381 results found
Arteaga JM, Sanchez J, Elsakloul F, et al., 2023, High frequency inductive power transfer through soil for agricultural applications, IEEE Transactions on Power Electronics, Vol: 38, Pages: 13415-13429, ISSN: 0885-8993
This paper presents 13.56 MHz inductive powertransfer (IPT) through soil for sensors in agricultural ap-plications. Two IPT system designs and their prototypes are presented. The first was designed for gathering data and observing the relationship between the performance of the coil driving circuits in response to water content, salinity, organic matter and compaction of the soil. The second prototype was designed as an application demonstrator, featuring IPT to an in-house sensor node enclosure buried 200 mm under the surface of an agricultural field. The results highlight that from the parameters studied, the combination of high salinity and high water content significantly increases the losses of the IPT system.The experiments demonstrate an over 40% rise in the losses from dc source to dc load after a 16% increase in soil water content and high salinity. In the technology demonstrator we mounted an IPT transmitter on a drone to wirelessly power an in-house bank of supercapacitors in the buried sensor-node enclosure. A peak power transfer of 30 W received at over 40% efficiency was achieved from a 22 V power supply on the drone to the energy storage under the ground. The coil separation in these experiments was 250 mm of which 200 mm correspond to the layer of soil. The coupling factor in all the experiments was lower than 5%. This system was trialled in the field for forty days andwireless power was performed five times throughout.
Gil B, Keshavarz M, Wales D, et al., 2023, Orthogonal Surface-Enhanced Raman Scattering/Field-Effect Transistor Detection of Breast and Colorectal Cancer-Derived Exosomes using Graphene as a Tag-Free Diagnostic Template, ADVANCED NANOBIOMED RESEARCH, ISSN: 2699-9307
Xiao B, Lam H-K, Xuan C, et al., 2023, Optimization for interval type-2 polynomial fuzzy systems: a deep reinforcement learning approach, IEEE Transactions on Artificial Intelligence, Vol: 4, Pages: 1269-1280, ISSN: 2691-4581
It is known that the interval type-2 (IT2) fuzzy controllers are superior compared to their type-1 counterparts in terms of robustness, flexibility, etc. However, how to conduct the type reduction optimally with the consideration of system stability under the fuzzy-model-based (FMB) control framework is still an open problem. To address this issue, we present a new approach through the membership-function-dependent (MFD) and deep reinforcement learning (DRL) approaches. In the proposed approach, the reduction of IT2 membership functions of the fuzzy controller is completing during optimizing the control performance. Another fundamental issue is that the stability conditions must hold subject to different type-reduction methods. It is tedious and impractical to resolve the stability conditions according to different type-reduction methods, which could lead to infinite possibility. It is more practical to guarantee the holding of stability conditions during type-reduction rather than resolving the stability conditions, the MFD approach is proposed with the imperfect premise matching (IPM) concept. Thanks to the unique merit of the MFD approach, the stability conditions according to all the different embedded type-1 membership functions within the footprint of uncertainty (FOU) are guaranteed to be valid. During the control processes, the state transitions associated with properly engineered cost/reward function can be used to approximately calculate the deterministic policy gradient to optimize the acting policy and then to improve the control performance through determining the grade of IT2 membership functions of the fuzzy controller. The detailed simulation example is provided to verify the merits of the proposed approach.
