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This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This study aims to introduce a novel technique for nonlinear sensor time constant estimation and sensor dynamic compensation in hot-bar soldering using an extended Kalman filter (EKF) to estimate the temperature of the thermocouple.

Temperature optimal control is combined with a closed-loop proportional integral differential (PID) control method based on an EKF. Different control methods for measuring the temperature of the thermode in terms of temperature control, error and antidisturbance are studied. A soldering process in a semi-industrial environment is performed. The proposed control method was applied to the soldering of flexible printed circuits and circuit boards. An infrared camera was used to measure the top-surface temperature.

The proposed method can not only estimate the soldering temperature but also eliminate the noise of the system. The performance of this methodology was exemplary, characterized by rapid convergence and negligible error margins. Compared with the conventional control, the temperature variability of the proposed control is significantly attenuated.

An EKF was designed to estimate the temperature of the thermocouple during hot-bar soldering. Using the EKF and PID controller, the nonlinear properties of the system could be effectively overcome and the effects of disturbances and system noise could be decreased. The proposed method significantly enhanced the temperature control performance of hot-bar soldering, effectively suppressing overshoot and shortening the adjustment time, thereby achieving precise temperature control of the controlled object.

This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time, energy and material.

The approach is designed based on the frequently observed fact that printing failures are accompanied by abnormal material phenomena occurring close to the nozzle. To effectively and timely capture the phenomena near the nozzle, a camera is delicately installed on a typical MEX printer. Then, aided by the captured phenomena (images), a smart printing failure predictor is built based on the artificial neural network (ANN). Finally, based on the predictor, the printing failures, as well as their types, can be effectively detected from the images captured by the camera in real-time.

Experiments show that printing failures can be detected timely with an accuracy of more than 98% on average. Comparisons in methodology demonstrate that this approach has advantages in real-time printing failure detection in MEX.

A novel real-time approach for failure detection is proposed based on ANN. The following characteristics make the approach have a great potential to be implemented easily and widely: (1) the scheme designed to capture the phenomena near the nozzle is simple, low-cost, and effective; and (2) the predictor can be conveniently extended to detect more types of failures by using more abnormal material phenomena that are occurring close to the nozzle.

The purpose of this paper was to investigate how variations in the geometry of silicon chips and the presence of surface defects affect their static bending properties. By comparing the bending radius and strength across differently sized and treated chips, the study sought to understand the underlying mechanics that contribute to the flexibility of silicon-based electronic devices. This understanding is crucial for the development of advanced, robust and adaptable electronic systems that can withstand the rigors of manufacturing and everyday use.

This study explores the impact of silicon chip geometry and surface defects on flexibility through a multifaceted experimental approach. The methodology included preparing silicon chips of three distinct dimensions and subjecting them to thinning processes to achieve a uniform thickness verified via scanning electron microscopy (SEM). Finite element method (FEM) simulations and a series of four-point bending tests were used to analyze the bending flexibility theoretically and experimentally. The approach was comprehensive, examining both the intrinsic geometric factors and the extrinsic influence of surface defects induced by manufacturing processes.

The findings revealed a significant deviation between the theoretical predictions from FEM simulations and the experimental outcomes from the four-point bending tests. Rectangular-shaped chips demonstrated superior flexibility, with smaller dimensions leading to an increased bending strength. Surface defects, identified as critical factors affecting flexibility, were analyzed through SEM and atomic force microscopy, showing that etching processes could reduce defect density and enhance flexibility. Notably, the study concluded that surface defects have a more pronounced impact on silicon chip flexibility than geometric factors, challenging initial assumptions and highlighting the need for defect minimization in chip manufacturing.

This research contributes valuable insights into the design and fabrication of flexible electronic devices, emphasizing the significant role of surface defects over geometric considerations in determining silicon chip flexibility. The originality of the work lies in its holistic approach to dissecting the factors influencing silicon chip flexibility, combining theoretical simulations with practical bending tests and surface defect analysis. The findings underscore the importance of optimizing manufacturing processes to reduce surface defects, thereby paving the way for the creation of more durable and flexible electronic devices for future technologies.

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

This paper aims to present the design development and measurement of two aerodynamic slotted X-bands back-to-back planer substrate-integrated rectangular waveguide (SIRWG/SIW) to Microstrip (MS) line transition for satellite and RADAR applications. It facilitates the realization of nonplanar (waveguide-based) circuits into planar form for easy integration with other planar (microstrip) devices, circuits and systems. This paper describes the design of a SIW to microstrip transition. The transition is broadband covering the frequency range of 8–12 GHz. The design and interconnection of microwave components like filters, power dividers, resonators, satellite dishes, sensors, transmitters and transponders are further aided by these transitions. A common planar interconnect is designed with better reflection coefficient/return loss (RL) (S₁₁/S₂₂ ≤ 10 dB), transmission coefficient/insertion loss (IL) (S₁₂/S₂₁: 0–3.0 dB) and ultra-wideband bandwidth on low profile FR-4 substrate for X-band and Ku-band functioning to interconnect modern era MIC/MMIC circuits, components and devices.

