ABSTRACT 3D‐printed flexible strain sensors are attracting increasing interest in wearable health monitoring, soft robotics, and broader mechanical sensing because 3D‐printing enables compliant, geometry‐controlled, and increasingly integrated sensor architectures. This systematic review, conducted in accordance with PRISMA 2020, examines 76 peer‐reviewed experimental studies published between February 2014 and March 2026 on 3D‐printed flexible strain sensors. The analysis compares 3D‐printing routes, conductive material systems, transduction mechanisms, application domains, gauge‐factor reporting modes, strain‐range reporting, and durability‐related performance metrics. A key contribution of this review is the traceable separation of linear and maximum gauge factor reporting, together with the distinction between linear operating range and absolute strain capacity. Material extrusion emerged as the dominant manufacturing approach and was most strongly associated with carbon‐based conductive elastomer composites, whereas direct ink writing and vat photopolymerization were more widely implemented for ionic, hydrogel, and ionogel‐based systems. Around 20% of studies reported linear gauge factor, whereas more than 50% reported maximum gauge factor; similarly, absolute strain capacity was extractable in more than 60% of studies, but clearly defined linear operating ranges were reported far less consistently. Overall, 3D printing should be regarded as a design framework for co‐optimizing material, structure, and sensing function.

This article explores recent advancements in robotic systems for environmental monitoring (EM). It covers various types of sensors employed in this field, including air quality sensors, temperature and humidity sensors, and wind speed and pressure sensors. These sensors are categorized based on their primary sensing mechanisms, such as electrochemical, metal oxide, photoionization, and optical sensors. This article also provides a comprehensive review of robotic systems used in EM, detailing their applications in wildlife observation, conservation, habitat mapping, atmospheric studies, vegetation and forest health monitoring, agricultural crop assessment, coastal and marine environment monitoring, and disaster response. The review includes an examination of different robotic platforms, including wheeled robots, legged robots, and drones.

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Many indoor robots operate in environments designed to support human activities. Understanding probable human actions in such surroundings is crucial for facilitating better human-robot interactions. This article presents an innovative approach to map unseen human actions in indoor environments by leveraging spatial affordances learned from geometric features extracted from point clouds captured by 3D cameras. Instead of directly observing real people to understand human context, the method utilizes virtual human models and their interactions with the environment to uncover hidden human affordances. This approach proves to be efficient for learning the affordance map, even when dealing with highly imbalanced datasets. To achieve this, we employ a supervised learning model optimized for the F1 score, using the Structured-SVM (S-SVM) architecture. We conducted experiments with actual 3D scenes, evaluating various affordance types both qualitatively and quantitatively. The results show that the proposed S-SVM-based method outperforms other models, demonstrating its effectiveness in efficiently mapping human context in indoor environments. The S-SVM-based method outperformed other models, demonstrating efficient human context mapping in indoor environments.

Recent advancements in exoskeleton technology, both passive and active, are driven by the need to enhance human capabilities across various industries as well as the need to provide increased safety for the human worker. This review paper examines the sensors, actuators, mechanisms, design, and applications of passive and active exoskeletons, providing an in-depth analysis of various exoskeleton technologies. The main scope of this paper is to examine the recent developments in the exoskeleton developments and their applications in different fields and identify research opportunities in this field. The paper examines the exoskeletons used in various industries as well as research-level prototypes of both active and passive types. Further, it examines the commonly used sensors and actuators with their advantages and disadvantages applicable to different types of exoskeletons. Communication protocols used in different exoskeletons are also discussed with the challenges faced.

