Strategy, Design, and Fabrication of Electrochemical Biosensors: A Tutorial

Advanced healthcare requires novel technologies capable of real-time sensing to monitor acute and long-term health. The challenge relies on converting a real-time quantitative biological and chemical signal into a desired measurable output. Given the success in detecting glucose and the commercialization of glucometers, electrochemical biosensors continue to be a mainstay of academic and industrial research activities. Despite the wealth of literature on electrochemical biosensors, reports are often specific to a particular application (e.g., pathogens, cancer markers, glucose, etc.), and most fail to convey the underlying strategy and design, and if it is transferable to detection of a different analyte. Here we present a tutorial review for those entering this research area that summarizes the basic electrochemical techniques utilized as well as discusses the designs and optimization strategies employed to improve sensitivity and maximize signal output.

Eddy Current Position Measurement in Harsh Environments: A Temperature Compensation and Calibration Approach

Eddy current displacement sensors (ECDSs) are widely used for the noncontact position measurement of small displacements (lift-offs). Challenges arise with larger displacements as the sensitivity of the ECDSs decreases. This leads to a more pronounced impact of temperature variations on the inductance and, consequently, an increased position error. Design solutions often rely on multiple coils, suitable coil carrier materials, and compensation measures to address the challenges. This study presents a single-coil ECDS for large displacement ranges in environments with high temperatures and temperature variations. The analysis is based on a sensor model derived from an equivalent circuit model (ECM). We propose design measures for both the sensing coil and the target, focusing on material selection to handle the impact of temperature variations. A key part of improving performance under varying temperatures includes model-based temperature compensation for the inductance of the sensing coil. We introduce a method to calibrate the sensor for large displacements, using a modified coupling coefficient based on field simulation data. Our analysis shows that this single-coil ECDS design maintains a position error of less than 0.2% full-scale for a temperature variation of 100 K for the sensing coil and 110 K for the target.

Four-Stage Multi-Physics Simulations to Assist Temperature Sensor Design for Industrial-Scale Coal-Fired Boiler

The growth of renewable energy sources presents a pressing challenge to the operation and maintenance of existing fossil fuel power plants, given that fossil fuel remains the predominant fuel source, responsible for over 60% of electricity generation in the United States. One of the main concerns within these fossil fuel power plants is the unpredictable failure of boiler tubes, resulting in emergency maintenance with significant economic and societal consequences. A reliable high-temperature sensor is necessary for in situ monitoring of boiler tubes and the safety of fossil fuel power plants. In this study, a comprehensive four-stage multi-physics computational framework is developed to assist the design, optimization installation, and operation of the high-temperature stainless-steel and quartz coaxial cable sensor (SSQ-CCS) for coal-fired boiler applications. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. With the simulation-guided sensor installation plan, the newly designed SSQ-CCSs have been employed for field testing for more than 430 days. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

Electrostatic Acoustic Sensor with an Impedance-Matched Diaphragm Characterized for Body Sound Monitoring

Acoustic sensors are able to capture more incident energy if their acoustic impedance closely matches the acoustic impedance of the medium being probed, such as skin or wood. Controlling the acoustic impedance of polymers can be achieved by selecting materials with appropriate densities and stiffnesses as well as adding ceramic nanoparticles. This study follows a statistical methodology to examine the impact of polymer type and nanoparticle addition on the fabrication of acoustic sensors with desired acoustic impedances in the range of 1-2.2 MRayls. The proposed method using a design of experiments approach measures sensors with diaphragms of varying impedances when excited with acoustic vibrations traveling through wood, gelatin, and plastic. The sensor diaphragm is subsequently optimized for body sound monitoring, and the sensor's improved body sound coherence and airborne noise rejection are evaluated on an acoustic phantom in simulated noise environments and compared to electronic stethoscopes with onboard noise cancellation. The impedance-matched sensor demonstrates high sensitivity to body sounds, low sensitivity to airborne sound, a frequency response comparable to two state-of-the-art electronic stethoscopes, and the ability to capture lung and heart sounds from a real subject. Due to its small size, use of flexible materials, and rejection of airborne noise, the sensor provides an improved solution for wearable body sound monitoring, as well as sensing from other mediums with acoustic impedances in the range of 1-2.2 MRayls, such as water and wood.

A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth

We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution monitoring schemes. This use case is further supported by its out-of-water operation, which provides low-effort installations and longer maintenance-free intervals when compared with in-water sensors. The inclusion of both velocity and depth measurement capabilities allows the sensor to also be used as an all-in-one solution for flowrate measurement. We discuss the design of the sensor, which has been made freely available under open-hardware and open-source licenses. The design uses commonly available electronic components, and a 3D-printed casing makes the design easy to replicate and modify. Not before seen on a hydrology sensor, we include a 3D-printed radar lens in the casing, which boosts radar sensitivity by 21 dB. The velocity and depth-sensing performance were characterised in laboratory and in-field tests. The depth is accurate to within ±6% and ±7 mm and the uncertainty in the velocity measurements ranges from less than 30% to 36% in both laboratory and field conditions. Our sensor is demonstrated to be a feasible low-cost design which nears the uncertainty of current, yet more expensive, velocity sensors, especially when field performance is considered.

