insights, ongoing research is aiming to collect these different modalities at the same time, with the goal to present them in a joint visualization. One idea to create a combined view is the projection of the manometry and impedance values onto the right location in the X-ray images. This requires to identify the exact sensor locations in the images. This work gives an overview of the challenges associated with the sensor detection task and proposes a robust approach to detect the sensors in X-ray image sequences, ultimately allowing to project the manometry and impedance values onto the right location in the images. The developed sensor detection approach is evaluated on a total of 14 sequences from different patients, achieving a F1-score of 86.36%. To demonstrate the robustness of the approach, another study is performed by adding different levels of noise to the images, with the performance of our sensor detection method only slightly decreasing in these scenarios. This robust sensor detection provides the basis to accurately project manometry and impedance values onto the images, allowing to create a multimodal visualization of the swallow process. The resulting visualizations are evaluated qualitatively by domain experts, indicating a great benefit of this proposed fused visualization approach. Using our preprocessing and sensor detection method, we show that the sensor detection task can be successfully approached with high accuracy. This allows to create a novel, multimodal visualization of esophageal motility, helping to provide more insights into swallow disorders of patients.

Moisture‐resistant nitroaromatic explosive gas sensor based on hydrophilic pentiptycene polymer

AbstractThe detection of explosive materials, particularly nitroaromatic compounds such as 2,4,6‐trinitrotoluene (TNT), is critical for public safety and national security. Existing detection methods often require complex instrumentation, limiting their applicability for real‐time or in‐field use. Fluorescent sensors, which offer rapid and sensitive detection through fluorescence quenching, present a promising alternative. This study evaluates the performance of two pentiptycene‐based polymers, P‐1 and P‐2, in detecting explosive vapors, with a specific focus on their behavior under high‐humidity conditions. P‐2, modified with triethylene glycol groups, demonstrated significantly increased hydrophilicity compared to the commonly studied P‐1, as confirmed by contact angle measurements. Spectroscopic analysis revealed a blue shift in P‐2's UV–Vis absorption and photoluminescence spectra, indicating electronic property changes due to structural modifications. The enhanced hydrophilicity of P‐2 enabled it to maintain stable sensing performance under moist conditions, showing less than a 10% reduction in sensitivity, compared to the 20% decrease observed in P‐1. This superior moisture resistance suggests that P‐2 is a more robust and practical sensor for explosive detection in environments with variable humidity levels.

Lanthanide detection by novel arylether based receptor with imine functional groups: synthetic, photophysical, electrochemical and computational elucidation

AbstractThe present research discloses a novel chemical sensor (TEI) [1-((E)-(2-(3-(2-((E)-(2-hydroxynaphthalene-1-yl)methyleneamino)phenoxy)phenoxy)phenylimino)methyl)naphthalene-2-ol] for the detection of rare earth element cerium (III) in which spectrophotometric and voltametric sensor techniques were used with a versatile combination of ether and imine group. Various lanthanide ions were checked for the binding in a solution of TEI under identical conditions, including Ce(III), Dy(III), Ho(III), La(III), Sm(III), Eu(III), Gd(III), Tb(III), Er(III), Yb(III), Tm(III), Pr(III) and Nd(III). As observed in absorption studies, the enhancement of spectral intensity at 310 nm caused by Ce(III) was expected over other lanthanide ions. Cyclic and differential pulse voltammograms were also drawn for TEI receptor with and without Ce3+ ions With incremental addition of Ce3+ ions the anodic peak at 0.68 V oxygen gets completely diminished. Another anodic peak at 0.75 V which was due to complete oxidation of ether group and re-oxidation of reduced imine group, got reduced. In case of cathodic peak (due to reduction of imine group) at 0.6 V, there was hardly any decrease in current. This leads to the confirmation that there was no involvement of imine group in binding in the complex. Detection limit obtained by this sensor is 5 × 10–7 M without any interference which makes it a potent sensor for cerium detection.

Retraction Note: Simulation of machine vision based on light detection sensors in aerobics judgment assistance system

Retraction Note: Simulation of machine vision based on light detection sensors in aerobics judgment assistance system

Double-Chamber Underwater Thruster Diaphragm with Flexible Displacement Detection Function.

The purpose of this paper is to develop a self-detecting diaphragm integrated with a flexible sensor, which is utilized in an underwater thruster. Resistive strain sensors are easy to manufacture and integrate due to their advantages in reliable stretchability and ductility. Inspired by the structure of neurons, we fabricated resistive flexible sensors using silica gel as the matrix with carbon black and carbon nanotubes as additives. All fabricated sensors demonstrated positive resistance characteristics under 60% strain conditions, with the sensor containing a mass ratio of 9 wt % carbon black and carbon nanotubes exhibiting the best resistance-strain linearity. To verify the anti-interference capability of sensors with silica gel substrates of varying hardness values under changing environmental pressure, we tested the pressure sensitivity of the sensors by altering the hardness of the silica gel. The results indicate that silica gel with the highest hardness value provides the best resistance to environmental pressure interference. To detect the motion and deformation of the internal functional components of the thruster, we combined strain detection with the movement operation function of a silica gel diaphragm, resulting in a new integrated diaphragm with sensor detection capabilities. The integrated diaphragm was evaluated by using a tensile testing machine and an LCR tester. The results demonstrate that the mechanical properties of the diaphragm are stable, exhibiting reliable resistance characteristics and a sensitive response during underwater operation. This research can also be applied to the detection of motion amplitudes of other types of soft robots.