Two series of metal via (6 via/row) have been used so that all surface current and electric field vectors are confined within the metallic via-wall in SIW length. Introduced aerodynamic slots in tapered portions achieve excellent impedance matching and tapered junctions with SIW are mitered for fine tuning to achieve minimum reflections and improved transmissions at X-band center frequency.

Using this method, the measured IL and RLs are found in concord with simulated results in full X-band (8.22–12.4 GHz). RLC T-equivalent and p-equivalent electrical circuits of the proposed design are presented at the end.

The measurement of the prototype has been carried out by an available low-cost X-band microwave bench and with a Keysight E4416A power meter in the microwave laboratory.

The transition is fabricated on FR-4 substrate with compact size 14 mm × 21.35 mm × 1.6 mm and hence economical with IL lie within limits 0.6–1 dB and RL is lower than −10 dB in bandwidth 7.05–17.10 GHz. Because of such outstanding fractional bandwidth (FBW: 100.5%), the transition could also be useful for Ku-band with IL close to 1.6 dB.

Tactile sensation is an important sensory function for robots in contact with the external environment. To better acquire tactile information about objects, this paper aims to propose a three-layer structure of the interdigital flexible tactile sensor.

The sensor consists of a bottom electrode layer, a middle pressure-sensitive layer and a top indenter layer. First, the pressure sensitive material, structure design, fabrication process and circuit design of the sensor are introduced. Then, the calibration and performance test of the designed sensor is carried out. Four functions are used to fit and calibrate the relationship between the output voltage of the sensor and the contact force. Finally, the contact force sensing test of different weight objects and the flexible test of the sensor are carried out.

The performance test results show that the sensitivity of the sensor is 0.93 V/N when it is loaded with 0–3 N and 0.23 V/N when it is loaded with 3–5 N. It shows good repeatability, and the cross-interference between the sensing units is generally low. The contact force sensing test results of different weight objects show that the proposed sensor performs well in contact force. Each part of the sensor is a flexible material, allowing the sensor to achieve bending deformation, so that the sensor can better perceive the contact signs of the grasped object.

The sensor can paste the surface of the paper robot’s gripper to measure the contact force of the grasping object and estimate the contour of the object.

In this paper, a three-layer interdigital flexible tactile sensor is proposed, and the structural parameters of the interdigital electrode are designed to improve the sensitivity and response speed of the sensor. The indenter with three shapes of the prism, square cylinder and hemisphere is preliminarily designed and the prism indenter with better conduction force is selected through finite element analysis, which can concentrate the external force in the sensing area to improve the sensitivity. The sensor designed in this paper can realize the measurement of contact force, which provides a certain reference for the field of robot tactile.

The purpose of this study is to describe the design and validation of a three-dimensional (3D)-printed phantom of a uterus to support the development of uterine balloon tamponade devices conceived to stop post-partum haemorrhages (PPHs).

The phantom 3D model is generated by analysing the main requirements for validating uterine balloon tamponade devices. A modular approach is implemented to guarantee that the phantom allows testing these devices under multiple working conditions. Once finalised the design, the phantom effectiveness is validated experimentally.

The modular phantom allows performing the required measurements for testing the performance of devices designed to stop PPH.

PPH is the leading obstetric cause of maternal death worldwide, mainly in low- and middle-income countries. The proposed phantom could speed up and optimise the design and validation of devices for PPH treatment, reducing the maternal mortality ratio.

To the best of the authors’ knowledge, the 3D-printed phantom represents the first example of a modular, flexible and transparent uterus model. It can be used to validate and perform usability tests of medical devices.

This paper aims to illustrate the growing role of robots in the electronics industries.

Following a short introduction, this paper discusses robotic applications and products in three sectors of the electronics industry: semiconductor processing, printed circuit manufacture and electronic product assembly. Finally, conclusions are drawn.

The major application in semiconductor manufacture is the handling of silicon wafers during both front- and back-end processes and products include cleanroom certified multi-axis robotic arms, some mounted on mobile platforms, and automated guided vehicles. Applications in printed circuit board production include component handling and insertion, soldering, inspection, testing and packing. These exploit Cartesian, SCARA and six-axis articulated robots and cobots play an important role where automated and manual processes operate in close proximity. Electronic product assembly applications include part handling, soldering, bonding and sealing, screw driving, test and inspection and packaging. Cobots offer the benefits of a small footprint which allows deployment in the often limited space and use in proximity to humans. As yet, robotic assembly of complex electronic products such as smartphones and computers has not been realised for technical reasons.

This study provides a detailed review of robotic products and applications in three key sectors of the electronics industries.