Evaluating the Potential of an Oral-Based Bioguard to Estimate Heart Rate Using Photoplethysmography

The reliable monitoring of heart rate during intense exercise is imperative to effectively manage training loads while providing insights from a healthcare perspective. However, current technologies perform poorly in contact sports settings. This study aims to evaluate the best approach for heart rate tracking using photoplethysmography sensors embedded into an instrumented mouthguard (iMG). Seven adults wore iMGs and a reference heart rate monitor. Several sensor placements, light sources and signal intensities were explored for the iMG. A novel metric related to the positioning of the sensor in the gum was introduced. The error between the iMG heart rate and the reference data was assessed to obtain insights into the effect of specific iMG configurations on measurement errors. Signal intensity was found to be the most important variable for error prediction, followed by the sensor light source, sensor placement and positioning. A generalized linear model combining an infrared light source, at an intensity of 5.08 mA, and a frontal placement high in the gum area resulted in a heart rate minimum error of 16.33%. This research shows promising preliminary results for the use of oral-based heart rate monitoring, but highlights the need for the careful consideration of sensor configurations within these systems.

Development of a Novel Spherical Light-Based Positioning Sensor in Solar Tracking

Tracking of the sun, which increases the efficiency of solar energy production systems, has shown considerable development in recent years. This development has been achieved by custom-positioned light sensors, image cameras, sensorless chronological systems and intelligent controller supported systems or by synergetic use of these systems. This study contributes to this research area with a novel spherical-based sensor which measures spherical light source emittance and localizes the light source. This sensor was built by using miniature light sensors placed on a spherical shaped three-dimensional printed body with data acquisition electronic circuitry. Besides the developed sensor data acquisition embedded software, preprocessing and filtering processes were conducted on these measured data. In the study, the outputs of Moving Average, Savitzky-Golay, and Median filters were used for the localization of the light source. The center of gravity for each filter used was determined as a point, and the location of the light source was determined. The spherical sensor system obtained by this study is applicable for various solar tracking methods. The approach of the study also shows that this measurement system is applicable for obtaining the position of local light sources such as the ones placed on mobile or cooperative robots.

Research on Rapid and Low-Cost Spectral Device for the Estimation of the Quality Attributes of Tea Tree Leaves

Tea polyphenols, amino acids, soluble sugars, and other ingredients in fresh tea leaves are the key parameters of tea quality. In this research, a tea leaf ingredient estimation sensor was developed based on a multi-channel spectral sensor. The experiment showed that the device could effectively acquire 700-1000 nm spectral data of tea tree leaves and could display the ingredients of leaf samples in real time through the visual interactive interface. The spectral data of Fuding white tea tree leaves acquired by the detection device were used to build an ingredient content prediction model based on the ridge regression model and random forest algorithm. As a result, the prediction model based on the random forest algorithm with better prediction performance was loaded into the ingredient detection device. Verification experiment showed that the root mean square error (RMSE) and determination coefficient (R²) in the prediction were, respectively, as follows: moisture content (1.61 and 0.35), free amino acid content (0.16 and 0.79), tea polyphenol content (1.35 and 0.28), sugar content (0.14 and 0.33), nitrogen content (1.15 and 0.91), and chlorophyll content (0.02 and 0.97). As a result, the device can predict some parameters with high accuracy (nitrogen, chlorophyll, free amino acid) but some of them with lower accuracy (moisture, polyphenol, sugar) based on the R² values. The tea leaf ingredient estimation sensor could realize rapid non-destructive detection of key ingredients affecting tea quality, which is conducive to real-time monitoring of the current quality of tea leaves, evaluating the status during tea tree growth, and improving the quality of tea production. The application of this research will be helpful for the automatic management of tea plantations.

Design of electrical impedance spectroscopy sensing surgical drill using computational modelling and experimental validation

Electrical Impedance Spectroscopy (EIS) sensing surgical instruments could provide valuable and real-time feedback to surgeons about hidden tissue boundaries, therefore reducing the risk of iatrogenic injuries. In this paper, we present an EIS sensing surgical drill as an example instrument and introduce a strategy to optimize the mono-polar electrode geometry using a finite element method (FEM)-based computational model and experimental validation. An empirical contact impedance model and an adaptive mesh refinement protocol were developed to accurately preserve the behaviour of sensing electrodes as they approach high impedance boundaries. Specifically, experiments with drill-bit, cylinder, and conical geometries suggested a 15%-35% increase in resistance as the sensing electrode approached a high impedance boundary. Simulations achieved a maximum mean experiment-to-simulation mismatch of +1.7% for the drill-bit and +/-11% range for other electrode geometries. The simulations preserved the increase in resistance behaviour near the high impedance boundary. This highly accurate simulation framework allows us a mechanism for optimizing sensor geometry without costly experimental evaluation.

Case-Specific Focal Sensor Design for Cardiac Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a non-invasive detection technology that uses the electrical response value at the boundary of an observation field to image the conductivity changes in an area. When EIT is applied to the thoracic cavity of the human body, the conductivity change caused by the heartbeat will be concentrated in a sub-region of the thoracic cavity, that is, the heart region. In order to improve the spatial resolution of the target region, two sensor optimization methods based on conformal mapping theory were proposed in this study. The effectiveness of the proposed method was verified by simulation and phantom experiment. The qualitative analysis and quantitative index evaluation of the reconstructed image showed that the optimized model could achieve higher imaging accuracy of the heart region compared with the standard sensor. The reconstruction results could effectively reflect the periodic diastolic and systolic movements of the heart and had a better ability to recognize the position of the heart in the thoracic cavity.