Wright SW, Kiziroglou ME, Yeatman EM, 2023, Inductive power line harvester with flux guidance for self-powered sensors, IEEE Sensors Journal, Vol: 23, Pages: 20474-20482, ISSN: 1530-437X
Self-powered sensors are expected to enable new large-scale deployment and location access capabilities for sensor systems. Energy harvesting devices have been shown to provide adequate power densities but their dependence on very specific environmental conditions restricts their applicability. Energy harvesting from power line infrastructure offers an architecture for addressing this challenge, because such infrastructure is widely available. In this paper an inductive power line harvester concept is presented, based on a flux concentration approach adapted to a closed-loop core geometry. Flux concentration is studied by simulation, showing a 26% flux increase using a 1:3 geometrical concentration ratio in a closed-loop core. A 20×20×25 mm prototype with a U-shaped soft-core sheet and a 200-turn Cu coil around a 5 mm diameter, 20 mm long soft-core rod is introduced. The total device volume is 9.1 cm 3 . Characterization results on a power line evaluation setup for currents up to 35 A RMS and a 50 Hz – 1 kHz range are presented. Power between 2.2 mW (50 Hz) and 233 mW (1 kHz) is demonstrated on an ohmic load, from a 10 A RMS power line current, employing impedance matching with reactance cancellation. The corresponding power densities are 0.24 mW/cm 3 and 25 mW/cm 3 respectively, per total device volume. This performance is adequate for enabling self-powered wireless sensor networks installed along power distribution lines.
Yang SKE, Kiziroglou ME, Yeatman EM, et al., 2023, Acoustic flow sensor using a passive bell transducer, IEEE Sensors Journal, Vol: 23, Pages: 20553-20560, ISSN: 1530-437X
Sensing based on a passive transducer that is wirelessly linked to a nearby data collection node can offer an attractive solution for use in remote, inaccessible, or harsh environments. Here we report a pipe flow sensor based on this principle. A transducer mounted inside the pipe generates an acoustic signal that is picked up by an external microphone. The passive transducer comprises a cavity with a trapped ball that can oscillate in response to flow. Its collisions generate an acoustic signal correlated to the flow speed. The transducer is implemented on a 6 mm diameter probe and characterized as a water flow meter. The time - average microphone voltage output is calculated by an analogue circuit, without any further signal processing. With the microphone mounted on the probe, and for flow rates in the range 0.35 m/s to 6.5 m/s, correlation between the sensor voltage output and flow rate data from a commercial flow meter is demonstrated with a worst-case accuracy of 2%. This was achieved by simple averaging of the acoustic pulse train over a 5-second time interval. Consistent correlation with the microphone mounted on the pipe wall at distances up to 150 mm from the probe location is also reported. These results demonstrate the viability of remote acoustic flow sensing using passive structures and offer a simple and minimally invasive flow monitoring method.
Kim JA, Hou Y, Keshavarz M, et al., 2023, Characterization of bacteria swarming effect under plasmonic optical fiber illumination, Journal of Biomedical Optics, Vol: 28, Pages: 1-15, ISSN: 1083-3668
SignificancePlasmo-thermo-electrophoresis (PTEP) involves using plasmonic microstructures to generate both a large-scale convection current and a near-field attraction force (thermo-electrophoresis). These effects facilitate the collective locomotion (i.e., swarming) of microscale particles in suspension, which can be utilized for numerous applications, such as particle/cell manipulation and targeted drug delivery. However, to date, PTEP for ensemble manipulation has not been well characterized, meaning its potential is yet to be realized.AimOur study aims to provide a characterization of PTEP on the motion and swarming effect of various particles and bacterial cells to allow rational design for bacteria-based microrobots and drug delivery applications.ApproachPlasmonic optical fibers (POFs) were fabricated using two-photon polymerization. The particle motion and swarming behavior near the tips of optical fibers were characterized by image-based particle tracking and analyzing the spatiotemporal concentration variation. These results were further correlated with the shape and surface charge of the particles defined by the zeta potential.ResultsThe PTEP demonstrated a drag force ranging from a few hundred fN to a few tens of pN using the POFs. Furthermore, bacteria with the greater (negative) zeta potential ( | ζ | > 10 mV) and smoother shape (e.g., Klebsiella pneumoniae and Escherichia coli) exhibited the greatest swarming behavior.ConclusionsThe characterization of PTEP-based bacteria swarming behavior investigated in our study can help predict the expected swarming behavior of given particles/bacterial cells. As such, this may aid in realizing the potential of PTEP in the wide-ranging applications highlighted above.
