Proposed Sensor System Research Articles

Development of an enzyme-functionalized immunosensor for measuring maturation-inducing hormone in fish

In modern aquaculture, simple and rapid methods of predicting fish ovulation are needed to produce seedlings in a stable and efficient manner. Ovulation time is variable due to environmental and physiological factors, while 17α,20β-dihydroxy-4-pregnen-3-one (DHP), an indicator of ovulation, increases its concentration rapidly just before spawning. In this paper, we developed a biosensor system in which immune and enzymatic reaction assays were combined to monitor DHP levels with low environmental loads. We attempted to quantify DHP by analyzing the decrease rate in the output current after the immunoreaction using the amperometric method as a transfer inhibition degree of the enzyme-generated electrons generated by the formation of the antigen-antibody complex. DHP standard samples were measured under investigated optimal conditions and a specific response with a good linear correlation was obtained between the current decrease rate of the sensor system and the DHP concentration in a range of 7.81∼500 pg ml−1. Further, DHP levels in goldfish (Carassius auratus) during the ovulation period obtained using the sensor system were compared with those of using the conventional method (ELISA) and a good correlation was obtained. These findings suggest that the proposed sensor system can detect DHP quickly and easily compared with the conventional method.

Use of smartphone videos and pattern recognition for food authentication

A novel sensor system for food authentication is presented, which is based on computer vision and pattern recognition. The sensor system uses a smartphone to generate a sequence of light with varying colours to illuminate a food sample, and uses the smartphone camera to receive reflected light by way of recording a video. The video is processed using computer vision techniques and transformed into sensor data in the form of a data vector. The sensor data is analysed using pattern recognition techniques. The locally weighted partial least squares regression method is extended for classification to improve the modelling effectiveness and robustness. The sensor system is evaluated on the task of authentication of olive oil and milk – to verify how they are labelled. Large quantities of olive oil and milk were purchased from supermarkets, and sensor videos were created using the sensor system. Test accuracies of 96.2% and 100% were achieved for olive oil and milk authentication respectively. These results suggest the proposed sensor system is effective. Since the sensor system is built in a smartphone, it has the potential to serve as a low-cost and effective solution for food authentication and to empower consumers in food fraud detection.

Sensor subsystem design for small unmanned surface vehicle

The construction of unmanned vehicles is a major trend in a modern robotics and automation. One of the promising branches is the development of unmanned boats and surface vehicles (USV). They possess the great variety of possible applications, including environmental studies, military and security issues. In this paper, we consider the design and rapid prototyping of sensory subsystem for small-sized USV. The proposed sensor system incorporates the lidar, Doppler radar rangefinder and video camera in a waterproof housing. The housing is made with additive technology and provides the efficient and rigid placement of chosen set of sensors. The circuitry and design of the sensory subsystem are given and discussed in comparison with existing solution. The prototype of the system is described and the results of its experimental testing are provided.

3D-Printing Techniques on the Development of Multiparameter Sensors Using One FBG.

We report the development of a fiber Bragg grating (FBG) sensor for multiparameter sensing using only one FBG. The FBG was half-embedded in a 3D-printed structure, which resulted in a division of the grating spectrum creating two peaks with different sensitivities with respect to different physical parameters. A numerical analysis of the proposed technique was performed using the coupled-mode theory with modified transfer matrix formulation. Then, experimental analyses were performed as function of temperature, strain and force, where the peaks showed different sensitivities in all analyzed cases. Such results enable the application of a technique for simultaneous measurement of multiple physical parameters using both peaks and the full width half maximum of the FBG embedded in a 3D structure. In the simultaneous multiparameter assessment, the proposed sensor system was able to estimate the three tested parameters (strain, temperature and force) with relative errors as low as 4%.