A Low-Cost, Low-Power Water Velocity Sensor Utilizing Acoustic Doppler Measurement

Current commercial sensors to monitor water flow velocities are expensive, bulky, and require significant effort to install. Low-cost sensors open the possibility of monitoring storm and waste water systems at a much greater spatial and temporal resolution without prohibitive costs and resource investment. To aid in this, this work developed a low-cost, low-power velocity sensor based on acoustic Doppler velocimetry. The sensor, costing less than 50 USD is open-source, open-hardware, compact, and easily interfaceable to a wide range of data-logging systems. A freely available sensor design at this price point does not currently exist, and its novelty is in enabling high-resolution real-time monitoring schemes. The design is capable of measuring water velocities up to 1200 mm/s. The sensor is characterised and then verified in an in-field long-term test. Finally, the data from this test are then used to evaluate the performance of the sensor in a real-world scenario. The analysis concludes that the sensor is capable of effectively measuring water velocity.

In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

Untethered soft robots that locomote using electrothermally-responsive materials like shape memory alloy (SMA) face challenging design constraints for sensing actuator states. At the same time, modeling of actuator behaviors faces steep challenges, even with available sensor data, due to complex electrical-thermal-mechanical interactions and hysteresis. This article proposes a framework for in-situ sensing and dynamics modeling of actuator states, particularly temperature of SMA wires, which is used to predict robot motions. A planar soft limb is developed, actuated by a pair of SMA coils, that includes compact and robust sensors for temperature and angular deflection. Data from these sensors are used to train a neural network-based on the long short-term memory (LSTM) architecture to model both unidirectional (single SMA) and bidirectional (both SMAs) motion. Predictions from the model demonstrate that data from the temperature sensor, combined with control inputs, allow for dynamics predictions over extraordinarily long open-loop timescales (10 min) with little drift. Prediction errors are on the order of the soft deflection sensor's accuracy. This architecture allows for compact designs of electrothermally-actuated soft robots that include sensing sufficient for motion predictions, helping to bring these robots into practical application.

Estimation and Error Analysis for Optomechanical Inertial Sensors

A sensor model and methodology to estimate the forcing accelerations measured using a novel optomechanical inertial sensor with the inclusion of stochastic bias and measurement noise processes is presented. A Kalman filter for the estimation of instantaneous sensor bias is developed; the outputs from this calibration step are then employed in two different approaches for the estimation of external accelerations applied to the sensor. The performance of the system is demonstrated using simulated measurements and representative values corresponding to a bench-tested 3.76 Hz oscillator. It is shown that the developed methods produce accurate estimates of the bias over a short calibration step. This information enables precise estimates of acceleration over an extended operation period. These results establish the feasibility of reliably precise acceleration estimates using the presented methods in conjunction with state of the art optomechanical sensing technology.

AirKit: A Citizen-Sensing Toolkit for Monitoring Air Quality

Increasing urbanisation and a better understanding of the negative health effects of air pollution have accelerated the use of Internet of Things (IoT)-based air quality sensors. Low-cost and low-power sensors are now readily available and commonly deployed by individuals and community groups. However, there are a wide range of such IoT devices in circulation that differently focus on problems of sensor validation, data reliability, or accessibility. In this paper, we present AirKit, which was developed as an integrated and open source “social IoT technology”. AirKit enables a comprehensive approach to citizen-sensing air quality through several integrated components: (1) the Dustbox 2.0, a particulate matter sensor; (2) Airsift, a data analysis platform; (3) a reliable and automatic remote firmware update system; (4) a “Data Stories” method and tool for communicating citizen data; and (5) an AirKit logbook that provides a guide for designing and running air quality projects, along with instructions for building and using AirKit components. Developed as a social technology toolkit to foster open processes of research co-creation and environmental action, Airkit has the potential to generate expanded engagements with IoT and air quality by improving the accuracy, legibility and use of sensors, data analysis and data communication.

Design and Calibration of Robot Base Force/Torque Sensors and Their Application to Non-Collocated Admittance Control for Automated Tool Changing

Robotic manipulators physically interacting with their environment must be able to measure contact forces/torques. The standard approach to this end is attaching force/torque sensors directly at the end-effector (EE). This provides accurate measurements, but at a significant cost. Indirect measurement of the EE-loads by means of torque sensors at the actuated joint of a robot is an alternative, in particular for series-elastic actuators, but requires dedicated robot designs and significantly increases costs. In this paper, two alternative sensor concept for indirect measurement of EE-loads are presented. Both sensors are located at the robot base. The first sensor design involves three load cells on which the robot is mounted. The second concept consists of a steel plate with four spokes, at which it is suspended. At each spoke, strain gauges are attached to measure the local deformation, which is related to the load at the sensor plate (resembling the main principle of a force/torque sensor). Inferring the EE-load from the so determined base wrench necessitates a dynamic model of the robot, which accounts for the static as well as dynamic loads. A prototype implementation of both concepts is reported. Special attention is given to the model-based calibration, which is crucial for these indirect measurement concepts. Experimental results are shown when the novel sensors are employed for a tool changing task, which to some extend resembles the well-known peg-in-the-hole problem.