Blagojevic M, Dieudonne A, Kamecki L, et al., 2023, Autonomous electrical current monitoring system for aircraft, IEEE Transactions on Aerospace and Electronic Systems, Vol: 59, Pages: 3345-3358, ISSN: 0018-9251
Aircraft monitoring systems offer enhanced safety, reliability, reduced maintenance cost and improved overall flight efficiency. Advancements in wireless sensor networks (WSN) are enabling unprecedented data acquisition functionalities, but their applicability is restricted by power limitations, as batteries require replacement or recharging and wired power adds weight and detracts from the benefits of wireless technology. In this paper, an energy autonomous WSN is presented for monitoring the structural current in aircraft structures. A hybrid inductive/hall sensing concept is introduced demonstrating 0.5 A resolution, < 2% accuracy and frequency independence, for a 5 A – 100 A RMS, DC-800 Hz current and frequency range, with 35 mW active power consumption. An inductive energy harvesting power supply with magnetic flux funnelling, reactance compensation and supercapacitor storage is demonstrated to provide 0.16 mW of continuous power from the 65 μT RMS field of a 20 A RMS, 360 Hz structural current. A low-power sensor node platform with a custom multi-mode duty cycling network protocol is developed, offering cold starting network association and data acquisition/transmission functionality at 50 μW and 70 μW average power respectively. WSN level operation for 1 minute for every 8 minutes of energy harvesting is demonstrated. The proposed system offers a unique energy autonomous WSN platform for aircraft monitoring.
Wang Z, Lam H-K, Guo Y, et al., 2023, Adaptive Event-Triggered Control for Nonlinear Systems With Asymmetric State Constraints: A Prescribed-Time Approach, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 68, Pages: 3625-3632, ISSN: 0018-9286
Becker T, Kiziroglou ME, Duffy M, et al., 2023, Industrial Adoption of Energy Harvesting: Challenges and Opportunities, IEEE POWER ELECTRONICS MAGAZINE, Vol: 10, Pages: 57-64, ISSN: 2329-9207
Liu M, Zhang Y, Fu H, et al., 2023, A seesaw-inspired bistable energy harvester with adjustable potential wells for self-powered internet of train monitoring, APPLIED ENERGY, Vol: 337, ISSN: 0306-2619
Zhou X, Yang Z, Ren Y, et al., 2023, Modified Bilateral Active Estimation Model: A Learning-Based Solution to the Time Delay Problem in Robotic Tele-Control, IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 8, Pages: 2653-2660, ISSN: 2377-3766
Li X, Keshavarz M, Kassanos P, et al., 2023, SERS detection of breast cancer-derived exosomes using a nanostructured Pt-black template, Advanced Sensor Research, Vol: 4, Pages: 1-12, ISSN: 2751-1219
At present, there are no cancer treatments that are both non-invasive and highly accurate. New tests that can diagnose cancer at an early stage would help to facilitate such improved therapies, and many recent studies have focused on the development of liquid biopsy tests for this purpose. Exosomes are extracellular vesicles secreted by cells as a means of communication that can be simply collected from blood samples. Current studies have shown the potential of surface-enhanced Raman spectroscopy (SERS) in differentiating cancerous cells from healthy cells. Herein, a bespoke platinum-black (Pt-black) SERS template is developed—via a cost-effective fabrication method of electroplating—to detect malfunctioned (cancerous) exosomes. The results demonstrate that the Pt-black SERS substrate exhibits stable and consistent spectra, which produces the high reproducibility required for a reliable diagnostic template. More importantly, using the Pt-black SERS template allows for the differentiation of cancer-derived exosomes (extracted from 4T1 cells—a triple-negative breast cancer cell line) and exosomes from healthy fibroblast cells with an 83.3% sensitivity and a 95.8% specificity. This study establishes the potential of the Pt-black template in detecting cancerous exosomes and lays a solid foundation for future studies in the clinical application of SERS in cancer diagnosis.