Development of a Passive Capacitively Coupled Contactless Conductivity Detection (PC4D) Sensor System for Fluidic Channel Analysis Toward Point-of-Care Applications

A sensor system based on a modified capacitively coupled contactless conductivity detection sensor is proposed and developed. The proposed system provides a passive and wireless readout technique, through which the conductivity of fluidic flow can be analyzed and foreign objects occurring in the fluidic flow can be detected. The proposed sensor system takes advantage of the series resonance principle and detects shifts in the resonance frequency and reflection coefficient to estimate the conductivity of the fluidic flow. In this paper, the working principle of the device is proposed and analyzed using a multiphysics simulation, and its performance is validated experimentally. The sensing performance is confirmed by measuring the conductivity of the fluidic media and the detection of foreign objects, such as air bubbles or water droplets, occurring in the flow. The influence of the distance between the inductors on the resonance frequency for different solution conductivities is also investigated and reported. The proposed sensor system shows its potential for use in various applications in biomedicine and chemistry, particularly in point-of-care applications, where the sensing chip can be easily set up for measurement and disposed of after use.

Smartphone Integrated Polymer Optical Fiber Humidity Sensor: Towards a Fully Portable Solution for Healthcare

This letter presents a humidity sensor based on the colorimetric change on a silica gel sphere with the increase of the relative humidity, which leads to variations on the optical power transmission in a polymer optical fiber (POF). The sensor setup presented employs a light coupler with two POF ends positioned on a sphere of silica gel. The sensor is characterized with the reflected signal acquired by a spectrometer and the relative fluorescence spectrum of the fibers at different relative humidity is acquired and compared. Then, the sensor is integrated with a smartphone, which is used as the interrogator. In this case, the flashlight and camera are employed as a light source and a photodetector, respectively. Results show the feasibility of the proposed approach, which has some advantageous features such as mechanical robust and compact sensor that presents a linear behavior on the relative humidity range (25%-80%) analyzed. Furthermore, the smartphone integration provides additional advantage for the sensor by increasing its portability and ease to use. Thus, the proposed sensor system can be readily applied in many healthcare applications, including home monitoring, assistive robotics, and medical devices.

Fiber Optic Sensor Based on Vernier Microwave Frequency Comb

We demonstrate a proposed fiber optic sensor based on detecting the envelope of a Vernier microwave frequency comb (VMFC). A mode-locked fiber laser was employed as a microwave frequency comb source. A fiber ring, functioning as a sensor head as well as a microwave photonic filter, tailored the amplitude of each harmonic of the microwave frequency comb. By carefully designing the fiber ring length and the frequency separation of the microwave frequency comb, the Vernier effect is generated on the photodiode recovered microwave frequency comb after the laser pulses pass through the fiber ring. The sensing information can be deduced by tracking the envelope of the VMFC. The experimental results of a temperature sensing test show that the frequency shifts of the envelope peak have a good linear relationship with temperature variation. Furthermore, the sensitivity of the proposed sensor system is controllable.

Development of bulldozer sensor system for estimating the position of blade cutting edge

This paper proposed a bulldozer sensor system for estimating the blade cutting edge position, designed to help bulldozer operators guide the bulldozer blade cutting edge towards a precise position in leveling works. The proposed sensor system consists of two GNSSs, two IMUs, and a position estimation controller. Each sensor and position estimation controller are connected through CAN and RS-232 communications, which facilitate reception of the GNSS's position data and the IMU's angle data as well as the calculation of the bulldozer posture and the blade position. A blade cutting edge position estimation formula is proposed using the frame mapping method reflecting kinematic analysis to calculate the position of the blades. The bulldozer mechanism was modeled, and the effectiveness of the proposed method was verified via simulation to determine accuracy of the estimated positions. The proposed sensor system was then applied to a navigation system to estimate the position of the blade cutting edge after being mounted on an actual bulldozer. The performance of the proposed sensor system was verified by comparing with the positions provided by a commercial GPS.

A Wearable Wireless Armband Sensor for High-Density Surface Electromyography Recording.