Towards Easy-to-Use Bacteria Sensing: Modeling and Simulation of a New Environmental Impedimetric Biosensor in Fluids

Conventional pathogenic bacteria-detection methods are lab-bound, time-consuming and need trained personnel. Microelectrodes can be used to recognize harmful microorganisms by dielectric impedance spectroscopy. However, crucial for this spectroscopy method are the spatial dimensions and layout of the electrodes, as the corresponding distribution of the electric field defines the sensor system parameters such as sensitivity, SNR, and dynamic range. Therefore, a variety of sensor models are created and evaluated. FEM simulations in 2D and 3D are conducted for this impedimetric sensor. The authors tested differently shaped structures, verified the linear influence of the excitation amplitude and developed a mathematical concept for a quality factor that practically allows us to distinguish arbitrary sensor designs and layouts. The effect of guard electrodes blocking outer influences on the electric field are investigated, and essential configurations are explored. The results lead to optimized electronic sensors in terms of geometrical dimensions. Possible material choices for real sensors as well as design and layout recommendations are presented.

Annular Cavity Design for Photoluminescent Polymer Optical Fiber Sensors

We present optimization results on the design of a polymer optical fiber single point sensor suitable for photoluminescence-based sensing. The single point sensing design consists of one or two annular cavities, separated by a small distance, milled into the fiber and subsequently filled with a thick solution of polymer, solvent, and photoluminescent molecules, which is then allowed to dry. The design is tested by varying the depth and length of a single cavity and utilizing two cavities with varying separations. Results from experiments show a maximum response at a separation of 2 mm for which we present an analytical explanation. A geometrical, numerical simulation model, taking into account both skew and meridional rays, is developed and shows very good agreement with the experimental results. The fiber design presents a general platform that has the potential for the fabrication of multi-point photoluminescent sensors, for which it is necessary to have several points along the fiber functionalized for sensing. Furthermore, the approach with polymer fibers and polymer sensing gels allows for a robust integration of the sensing matrix and the optical fiber, more so than is possible using glass optical fibers.

New advances in mechanomyography sensor technology and signal processing: Validity and intrarater reliability of recordings from muscle

Introduction

The Mechanical Muscle Activity with Real-time Kinematics project aims to develop a device incorporating wearable sensors for arm rehabilitation following stroke. These will record kinematic activity using inertial measurement units and mechanical muscle activity. The gold standard for measuring muscle activity is electromyography; however, mechanomyography offers an appropriate alterative for our home-based rehabilitation device. We have patent filed a new laboratory-tested device that combines an inertial measurement unit with mechanomyography. We report on the validity and reliability of the mechanomyography against electromyography sensors.

Methods

In 18 healthy adults (27–82 years), mechanomyography and electromyography recordings were taken from the forearm flexor and extensor muscles during voluntary contractions. Isometric contractions were performed at different percentages of maximal force to examine the validity of mechanomyography. Root-mean-square of mechanomyography and electromyography was measured during 1 s epocs of isometric flexion and extension. Dynamic contractions were recorded during a tracking task on two days, one week apart, to examine reliability of muscle onset timing.

Results

Reliability of mechanomyography onset was high (intraclass correlation coefficient = 0.78) and was comparable with electromyography (intraclass correlation coefficient = 0.79). The correlation between force and mechanomyography was high (R² = 0.94).

Conclusion

The mechanomyography device records valid and reliable signals of mechanical muscle activity on different days.

MakeSense: Automated Sensor Design for Proprioceptive Soft Robots

Soft robots have applications in safe human-robot interactions, manipulation of fragile objects, and locomotion in challenging and unstructured environments. In this article, we present a computational method for augmenting soft robots with proprioceptive sensing capabilities. Our method automatically computes a minimal stretch-receptive sensor network to user-provided soft robotic designs, which is optimized to perform well under a set of user-specified deformation-force pairs. The sensorized robots are able to reconstruct their full deformation state, under interaction forces. We cast our sensor design as a subselection problem, selecting a minimal set of sensors from a large set of fabricable ones, which minimizes the error when sensing specified deformation-force pairs. Unique to our approach is the use of an analytical gradient of our reconstruction performance measure with respect to selection variables. We demonstrate our technique on a bending bar and gripper example, illustrating more complex designs with a simulated tentacle.

Wearable strain gauge-based technology measures manual tactile forces during the activities of daily living

Introduction

Current methods of determining applied forces in the hand rely on grip dynamometers or force-measurement gloves which are limited in their ability to isolate individual finger forces and interfere with the sense of touch. The objective of this study was to develop an improved force measurement system that could be used during various activities of daily living.

Methods

Custom-made strain gauge sensors were secured to the fingernail of four fingers and two middle phalanges and calibrated to measure hand forces in eight healthy individuals during five activities of daily living.

Results

These sensors were capable of measuring forces as small as 0.17 N and did not saturate at high force tasks around 15 N, which is within the envelope of forces experienced during daily life. Preliminary data demonstrate the ability of these tactile sensors to reliably distinguish which fingers/segments were used in various tasks.

Conclusions

Until now, there has been no method for real-time unobtrusive monitoring of force exposure during the tasks of daily life. The system used in this study provides a new type of low-cost wearable technology to monitor forces in the hands without interfering with the contact surface of the hand.