Chen X, Zhao J, Vyas K, et al., 2023, Origami-inspired flexure-based robot for endomicroscopy probe manipulation, The 22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Publisher: IEEE
Probe-based confocal endomicroscopy (pCLE) is apromising imaging modality but requires precise andcontrolled scanning over the tissue surface, which issignificantly challenging to the operator. The paperpresents a 3D-printed origami-inspired miniature deltarobot for accurate manipulation of pCLE probe.Kinematics and Finite Element Analysis (FEA) simulationare conducted for a transfer matrix from the applied voltageto the displacement. An open-loop kinematiccharacterization based on the simulation was performed.The results demonstrate adequate repeatability andprecision, allowing the execution of various motions.Further 3D motion control will be achieved by employingvisual servoing.
Shi M, Zhang Y, Guo X, et al., 2023, Microstructure-enhanced vision-based tactile sensor, 22nd International Conference on Solid-State Sensors, Actuators and Microsystems (Transducers 2023)
This paper presents for the first time a vision-based tactile sensor (VBTS) enhanced by micro-structured features. Differing from conventional designs where tracking markers are added to unmodified structures, here an interface surface is constructed with micromachined trenches, which allow varying amounts of light to transmit according to the applied force, forming a matrix of bright cross-shaped patterns on the bottom surface. The variation of brightness, wire width, and location of the cross patterns was captured by a camera and used to sense force magnitude and contact location.Compared to previously reported VBTSs, this microstructured sensor increases the sensitivity by magnifying the visual effect of shape distortion. With theoretical and experimental analysis, this sensor achieved a sensitivity of 20 mN. The resolution reached 1 mm for single-point touch. This sensor is entirely soft and compatible with soft robots and wearable electronics. Unlike piezoelectric sensor arrays, it is immune to electrical crosstalk and interference.
Sun L, Huang Y, Fei H, et al., 2023, Fixed-time regulation of spacecraft orbit and attitude coordination with optimal actuation allocation using dual quaternion, FRONTIERS IN ROBOTICS AND AI, Vol: 10, ISSN: 2296-9144
Wright SW, Kiziroglou ME, Yeatman EM, 2023, Clamped closed-loop flux guides for power line inductive harvesting, 2022 21st International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS), Publisher: IEEE, Pages: 82-85
Inductive harvesting from existing power lines in vehicle, industrial and infrastructure environments offers an opportunity for providing energy autonomy to sensors in a wide range of environments with high sensing interest. Flux funnelling has been shown to improve the power density of such devices by over an order of magnitude. The requirement for retrofitting onto existing power lines leads to a demand for detachable magnetic core interfaces, which introduce gaps and uncertainty to device performance. In this paper, an inductive energy harvesting device design that addresses this challenge is introduced. The design allows the interfaces to be internal to the device housing. Repeatable fixing, with reduced sensitivity to installation practicalities and controllable force is achieved by a screw-pressing mechanism, and the employment of a hard polyoxymethylene housing material. This method is utilized in an inductive power-line prototype, demonstrating power output up to 260 mW from a 40 A RMS, 500 Hz current, emulating aircraft power lines.
Zhang D, Gorochowski TE, Marucci L, et al., 2023, Advanced medical micro-robotics for early diagnosis and therapeutic interventions, Frontiers in Robotics and AI, Vol: 9, Pages: 1-19, ISSN: 2296-9144
Recent technological advances in micro-robotics have demonstrated their immense potential for biomedical applications. Emerging micro-robots have versatile sensing systems, flexible locomotion and dexterous manipulation capabilities that can significantly contribute to the healthcare system. Despite the appreciated and tangible benefits of medical micro-robotics, many challenges still remain. Here, we review the major challenges, current trends and significant achievements for developing versatile and intelligent micro-robotics with a focus on applications in early diagnosis and therapeutic interventions. We also consider some recent emerging micro-robotic technologies that employ synthetic biology to support a new generation of living micro-robots. We expect to inspire future development of micro-robots toward clinical translation by identifying the roadblocks that need to be overcome.