In this paper, a comprehensive review of the wireless body area network is provided. A review of the WBAN architectures, standard network topologies, and WBAN communication protocols is discussed in detail. Also, the security requirements of WBAN, security threats and types of attacks, and authentications used in WBAN are discussed. The paper also includes very detailed coverage of antenna types, antenna designs, and flexible antennas used in WBAN with some design considerations and comparisons. Some new energy harvesting technologies, materials used for energy harvesting, and energy management are also discussed. Energy harvesting and power management is an ever-growing area of research. Despite the fact that there are many nanogenerator-based energy harvesting methods, the demand for more efficient energy harvesting mechanisms is ever-increasing. The paper has an extensive discussion of energy harvesting and power management methods. Subsequently, some reviews of recent developments in wearable sensors and novel materials for developing wearable sensors are discussed. Finally, the application areas of WBAN are discussed

Recent developments in networked and smart sensors have significantly changed the way Structural Health Monitoring (SHM) and asset management are being carried out. Since the sensor networks continuously provide real-time data from the structure being monitored, they constitute a more realistic image of the actual status of the structure where the maintenance or repair work can be scheduled based on real requirements. This review is aimed at providing a wealth of knowledge from the working principles of sensors commonly used in SHM, to artificial-intelligence-based digital twin systems used in SHM and proposes a new asset management framework. The way this paper is structured suits researchers and practicing experts both in the fields of sensors as well as in asset management equally.

Cerebral temperature is one of the key indicators of fever, trauma, and physical activity. It has been reported that the temperature of the healthy brain is up to 2 °C higher than the core body temperature. The main methods to monitor brain temperature include infrared spectroscopy, radiometry, and acoustic thermometry. While these methods are useful, they are not very effective when portability is desired, the temperature needs to be monitored for a longer period, or localized monitoring is required. This paper presents a short review of invasive and non-invasive brain temperature monitoring sensors and tools. We discuss the type of temperature sensors that can be integrated with probes. Furthermore, implantable and bioresorbable sensors are briefly mentioned. Biocompatibility and invasiveness of the sensors in terms of their functional materials, encapsulation, and size are highlighted.

We propose a low-cost internet of things (IoT)-enabled COVID-19 standard operating procedure (SOP) compliance system that counts the number of people entering and leaving a vicinity, ensures physical distancing, monitors body temperature and warns attendees and managers of violations. The system comprises of multiple sensor nodes communicating with a centralized server. The data stored on the server can be used for compliance auditing, real-time monitoring, and planning purposes. The system does not record the personal information of attendees nor provide contact tracing information.

In this paper we propose a method which is useful to measure out of plane displacement of beams. The proposed method is targeted to be effective in micro fabrication applications where a speckle pattern is impossible to make on the microactuators. However, microfabrication techniques where etch holes are used to release actuator beams can make use of this method. The paper presents the application of image processing techniques that can be exploited to measure effective in-plane pixel displacement for a corresponding out of plane (vertical) beam displacements. Firstly, a calibration measurement is taken at known beam deflections. Secondly, beam deflection at various unknown points can be extracted. Lastly, a profile of the beam deflection along its length can be achieved for any deflection.

The design of a micromirror for biomedical applications requires multiple output responses to be optimized, given a set of performance parameters and constraints. This paper presents the parametric design optimization of an electrothermally actuated micromirror for the deflection angle, input power, and micromirror temperature rise from the ambient for Optical Coherence Tomography (OCT) system. Initially, a screening design matrix based on the Design of Experiments (DOE) technique is developed and the corresponding output responses are obtained using coupled structural-thermal-electric Finite Element Modeling (FEM). The interaction between the significant design factors is analyzed by developing Response Surface Models (RSM) for the output responses. The output responses are optimized by combining the individual responses into a composite function using desirability function approach. A downhill simplex method, based on the heuristic search algorithm, is implemented on the RSM models to find the optimal levels of the design factors. The predicted values of output responses obtained using multi-response optimization are verified by the FEM simulations.

This paper proposes an optimal defect shape to increase the sensitivity of a MEMS cantilever based piezo resistive sensor. This work describes the sensitivity improvement using Stress concentration region (SCR) introduced in the cantilever beam. The SCR improves the surface stress on the cantilever beam and enhances the sensitivity of the sensor. A particular defect (sigma star) is introduced which is designed and place in a way that increases the sensitivity by about 20%.