Focusing Sensor Design for Open Electrical Impedance Tomography Based on Shape Conformal Transformation

Electrical Impedance Tomography (EIT) is a non-invasive detection method to image the conductivity changes inside an observation region by using the electrical measurements at the boundary of this region. In some applications of EIT, the observation domain is infinite and is only accessible from one side, which leads to the so-called open EIT (OEIT) problem. Compared with conventional EIT problems, the observation region in OEIT can only be measured from limited projection directions, which makes high resolution imaging much more challenging. To improve the imaging quality of OEIT, a focusing sensor design strategy is proposed based on shape conformal theory. The conformal bijection is used to map a standard EIT sensor defined at a unit circle to a focusing OEIT sensor defined at an upper half plane. A series of numerical and experimental testes are conducted. Compared with the traditional sensor structure, the proposed focusing sensor has higher spatial resolution at the near-electrode region and is good at distinguishing multi-inclusions which are close to each other.

3D SSY Estimate of EPFM Constraint Parameter under Biaxial Loading for Sensor Structure Design

Conventional sensor structure design and related fracture mechanics analysis are based on the single J-integral parameter approach of elastic-plastic fracture mechanics (EPFM). Under low crack constraint cases, the EPFM one-parameter approach generally gives a stress overestimate, which results in a great cost waste of labor and sensor components. The J-A two-parameter approach overcomes this limitation. To enable the extensive application of the J-A approach on theoretical research and sensor engineering problem, under small scale yielding (SSY) conditions, the authors developed an estimate method to conveniently and quickly obtain the constraint (second) parameter A values directly from T-stress. Practical engineering application of sensor structure analysis and design focuses on three-dimensional (3D) structures with biaxial external loading, while the estimate method was developed based on two-dimensional (2D) plain strain condition with uniaxial loading. In the current work, the estimate method was successfully extended to a 3D structure with biaxial loading cases, which is appropriate for practical sensor design. The estimate method extension and validation process was implemented through a thin 3D single edge cracked plate (SECP) specimen. The process implementation was completed in two specified planes of 3D SECP along model thickness. A wide range of material and geometrical properties were applied for the extension and validation process, with material hardening exponent value 3, 5 and 10, and crack length ratio 0.1, 0.3 and 0.7.

A Simplified SSY Estimate Method to Determine EPFM Constraint Parameter for Sensor Design

To implement a sensor structure analysis and design (as well as other engineering applications), a two-parameter approach using elastic–plastic fracture mechanics (EPFM) could be applied to analyze a structure more accurately than a one-parameter approach, especially for structures with low crack constraint. The application of the J-A two-parameter approach on sensors and other structures depends on the obtainment of a constraint parameter A. To conveniently and effectively obtain the A parameter values, the authors have developed a T-stress-based estimate method under a small-scale yielding (SSY) condition. Under a uniaxial external loading condition, a simplified format of the T-stress-based estimate has been proposed by the authors to obtain the parameter A much more conveniently and effectively. Generally, sensors and other practical engineering structures endure biaxial external loading instead of the uniaxial one. In the current work, the simplified formation of the estimate method is extended to a biaxial loading condition. By comparing the estimated A parameter values with their numerical solutions from a finite element analysis (FEA) results, the extension of the simplified formation of T-stress-based estimate method to biaxial loading was discussed and validated. The comparison procedure was completed using a wide variety of materials and geometrical properties on three types of specimens: single edge cracked plate (SECP), center cracked plate (CCP), and double edge cracked plate (DECP).

Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors

Scientists require methods to monitor the distribution of gas bubbles in gas-liquid bubble column reactors. One non-destructive method that can potential satisfy this requirement in industrial situations is ultrasonic transmission tomography (UTT). In this paper, an ultrasonic transmission tomography sensor is designed for measuring bubble distribution in a reactor. Factors that influence the transducer design include transmission energy loss, the resonance characteristics and vibration modes of the transducer, and diffusion angles of the transducers, which are discussed. For practical application, it was found that an excitation frequency of 300 kHz could identify the location and size of gas bubbles. The vibration mode and diffusion also directly affect the quality of the imaging. The geometric parameters of the transducer (a cylinder transducer with a 10 mm diameter and 6.7 mm thickness) are designed to achieve the performance requirements. A UTT system, based on these parameters, was built in order to verify the effectiveness of the designed ultrasonic transducer array. A Sector-diffusion-matrix based Linear Back Projection (SLBP) was used to reconstruct the gas/liquid two-phase flow from the obtained measurements. Two other image processing methods, based on SLBP algorithm named SLBP-HR (SLBP-Hybrid Reconstruction) and SLBP-ATF (SLBP-Adaptive Threshold Filtering), were introduced, and the imaging results are presented. The imaging results indicate that a gas bubble with a 3 mm radius can be identified from reconstructed images, and that three different flow patterns, namely, single gas bubble, double gas bubble with different diameters, and eccentric flow, can be identified from reconstructed images. This demonstrates that the designed UTT sensor can effectively measure bubble distribution in gas-liquid bubble column reactors.