Kiziroglou ME, Yeatman EM, 2023, Energy Harvesters and Power Management, More-than-Moore Devices and Integration for Semi Conductors, Pages: 1-46, ISBN: 9783031216091
Energy harvesting is a subset of Renewable Energy Technologies. It regards specifically the collection of small amounts of ambient energy, typically in the milliwatt range and below, for local use with the objective of providing energy autonomy to microsystems. In this chapter, an overview of the most common energy harvesting methods is presented, including motion, heat and electromagnetic field energy sources. A brief summary of solar, acoustic and radio frequency wave energy harvesting technologies is also presented. Finally, an overview of the main power management technologies developed and employed in energy harvesting is provided. The current state of the art provides adequate tools for developing energy autonomous microsystems in specific applications. Research focusing on integrating these technologies in low-power microchips, for energy autonomous operation in important application environments, such as on the human body or around a mobile phone, could enable new interactive capabilities for electronic information systems within the next 5 years.
We report a miniaturized wet-wet differential pressure sensor with applications in pressure and flow sensing in water networks and other harsh environments. The device is similar in concept to a conventional wet-wet differential pressure sensor in that the sensing element is protected from the external environment by oil-filled cavities closed off by corrugated diaphragms. However, with a package envelope of 11.0 x 4.8 x 3.4 mm 3 , corresponding to a volume of only 0.18 cm 3 , the device is considerably smaller than commercially available wet-wet differential pressure sensors. A high degree of miniaturization has been achieved by using micromachining to fabricate the corrugated diaphragms. Preliminary experimental results are presented showing operation of the device as a delta-pressure flow speed sensor in a water flow test rig.
Cursi F, Bai W, Yeatman EMM, et al., 2022, Task Accuracy Enhancement for a Surgical Macro-Micro Manipulator With Probabilistic Neural Networks and Uncertainty Minimization, IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, ISSN: 1545-5955
Cursi F, Bai W, Yeatman EM, et al., 2022, Optimization of surgical robotic instrument mounting in a macro-micro manipulator setup for improving task execution, IEEE Transactions on Robotics, Vol: 38, Pages: 2858-2874, ISSN: 1552-3098
In Minimally Invasive Robotic Surgery (MIRS),the surgical instrument is usually inserted inside the patient’sbody through a small incision, which acts as a Remote Centerof Motion (RCM). Serial-link manipulators can be used asmacro robots on which micro surgical robotic instruments aremounted to increase the number of degrees of freedom (DOFs)of the system and ensure safe task and RCM motion execution.However, the surgical instrument needs to be placed in anappropriate configuration when completing the motion tasks.The contribution of this work is to present a novel frameworkthat preoperatively identifies the best base configuration, interms or Roll, Pitch, and Yaw angles, of the micro surgicalinstrument with respect to the macro serial-link manipulator’send-effector in order to achieve the maximum accuracy anddexterity in performing specified tasks. The framework relieson Hierarchical Quadratic Programming (HQP) for the control,Genetic Algorithm (GA) for the optimization, and on a resilienceto error strategy to make sure deviations from the optimum donot affect the system’s performance.Simulation results show that the mounting configuration ofthe surgical instrument significantly impacts the performanceof the whole macro-micro manipulator in executing the desiredmotion tasks, and both the simulation and experimental resultsdemonstrate that the proposed optimization method improves theoverall performance.