Visually impaired individuals are not able to peruse like ordinary people. Tactile technologies are helpful for those to read through sense of touch but these technologies are not yet widely available, due to their high cost, non ideal response and degree of safety. In this research an attempt is made on designing an affordable and useable MEMS (Microelectromechanical system) based Braille system, offering an efficient way in improving readability of visually impaired people. Our ultimate goal is to design a wearable system that converts digital text files into tactile signals using USB port. This system will be based on MEMS actuators that would mimic these Braille dots. In this paper such a Braille system is presented having overall size of 9mm*16mm. In comparison with other MEMS based Braille systems, this design requires low input voltage i.e. 0.6V in order to produce required deflection of 0.25mm of Braille dot. With the help of this tactile display visual impaired person can read with the speed of sighted human beings. The device is easy to wear as the material and operating temperature are not harmful to the human skin.

The paper presents the design of a fully functional self balancing vehicle capable of bearing the human load using the principle of dynamic stability. Requirement of the venture includes designing and fabrication of Segway and BLDC motor controller, modeling of the system and implementation of control for stabilization. Indigenous electronic circuitry, accelerometer and BLDC motor controller are used in the system. 500 Watt power motor makes this Segway capable of bearing the human load. It includes static and dynamic analysis of Segway on ANSYS, designing of BLDC Motor controller, mathematical modeling of the system and designing of the PID controller using Root Locus Analysis and implementation on Segway.

Every year hundreds of people lose their lives because of land mine explosions. The objective of this paper is to design a manipulator on which a mine detector can be mounted as its end effector and can effectively perform mine detection operation. In this paper the major factors for designing a 3 degree of freedom manipulator are discussed. These include design considerations, inverse kinematics, torque, velocity, stress, deformation analysis and centre of mass calculations are presented. A numerical approach is presented here for a manipulator design to achieve the required task. This robotic manipulator can support a robotic end effector (specifically mine detector) up to 2 kg.

Energy needs are becoming more and more complex, especially in underdeveloped countries. The solar energy is one of best solution for increasing demand of energy by mankind. Sun energy can fulfil our domestic and irrigation requirement because fossil fuels are running short day by day. Therefore, it is one of the most important source of energy to explore for its maturity. In this paper, kinematic and energy analysis of two solar trackers panel systems are studied comparatively for maximising efficiency. Structure of model 1 (single axis tracker) previously designed was bulky, causing the linear actuator to consume more electrical energy. Kinematic and force analysis of model 1 showed the drawbacks of displaced centre of gravity and excessive energy consumption due to weight of frame which supports the panel. Based on kinematic and force analysis of model 1, new model 2 has been designed in which all the above problems are addressed by shifting the centre of gravity on the axis of rotation, reducing weight of upper frame and readjusting the rotating mechanism. The calculation shows 39.5 % decreased consumption of energy by linear actuator. The new design also reduces material cost by approximately 34%. This research supports only small (Domestic) systems and can be applied to practical projects.

This paper will provide the kinematic and dynamic analysis of a lower limb exoskeleton. The forward and inverse kinematics of proposed exoskeleton is performed using Denevit and Hartenberg method. The torques required for the actuators will be calculated using Lagrangian formulation technique. This research can be used to design the control of the proposed exoskeleton. Keywords—Dynamic Analysis, Exoskeleton, Kinematic Analysis, Lower Limb, Rehabilitation Robotics

An optimized circuit for processing of EMG signals has been designed and presented in this paper. This circuit acquires EMG signals from surface of the skin using bipolar electrodes and enables the amputee to control the prosthetic hand in an efficient manner. EMG can be defined as the electrical potential produced due to the contraction of muscle. It can be picked from the residual portion of muscles of an amputee. EMG signal requires the processes of amplification, band limiting and rectification, before it can be fed to an analog to digital converter (ADC) and subsequently to motors driving the prosthetic device.