An Inductive Sensing System to Measure In-Socket Residual Limb Displacements for People Using Lower-Limb Prostheses

The objective of this research was to assess the performance of an embedded sensing system designed to measure the distance between a prosthetic socket wall and residual limb. Low-profile inductive sensors were laminated into prosthetic sockets and flexible ferromagnetic targets were created from elastomeric liners with embedded iron particles for four participants with transtibial amputation. Using insights from sensor performance testing, a novel calibration procedure was developed to quickly and accurately calibrate the multiple embedded sensors. The sensing system was evaluated through laboratory tests in which participants wore sock combinations with three distinct thicknesses and conducted a series of activities including standing, walking, and sitting. When a thicker sock was worn, the limb typically moved further away from the socket and peak-to-peak displacements decreased. However, sensors did not measure equivalent distances or displacements for a given sock combination, which provided information regarding the fit of the socket and how a sock change intervention influenced socket fit. Monitoring of limb⁻socket displacements may serve as a valuable tool for researchers and clinicians to quantitatively assess socket fit.

Fringing Electric Field Sensors for Anti-Attack at System-Level Protection

Information system security has been in the spotlight of individuals and governments in recent years. Integrated Circuits (ICs) function as the basic element of communication and information spreading, therefore they have become an important target for attackers. From this perspective, system-level protection to keep chips from being attacked is of vital importance. This paper proposes a novel method based on a fringing electric field (FEF) sensor to detect whether chips are dismantled from a printed circuit board (PCB) as system-level protection. The proposed method overcomes the shortcomings of existing techniques that can be only used in specific fields. After detecting a chip being dismantled from PCB, some protective measures like deleting key data can be implemented to be against attacking. Fringing electric field sensors are analyzed through simulation. By optimizing sensor's patterns, areas and geometrical parameters, the methods that maximize sensitivity of fringing electric field sensors are put forward and illustrated. The simulation is also reproduced by an experiment to ensure that the method is feasible and reliable. The results of experiments are inspiring in that they prove that the sensor can work well for protection of chips and has the advantage of universal applicability, low cost and high reliability.

Biotechnologies toward Mitigating, Curing, and Ultimately Preventing Edema through Compression Therapy

For a century-old problem, edema and its treatment have gone remarkably unnoticed by the biomedical community. Given the prevalence of lymphedema and its debilitating repercussions, there is an acute need for both efficacy-based measures and clinical standards to guide compression garment design and therapeutic application. This review outlines the current state of the art in compression treatment and suggests an integrated biomedical engineering approach going forward. Characterizing the pressure gradient profiles of commercial compression sleeves is necessary to better understand the role of compression treatment in the mitigation of swelling. Integration of pressure sensor technologies with advanced materials design and manufacture provides a critical path not only to elucidate the mechanisms of but also to improve on current compression-based therapies and associated therapeutic devices.

A Newly Designed Fiber-Optic Based Earth Pressure Transducer with Adjustable Measurement Range

A novel fiber-optic based earth pressure sensor (FPS) with an adjustable measurement range and high sensitivity is developed to measure earth pressures for civil infrastructures. The new FPS combines a cantilever beam with fiber Bragg grating (FBG) sensors and a flexible membrane. Compared with a traditional pressure transducer with a dual diaphragm design, the proposed FPS has a larger measurement range and shows high accuracy. The working principles, parameter design, fabrication methods, and laboratory calibration tests are explained in this paper. A theoretical solution is derived to obtain the relationship between the applied pressure and strain of the FBG sensors. In addition, a finite element model is established to analyze the mechanical behavior of the membrane and the cantilever beam and thereby obtain optimal parameters. The cantilever beam is 40 mm long, 15 mm wide, and 1 mm thick. The whole FPS has a diameter of 100 mm and a thickness of 30 mm. The sensitivity of the FPS is 0.104 kPa/με. In addition, automatic temperature compensation can be achieved. The FPS's sensitivity, physical properties, and response to applied pressure are extensively examined through modeling and experiments. The results show that the proposed FPS has numerous potential applications in soil pressure measurement.

Crowdsensing in Smart Cities: Overview, Platforms, and Environment Sensing Issues

Evidence shows that Smart Cities are starting to materialise in our lives through the gradual introduction of the Internet of Things (IoT) paradigm. In this scope, crowdsensing emerges as a powerful solution to address environmental monitoring, allowing to control air pollution levels in crowded urban areas in a distributed, collaborative, inexpensive and accurate manner. However, even though technology is already available, such environmental sensing devices have not yet reached consumers. In this paper, we present an analysis of candidate technologies for crowdsensing architectures, along with the requirements for empowering users with air monitoring capabilities. Specifically, we start by providing an overview of the most relevant IoT architectures and protocols. Then, we present the general design of an off-the-shelf mobile environmental sensor able to cope with air quality monitoring requirements; we explore different hardware options to develop the desired sensing unit using readily available devices, discussing the main technical issues associated with each option, thereby opening new opportunities in terms of environmental monitoring programs.