This paper presents a portable and modular wireless multichannel sensor system for high-density surface electromyography (HD-sEMG) signals acquisition. Featuring low-power and high-quality off-the-shelf components such as the Intan Technologies RHD2132 digital electrophysiology interface chip, the current iteration of the proposed sensor system allows the recording of 32 surface electromyography (sEMG) channels, each at a sampling rate of 1 kHz, and a sample resolution of 16 bits. It features the RHD2132's typical input-referred noise of 2.4 μVrms, with <; 15% variation with amplifier bandwidth as specified by the manufacturer, and a total power consumption of 49.5 mW. Data is sent in real-time to a base station using a 2.4-GHz industrial, scientific and medical (ISM) wireless link. Along with the recording platform, the integrated sensor system includes a dry surface electrodes array prototype directly built on a printed circuit board. Intended for complex muscles activity patterns detection on the forearm, the flexible 32 surface electrodes array is designed to be placed flat or to fit a curved area like the forearm in a hand gestures recognition prosthetic system. In such applications, this device will offer improved prosthesis control scheme intuitiveness and ease-of-use. Among other core features of the system are its compact, light-weight and easy to install physical design. The complete system fits on a 2 by 6.5 cm2 printed circuit board mounted on a 7.6 by 11.8 cm2 electrodes array. HD-sEMG user forearm output data collected with the system is presented with a proposed frequency-time-space cross-domain preprocessing method for visualization of HD-EMG data and building training datasets.

Fiber optic displacement sensor used in railway turnout contact monitoring system

Railway turnout contact monitoring is very important in high-speed rail operation systems. In order to measure the distance between the sharp rail and the basic rail in a switch system, a wide-range, high-precision fiber Bragg grating (FBG) displacement sensor was designed. Because the distance between the sharp and basic rails is always greater than 14 cm, the measurement range width and accuracy of the proposed sensor system are ensured through the use of a long spring and a beam of constant strength. A differential compensation method is used to eliminate temperature effects. Test results show that the resolution of the proposed sensor is 0.040 mm and the measuring range is 0–170 mm. A field test was also carried out to evaluate the performance of the sensors.

Realization of Sub-Nano-Strain Static Resolution With Injection-Locking Between Two Fiber Laser Sensors

Fiber Bragg grating (FBG) based sensors have achieved great performance in dynamic strain sensing, while static strain measurement is still very challenging because it requires extra reference for temperature compensation. In this paper, a high-resolution FBG laser sensor system is presented, which is capable of both static and dynamic strain measurements. In the proposed sensor, a distributed feedback fiber laser (DFB-FL) works as the strain sensing element, and a distributed Bragg reflector fiber laser (DBR-FL) works as the reference. The DFB-FL is injection-locked to the DBR-FL with closed loop control using Pound–Drever–Hall (PDH) technique and an acousto-optic frequency shifter. No independent narrow-linewidth probe laser source is required. In experiments, a frequency fluctuation range of 31.6 kHz in 1000 s between the DFB-FL and the DBR-FL is obtained, corresponding to a static strain resolution of 248 pico-strain. Meanwhile, a dynamic resolution of 580 femto-strain at l kHz is achieved. The limitation on strain resolution and dynamic range of the sensor is also discussed. Due to the high strain resolution and moderate cost, the proposed sensor system provides a powerful tool for various applications of strain measurement.

Using a convolutional neural network to construct a pen-type tactile sensor system for roughness recognition

The tactile texture of a product is one of many important factors that influences an impression of a product. Numerical evaluation methods for recognizing tactile texture measures, such as roughness, are required because there are indeed individual differences in how users experience tactile textures. In this paper, we propose a tactile sensor to recognize roughness using a convolutional neural network (CNN). Our sensor system consists of a pressure sensor and a six-axis acceleration sensor for detecting time-series data. The sensor measures time-series data, which are the pressure, speed, and posture of the sensor when the sensor is touching an object and is moved by a user. The surface roughness is calculated from these time-series data using a CNN. Here, our system configuration is simple and therefore easy and inexpensive to construct. To evaluate our approach, we constructed a prototype sensor and measured the roughness of six objects. The average correct recognition rate proved to be 71% for the experimental data acquired by one user, which are categorized into learning data and evaluation data. Further, the total average recognition rate for evaluation data by our five users for considering each individual using the sensor system was 42%. While the problem of roughness recognition by each individual user remains, we were able to show the possibility of roughness recognition via our approach. We conclude that our proposed sensor system is useful as a functional and useful device.

A fiber Bragg grating based passive semicircular sensor architecture with fault monitoring

Abstract In the investigation, we investigate a fiber Bragg grating (FBG) based semicircular sensor architecture with fiber fault monitoring experimentally. Two erbium-doped fiber amplifiers (EDFAs) are used in the monitoring center to generate a broadband light source for sensing the strain and temperature simultaneously. Here, we utilize six FBG based sensors with different reflected wavelength for proof-of-concept demonstration. There is no optical filter used in the FBG sensor system for wavelength-selection. In addition, the proposed sensor system can monitor one to two fiber faults. In the measurement, the temperature- and strain-induced changes are also analyzed and discussed. Therefore, the proposed multiple FBG based semicircular sensor system not only can sense the temperature and strain simultaneously, but also can be used to monitor where is the fiber fault.