Chen X, Kiziroglou ME, Yeatman EM, 2022, Linear displacement and force characterisation of a 3D-printed flexure-based delta actuator, Smart Materials and Structures, Vol: 31, Pages: 1-9, ISSN: 0964-1726
Piezoelectric beams provide a fast, high-force and scalable actuation mechanism that could offer precise motion control to medical microdevices including invasive micromanipulators, catheters and diagnosis tools. Their small displacement range can be addressed by motion amplification mechanisms. In this paper, a piezoelectric-actuated delta-robot actuator is proposed for probe-based confocal laser endomicroscopy (pCLE) microsystems. A prototype is designed and fabricated using three-dimensional (3D) polymer compound printing for a multi-flexure compliant motion amplifier and commercial piezoelectric beams. The flexure material is optimised for maximum linear output motion. The overall robot length is 76 mm and its maximum lateral dimension is 32 mm, with 10 g overall mass, including three piezoelectric beams. An axial motion control range of 0.70 mm and a maximum axial force of 20 mN are demonstrated, at 140 V actuation voltage. The proposed actuator architecture is promising for controlling lens, fibre and micromanipulator components for medical microrobotic applications.
Sensor installation on water infrastructure is challenging due to requirements for service interruption, specialised personnel, regulations and reliability as well as the resultant high costs. Here, a minimally invasive installation method is introduced based on hot-tapping and immersion of a sensor probe. A modular architecture is developed that enables the use of interchangeable multi-sensor probes, non-specialist installation and servicing, low-power operation and configurable sensing and connectivity. A prototype implementation with a temperature, pressure, conductivity and flow multi-sensor probe is presented and tested on an evaluation rig. This paper demonstrates simple installation, reliable and accurate sensing capability as well as remote data acquisition. The demonstrated minimally invasive multi-sensor probes provide an opportunity for the deployment of water quality sensors that typically require immersion such as pH and spectroscopic composition analysis. This design allows dynamic deployment on existing water infrastructure with expandable sensing capability and minimal interruption, which can be key to addressing important sensing parameters such as optimal sensor network density and topology.
Wales DJ, Keshavarz M, Howe C, et al., 2022, 3D Printability Assessment of Poly(octamethylene maleate (anhydride) citrate) and Poly(ethylene glycol) Diacrylate Copolymers for Biomedical Applications, ACS APPLIED POLYMER MATERIALS, Vol: 4, Pages: 5457-5470, ISSN: 2637-6105
Cursi F, Bai W, Yeatman EM, et al., 2022, Model learning with backlash compensation for a tendon-driven surgical Robot, IEEE Robotics and Automation Letters, Vol: 7, Pages: 7958-7965, ISSN: 2377-3766
Robots for minimally invasive surgery are becoming more and more complex, due to miniaturization and flexibility requirements. The vast majority of surgical robots are tendon-driven and this, along with the complex design, causes high nonlinearities in the system which are difficult to model analytically. In this work we analyse how incorporating a backlash model and compensation can improve model learning and control. We combine a backlash compensation technique and a Feedforward Artificial Neural Network (ANN) with differential relationships to learn the kinematics at position and velocity level of highly articulated tendon-driven robots. Experimental results show that the proposed backlash compensation is effective in reducing nonlinearities in the system, that compensating for backlash improves model learning and control, and that our proposed ANN outperforms traditional ANN in terms of path tracking accuracy.
Cursi F, Bai W, Li W, et al., 2022, Augmented neural network for full robot kinematic modelling in SE(3), IEEE Robotics and Automation Letters, Vol: 7, Pages: 7140-7147, ISSN: 2377-3766
Due to the increasing complexity of robotic structures, modelling robots is becoming more and more challenging, and analytical models are very difficult to build. Machine learning approaches have shown great capabilities in learning complex mapping and have widely been used in robot model learning and control. Generally, the inverse kinematics is directly learned, yet, learning the forward kinematics is simpler and allows computing exploiting the optimality of the controllers. Nevertheless, the learning method has no knowledge about the differential relationship between the position and velocity mappings. Currently, few works have targeted learning full robot poses considering both position and orientation. In this letter, we present a novel feedforward Artificial Neural network (ANN) architecture to learn full robot pose in SE(3) incorporating differential relationships in the learning process. Simulation and real world experiments show the capabilities of the proposed network to properly model the robot pose and its advantages over standard ANN.