Mechanical Structural Design of a MEMS-Based Piezoresistive Accelerometer for Head Injuries Monitoring: A Computational Analysis by Increments of the Sensor Mass Moment of Inertia

This work focuses on the proof-mass mechanical structural design improvement of a tri-axial piezoresistive accelerometer specifically designed for head injuries monitoring where medium-G impacts are common; for example, in sports such as racing cars or American Football. The device requires the highest sensitivity achievable with a single proof-mass approach, and a very low error (<1%) as the accuracy for these types of applications is paramount. The optimization method differs from previous work as it is based on the progressive increment of the sensor proof-mass mass moment of inertia (MMI) in all three axes. Three different designs are presented in this study, where at each step of design evolution, the MMI of the sensor proof-mass gradually increases in all axes. The work numerically demonstrates that an increment of MMI determines an increment of device sensitivity with a simultaneous reduction of cross-axis sensitivity in the particular axis under study. This is due to the linkage between the external applied stress and the distribution of mass (of the proof-mass), and therefore of its mass moment of inertia. Progressively concentrating the mass on the axes where the piezoresistors are located (i.e., x- and y-axis) by increasing the MMI in the x- and y-axis, will undoubtedly increase the longitudinal stresses applied in that areas for a given external acceleration, therefore increasing the piezoresistors fractional resistance change and eventually positively affecting the sensor sensitivity. The final device shows a sensitivity increase of about 80% in the z-axis and a reduction of cross-axis sensitivity of 18% respect to state-of-art sensors available in the literature from a previous work of the authors. Sensor design, modelling, and optimization are presented, concluding the work with results, discussion, and conclusion.

Development of a magnetic composite material for measurement of residual limb displacements in prosthetic sockets

INTRODUCTION

Wearable limb-socket displacement sensors may help patients and prosthetists identify a deteriorating socket fit and justify the need for repair or replacement.

METHODS

A novel sensor using an inductive sensing modality was developed to detect limb-to-socket distances. Key detection elements were a coil antenna placed in the socket wall and a magnetic composite sheath worn over the outside of the prosthesis user's elastomeric liner. The sheath was a nylon or cotton prosthetic stocking coated with a polyurethane composite. The polyurethane composite contained embedded iron particles (75 wt%).

RESULTS

Brushing γ-glycidoxypropyltriethoxysilane onto the sheath fabric, coating it first with unfilled polyurethane and then iron-filled polyurethane, enhanced bonding between the sheath and the composite and overcame mechanical degradation problems. A γ-glycidoxypropyltriethoxysilane-rich fumed silica layer applied to the outside of the sheath reduced friction and improved durability. Field testing demonstrated less than a 3% signal degradation from four weeks of field use.

CONCLUSIONS

The developed wearable displacement sensor meets durability and performance needs, and is ready for large-scale clinical testing.

Magnetoelectric Current Sensors

In this work a magnetoelectric (ME) current sensor design based on a magnetoelectric effect is presented and discussed. The resonant and non-resonant type of ME current sensors are considered. Theoretical calculations of the ME current sensors by the equivalent circuit method were conducted. The application of different sensors using the new effects, for example, the ME effect, is made possible with the development of new ME composites. A large number of studies conducted in the field of new composites, allowed us to obtain a high magnetostrictive-piezoelectric laminate sensitivity. An optimal ME structure composition was matched. The characterization of a non-resonant current sensor showed that in the operation range to 5 A, the sensor had a sensitivity of 0.34 V/A, non-linearity less than 1% and for a resonant current sensor in the same operation range, the sensitivity was of 0.53 V/A, non-linearity less than 0.5%.

Falls are unintentional: Studying simulations is a waste of faking time

Researchers tend to agree that falls are, by definition, unintentional and that sensor algorithms (the processes that allows a computer program to identify a fall among data from sensors) perform poorly when attempting to detect falls 'in the wild' (a phrase some scientists use to mean 'in reality'). Algorithm development has been reliant on simulation, i.e. asking actors to throw themselves intentionally to the ground. This is unusual (no one studies faked coughs or headaches) and uninformative (no one can intend the unintentional). Researchers would increase their chances of detecting 'real' falls in 'the real world' by studying the behaviour of fallers, however, vulnerable, before, during and after the event: the literature on the circumstances of falling is more informative than any number of faked approximations. A complimentary knowledge base (in falls, sensors and/or signals) enables multidisciplinary teams of clinicians, engineers and computer scientists to tackle fall detection and aim for fall prevention. Throughout this paper, I discuss differences between falls, 'intentional falling' and simulations, and the balance between simulation and reality in falls research, finally suggesting ways in which researchers can access examples of falls without resorting to fakery.

Older adults' satisfaction of wearing consumer-level activity monitors

There is a growing body of evidence to suggest that consumer-level activity monitors are a valid means of measuring physical activity in older adults. Understanding whether older adults are satisfied with wearing these activity monitors is an important step to ensuring that devices can be successfully implemented in clinical and research settings. Twenty-five older adults (mean age = 72.5 years, standard deviation = 4.9) wore two consumer-level activity monitors (Misfit Shine and Fitbit Charge HR) for seven consecutive days. After the week, participants were asked for their views and satisfaction of wearing each device, measured in part by the Quebec User Evaluation of Satisfaction with assistive Technology. Participants were generally satisfied with most aspects of the devices, though they were significantly more satisfied with the Misfit Shine. Participants were critical about their ability to adjust the fit of both the Misfit Shine and Fitbit Charge HR. Interestingly, the perceived satisfaction with the device was not associated with participants' consideration of wearing the device again. Future research needs to consider whether the design of consumer-level activity monitors are best suited for older adults.