Polymer Optical Fiber-Based Sensor System for Smart Walker Instrumentation and Health Assessment

This paper presents a polymer optical fiber (POF)-based sensor system for smart walker (SW) instrumentation. The system comprises an oximetry sensor working in reflectance mode, which is embedded in a 3D printed handle for the SW. In addition, there is also a POF-based smart textile that can be integrated in the users’ clothes and is placed on their chest. In this case, the smart textile can detect the displacement caused by the respiration, vibration due to heartbeat and bending induced in the gait. Results show that the proposed sensor system can detect the oxygen saturation, breathing rate, gait cadence, and heart rate with errors of about 1%. In addition, it is proposed an architecture for the SW in which the POF-based sensor system can be applied not only for remote healthcare applications, but also as sensor feedback in cloud robotics for some control paradigms for human–robot interaction. Furthermore, the proposed instrumentation presents the possibility of novel SW control, where the health conditions of the user are considered in the human–robot interaction.

PMMA-Coated Capacitive Type Soil Moisture Sensor: Design, Fabrication, and Testing

This paper describes the fringing electric field modeling and performance of four different shaped poly methyl methacrylate-coated capacitive sensors for soil moisture measurement. Experiments are carried out in the laboratory by placing the sensor inside the soil. The analytical solution for such fringing field system is difficult to obtain, so COMSOL Multiphysics software is used for modeling the capacitive sensor surrounded by the soil. Experimental data are compared with the software simulated value. Statistical root-mean-square error (RMSE) and percentage of normalized RMSE for polynomial fit are studied for the sensitivity and performance analysis. Effect of external temperature on the performance of the sensor is also discussed. The proposed signal conditioning circuit is implemented in printed circuit board to measure the output voltage with respect to capacitance change. Obtained results are transmitted through a global system for mobile communication module for remote observation of soil moisture. The thermogravimetric method is used for voltage to soil moisture calibration, and based on the experimental data, results are analyzed further. A review of some relevant fringing field capacitive sensors and their instrumentation system reported in past 7-8 years are studied for comparison with the proposed sensor system.

Polymer optical fiber-embedded, 3D-printed instrumented support for microclimate and human-robot interaction forces assessment

This paper presents the fabrication, characterization and applications of a 3D-printed instrumented support for wearable devices. Intensity variation-based polymer optical fiber (POF) sensors were employed in the support instrumentation, in order to obtain a low-cost system. In the proposed instrumented support, two POFs are embedded in a 3D-printed acrylonitrile butadiene styrene (ABS) rigid structure for microclimate assessment (without the influence of the applied force). Additionally, other two POFs are embedded in a thermoplastic polyurethane (TPU) flexible structure for the force assessment, where one sensor measures the applied force in flexion cycles and the other in extension cycles. All four sensors are characterized with respect to temperature and humidity. Both force sensors are also characterized with respect to the force and their cross-sensitivities with respect to the temperature and humidity. The results show the feasibility of the proposed sensor system embedded in the 3D-printed support, where the errors for the force assessment are below 2.8 N, and for temperature and humidity the errors are about 1.1 °C and 2.5%, respectively. The feasibility of the proposed instrumented support in measuring force and microclimate variations was also verified in the application as a shank support for a lower limb exoskeleton for knee rehabilitation and on a passive orthosis for gait assistance.

A High-Resolution Leaky Coaxial Cable Sensor Using a Wideband Chaotic Signal.

A high-resolution leaky coaxial cable (LCX) sensor for perimeter intrusion detection is proposed and experimentally demonstrated. In our proposed sensor system, a wideband Boolean-chaos signal is used as the probe signal, and a pair of leaky coaxial cables (LCXs) is applied for transmitting the probe signal and receiving the echo signal, respectively. By correlating the chaotic echo signal with its delayed duplicate and comparing the correlation traces before and after intrusion, the intruder can be accurately located. Experimental results demonstrate the proposed sensor can simultaneously detect multiple intruders. The range resolution reaches 30 cm, whilst the dynamic range can achieve 50 dB. In addition, this sensor possesses the excellent anti-interference performance to the noise and uncorrelated chaotic signal, which makes it show robust performance in the detection environment with noise or multiple chaotic LCX sensors cooperation.