Arteaga JM, Mitcheson PD, Yeatman EM, 2022, Development of a fast-charging platform for buried sensors using high frequency IPT for agricultural applications, 2022 IEEE Applied Power Electronics Conference and Exposition (APEC), Publisher: IEEE, Pages: 1116-1121
This paper describes the methodology and experimental results for wireless power delivery to a soil-sensors power and data distribution unit from an unmanned aerial vehicle (UAV), using a high frequency inductive power transfer (HF-IPT) link. The configuration features, at the transmit side, a lightweight single-turn air-core coil driven by a 13.56 MHz Class EF inverter mounted on a Matrice 100 drone by DJI, and at the receive side, a two-turn PCB coil with a voltage-tipler Class D rectifier, an off-the-shelf 42 V battery charger and a supercapacitors module for energy storage. The experiments were conducted with a coil-to-coil gap of 250 mm, which corresponds to a coupling factor lower than 5%. In the experiments, a 10 F, 42 V supercapacitors module was charged in eleven minutes with an energy efficiency of 34% from the 80 V DC source that feeds the inverter on the drone to the supercapacitor-based energy storage unit in the sensor module. At higher power (50 W) the HF-IPT system was able to achieve a 68% DC-DC efficiency with a coupling factor of 3.5%. The work reported in this paper is part of a multiple-discipline project which looks to enable the optimal usage of water in agriculture with broader sensing techniques and more frequent sensing cycles.
Kiziroglou ME, Wright SW, Yeatman EM, 2022, Power supply based on inductive harvesting from structural currents, IEEE Internet of Things Journal, Vol: 9, ISSN: 2327-4662
Monitoring infrastructure offers functional optimisation, lower maintenance cost, security, stability and data analysis benefits. Sensor nodes require some level of energy autonomy for reliable and cost-effective operation, and energy harvesting methods have been developed in the last two decades for this purpose. Here, a power supply that collects, stores and delivers regulated power from the stray magnetic field of currentcarrying structures is presented. In cm-scale structures the skin effect concentrates current at edges at frequencies even below 1 kHz. A coil-core inductive transducer is designed. A fluxfunnelling soft magnetic core shape is used, multiplying power density by the square of funnelling ratio. A power management circuit combining reactance cancellation, voltage doubling, rectification, super-capacitor storage and switched inductor voltage boosting and regulation is introduced. The power supply is characterised in house and on a full-size industrial setup, demonstrating a power reception density of 0.36 mW/cm3, 0.54 mW/cm3 and 0.73 mW/cm3 from a 25 A RMS structural current at 360 Hz, 500 Hz and 800 Hz respectively, corresponding to the frequency range of aircraft currents. The regulated output is tested under various loads and cold starting is demonstrated. The introduced method may enable power autonomy to wireless sensors deployed in current-carrying infrastructure.
Gil Rosa B, Akingbade OE, Guo X, et al., 2022, Multiplexed immunosensors for point-of-care diagnostic applications, Biosensors and Bioelectronics, Vol: 203, ISSN: 0956-5663
Accurate, reliable, and cost-effective immunosensors are clinically important for the early diagnosis and monitoring of progressive diseases, and multiplexed sensing is a promising strategy for the next generation of diagnostics. This strategy allows for the simultaneous detection and quantification of multiple biomarkers with significantly enhanced reproducibility and reliability, whilst requiring smaller sample volumes, fewer materials, and shorter average analysis time for individual biomarkers than individual tests. In this opinionated review, we compare different techniques for the development of multiplexed immunosensors. We review the state-of-the-art approaches in the field of multiplexed immunosensors using electrical, electrochemical, and optical methods. The barriers that prevent translating this sensing strategy into clinics are outlined together with the potential solutions. We also share our vision on how multiplexed immunosensors will continue their evolution in the coming years.
Bacha SC, Bai W, Wang Z, et al., 2022, Deep Reinforcement Learning-Based Control Framework for Multilateral Telesurgery, IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS, Vol: 4, Pages: 352-355
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