Guided Wave Based Crack Detection in the Rivet Hole Using Global Analytical with Local FEM Approach

In this article, ultrasonic guided wave propagation and interaction with the rivet hole cracks has been formulated using closed-form analytical solution while the local damage interaction, scattering, and mode conversion have been obtained from finite element analysis. The rivet hole cracks (damage) in the plate structure gives rise to the non-axisymmetric scattering of Lamb wave, as well as shear horizontal (SH) wave, although the incident Lamb wave source (primary source) is axisymmetric. The damage in the plate acts as a non-axisymmetric secondary source of Lamb wave and SH wave. The scattering of Lamb and SH waves are captured using wave damage interaction coefficient (WDIC). The scatter cubes of complex-valued WDIC are formed that can describe the 3D interaction (frequency, incident direction, and azimuth direction) of Lamb waves with the damage. The scatter cubes are fed into the exact analytical framework to produce the time domain signal. This analysis enables us to obtain the optimum design parameters for better detection of the cracks in a multiple-rivet-hole problem. The optimum parameters provide the guideline of the design of the sensor installation to obtain the most noticeable signals that represent the presence of cracks in the rivet hole.

Defining Requirements and Related Methods for Designing Sensorized Garments

Designing smart garments has strong interdisciplinary implications, specifically related to user and technical requirements, but also because of the very different applications they have: medicine, sport and fitness, lifestyle monitoring, workplace and job conditions analysis, etc. This paper aims to discuss some user, textile, and technical issues to be faced in sensorized clothes development. In relation to the user, the main requirements are anthropometric, gender-related, and aesthetical. In terms of these requirements, the user's age, the target application, and fashion trends cannot be ignored, because they determine the compliance with the wearable system. Regarding textile requirements, functional factors-also influencing user comfort-are elasticity and washability, while more technical properties are the stability of the chemical agents' effects for preserving the sensors' efficacy and reliability, and assuring the proper duration of the product for the complete life cycle. From the technical side, the physiological issues are the most important: skin conductance, tolerance, irritation, and the effect of sweat and perspiration are key factors for reliable sensing. Other technical features such as battery size and duration, and the form factor of the sensor collector, should be considered, as they affect aesthetical requirements, which have proven to be crucial, as well as comfort and wearability.

Development of clinically relevant implantable pressure sensors: perspectives and challenges

This review describes different aspects to consider when developing implantable pressure sensor systems. Measurement of pressure is in general highly important in clinical practice and medical research. Due to the small size, light weight and low energy consumption Micro Electro Mechanical Systems (MEMS) technology represents new possibilities for monitoring of physiological parameters inside the human body. Development of clinical relevant sensors requires close collaboration between technological experts and medical clinicians.  Site of operation, size restrictions, patient safety, and required measurement range and resolution, are only some conditions that must be taken into account. An implantable device has to operate under very hostile conditions. Long-term in vivo pressure measurements are particularly demanding because the pressure sensitive part of the sensor must be in direct or indirect physical contact with the medium for which we want to detect the pressure. New sensor packaging concepts are demanded and must be developed through combined effort between scientists in MEMS technology, material science, and biology. Before launching a new medical device on the market, clinical studies must be performed. Regulatory documents and international standards set the premises for how such studies shall be conducted and reported.

Overview of a novel sensor for continuous glucose monitoring

The core element of a continuous glucose monitoring (CGM) system is the glucose sensor, which should enable reliable CGM readings in the interstitial fluid in subcutaneous tissue for a period of several days. The aim of this article is to describe the layout and constituents of a novel glucose sensor and the rationale behind the measures that were used to optimize its performance. In order to achieve a stable glucose sensor signal, special attention was paid to the sensor materials and architecture, i.e., biocompatible coating of the sensor, limitation of glucose flux into the working electrode, low oxidation potential by use of manganese dioxide, and a tissue-averaging sensor design. A series of in vitro and in vivo evaluations showed that the sensor enables stable and accurate glucose sensing in the subcutaneous tissue for up to 7 days. Parallel measurements with four sensors in a single patient showed a close agreement between these sensors. In summary, this high-performance needle-type glucose sensor is well suited for CGM in patients with diabetes.

Sensor and display human factors based design constraints for head mounted and tele-operation systems

For mobile imaging systems in head mounted displays and tele-operation systems it is important to maximize the amount of visual information transmitted to the human visual system without exceeding its input capacity. This paper aims to describe the design constraints on the imager and display systems of head mounted devices and tele-operated systems based upon the capabilities of the human visual system. We also present the experimental results of methods to improve the amount of visual information conveyed to a user when trying to display a high dynamic range image on a low dynamic range display.

Design Principles for Rapid Prototyping Forces Sensors using 3D Printing

Force sensors provide critical information for robot manipulators, manufacturing processes, and haptic interfaces. Commercial force sensors, however, are generally not adapted to specific system requirements, resulting in sensors with excess size, cost, and fragility. To overcome these issues, 3D printers can be used to create components for the quick and inexpensive development of force sensors. Limitations of this rapid prototyping technology, however, require specialized design principles. In this paper, we discuss techniques for rapidly developing simple force sensors, including selecting and attaching metal flexures, using inexpensive and simple displacement transducers, and 3D printing features to aid in assembly. These design methods are illustrated through the design and fabrication of a miniature force sensor for the tip of a robotic catheter system. The resulting force sensor prototype can measure forces with an accuracy of as low as 2% of the 10 N measurement range.