Near-infrared acetylene sensor system using off-axis integrated-cavity output spectroscopy and two measurement schemes.

For highly sensitive and accurate acetylene (C2H2) detection, a near-infrared (NIR) off-axis integrated-cavity output spectroscopy (OA-ICOS) sensor system based on an ultra-compact cage-based absorption cell was proposed. The absorption cell with dimensions of 10 cm × 8 cm × 6 cm realized a dense-pattern and an easily-aligned stable optical system. The OA-ICOS sensor system employed a 6cm-long optical cavity that was formed by two mirrors with a reflectivity of 99.35% and provided an effective absorption path length of ∼9.28 m. The performance of the C2H2 sensor system based on two measurement schemes, i.e. laser direct absorption spectroscopy (LDAS) and wavelength modulation spectroscopy (WMS) is reported. A NIR distributed feedback (DFB) laser was employed for targeting a C2H2 absorption line at 6523.88 cm-1. An Allan deviation analysis yielded a detection sensitivity of 760 parts-per-billion in volume (ppbv) for an averaging time of 304 s using the LDAS-based OA-ICOS. A detection sensitivity of 85 ppbv for an averaging time of 250 s was obtained using the WMS-based OA-ICOS, which was further improved by a factor of ~9 compared to the result obtained with the LDAS method. The proposed sensor system has the advantages of reduced size and cost with acceptable detection sensitivity, which is suitable for applications in trace gas sensing in harsh environments and weight-limited balloon-embedded observations.

A method for real-time classification of insect vectors of mosaic and brown streak disease in cassava plants for future implementation within a low-cost, handheld, in-field multispectral imaging sensor

BackgroundThe paper introduces a multispectral imaging system and data-processing approach for the identification and discrimination of morphologically indistinguishable cryptic species of the destructive crop pest, the whitefly Bemisia tabaci. This investigation and the corresponding system design, was undertaken in two phases under controlled laboratory conditions. The first exploited a prototype benchtop variant of the proposed sensor system to analyse four cryptic species of whitefly reared under similar conditions. The second phase, of the methodology development, employed a commercial high-precision laboratory hyperspectral imager to recover reference data from five cryptic species of whitefly, immobilized through flash freezing, and taken from across four feeding environments.ResultsThe initial results, for the single feeding environment, showed that a correct species classification could be achieved in 85–95% of cases, utilising linear Partial Least Squares approaches. The robustness of the classification approach was then extended both in terms of the automated spatial extraction of the most pertinent insect body parts, to assist with the spectral classification model, as well as the incorporation of a non-linear Support Vector Classifier to maintain the overall classification accuracy at 88–98%, irrespective of the feeding and crop environment.ConclusionThis study demonstrates that through an integration of both the spatial data, associated with the multispectral images being used to separate different regions of the insect, and subsequent spectral analysis of those sub-regions, that B. tabaci viral vectors can be differentiated from other cryptic species, that appear morphologically indistinguishable to a human observer, with an accuracy of up to 98%. The implications for the engineering design for an in-field, handheld, sensor system is discussed with respect to the learning gained from this initial stage of the methodology development.

Systematic Experimental Assessment of a 2D-Motion Sensor to Detect Relative Movement between Residual Limb and Prosthetic Socket.

A sensor system for measuring the relative movement between prosthetic socket and residual limb based on a 2D-motion sensor is introduced and thoroughly tested experimentally. The quantitative analysis of test rig evaluation is used to identify advantageous sensor settings and liner configurations. Considering these favorable settings, sensor functionality is quantified to %. Advancing to convex measurement surfaces, the sensor shows absolute errors of mm in an observable measurement scenario. The feasibility of measuring gait-induced relative movement with the proposed 2D-motion sensor is shown via a biomechanical plausibility study. Overall, the findings suggest that the proposed sensor system is suitable for investigating the relative movement between residual limb and prosthetic socket in dynamic gait situations.