An inclined demand for flexible and wearable electronics, driven by progress in artificial intelligence technologies, underscores the significance of auxetic sensors in healthcare, medical rehabilitation, soft robotics, and humanmachine interfaces. To achieve widespread adoption, these sensors should exhibit high sensitivity, exceptional stretchability, and long-lasting durability. This paper delves into the potential for developing such wearable soft strain sensors based on conductive thermoplastic polyurethane (cTPU) 3D printed as auxetic soft metamaterials. Simultaneous empirical mechanical and electrical measurements for the auxetic soft sensor designs were compared with numerical simulations. Following the auxetic cTPU soft strain sensor was tested in human gait analytics to predict the gait type of the wearer by employing a single auxetic cTPU soft strain sensor. The results suggest that such soft sensors based on metamaterials are genuine candidates for applications in robotic, healthcare and human-robot interfaces when realized with 3D printing and artificial intelligence.

Alginate hydrogels offer distinct advantages as ionically crosslinked, biocompatible networks that can be shaped into spherical beads with high compositional flexibility. These spherical architectures provide isotropic geometry, modularity and the capacity for encapsulation, making them ideal platforms for scalable, stimuli-responsive actuation. Their ability to respond to thermal, magnetic, electrical, optical and chemical stimuli has enabled applications in targeted delivery, artificial muscles, microrobotics and environmental interfaces. This review examines recent advances in alginate sphere-based actuators, focusing on fabrication methods such as droplet microfluidics, coaxial flow and functional surface patterning, and strategies for introducing multi-stimuli responsiveness using smart polymers, nanoparticles and biologically active components. Actuation behaviours are understood and correlated with physical mechanisms including swelling kinetics, photothermal effects and the field-induced torque, supported by analytical and multiphysics models. Their demonstrated functionalities include shape transformation, locomotion and mechano-optical feedback. The review concludes with an outlook on the existing limitations, such as the material stability, cyclic durability and integration complexity, and proposes future directions toward the development of autonomous, multifunctional soft systems.

The surge in flexible and wearable electronics, fueled by advancements in smart technologies and growing market demand, has highlighted the importance of auxetic sensors for applications in healthcare, medical rehabilitation, soft robotics, and human-machine interfaces. For widespread adoption, these sensors must offer high sensitivity, substantial stretchability, and long-term durability. This study explores the possibilities of realizing such wearable soft sensors based on conductive thermoplastic polyurethane (cTPU) 3D printing enhanced with auxetic mechanical metamaterials. Following simultaneous empirical mechanical and electrical measurements, auxetic soft sensor designs were compared with numerical simulations. Results suggest that such soft sensors based on metamaterials are great candidates for applications in healthcare and robotics when realized with 3D printing.

The Internet of Things (IoT) has the potential to revolutionise daily life by connecting various devices and enabling smart functionalities. However, a critical issue in this realm is the charging problem faced by mosquito repellent devices. This paper introduces MOSQ-Charge, a system that focuses on wirelessly charging smart mosquito repellents within an IoT framework. Comprising five key components, including a wireless charger, Smart IoT Gateway, cloud services, security algorithm, and device control application, MOSQ-Charge aims to enhance home automation by addressing the charging concerns of mosquito repellent devices. The system utilises sensors to monitor battery levels, cloud services for data storage, and an IoT connectivity protocol named MQTT to link gateways to the cloud server. By designing and deploying a successful wireless charging setup for MOSQ-Charge, this research contributes to controlling mosquito-borne diseases and advancing IoT-based home automation.

Walking is a complex process requiring various musculoskeletal muscles' synchronized actions. Abnormal gait increases the risk of joint deformities, and foot pronation or supination is a common health issue. Wearable technologies for health monitoring have gained significant momentum. This study used an IMU to collect components of foot location (x, y, z) for detecting gait deformities such as pronation and supination. A machine learning classifier was developed to categorize different types of gaits: pronation, supination, and normal. The classification process was conducted in two phases. In Phase 1, the classes were pronation, supination, and normal. In Phase 2, the classes were severe pronation, pronation, normal, supination, and severe supination. The highest accuracy achieved in Phase 1 was 97%, while Phase 2 reached an accuracy of 99.2%. The novelty of this work lies in the sensor location, which is more convenient for the user than the current in-sole sensors. The proposed solution effectively corrects foot posture and is particularly efficient for cohorts like the elderly and children.

Smart sensing devices enabled hydroponics, a concept of vertical farming that involves soilless technology that increases green area. Although the cultivation medium is water, hydroponic cultivation uses 13 ± 10 times less water and gives 10 ± 5 times better quality products compared with those obtained through the substrate cultivation medium. The use of smart sensing devices helps in continuous real-time monitoring of the nutrient requirements and the environmental conditions required by the crop selected for cultivation. This, in turn, helps in enhanced year-round agricultural production. In this study, lettuce, a leafy crop, is cultivated with the Nutrient Film Technique (NFT) setup of hydroponics, and the growth results are compared with cultivation in a substrate medium. The leaf growth was analyzed in terms of cultivation cycle, leaf length, leaf perimeter, and leaf count in both cultivation methods, where hydroponics outperformed substrate cultivation. The results of the ‘AquaCrop simulator also showed similar results, not only qualitatively and quantitatively, but also in terms of sustainable growth and year-round production. The energy consumption of both the cultivation methods is compared, and it is found that hydroponics consumes 70 ± 11 times more energy compared to substrate cultivation. Finally, it is concluded that smart sensing devices form the backbone of precision agriculture, thereby multiplying crop yield by real-time monitoring of the agronomical variables.

This paper proposes a new variable stiffness soft gripper that enables high-performance grasping tasks in industrial applications. The design of the proposed monolithic soft gripper includes a middle bellow and two side bellows (i.e., fingers). The positions of the fingers are regulated by adjusting the negative pressure in the middle bellow actuator via an on-off controller. The stiffness of the soft gripper is modulated by controlling the positive pressure in the fingers through the use of a proportional air-pressure regulator. It is experimentally shown that the proposed soft gripper can modulate its stiffness by 125% within 250ms. It is also shown that the variable stiffness soft gripper can help improve the safety and performance of grasping tasks in industrial applications.

Haptics plays a significant role not only in the rehabilitation of neurological disorders, such as stroke, by substituting necessary cognitive information but also in human-computer interfaces (HCIs), which are now an integral part of the recently launched metaverse. This study proposes a unique, soft, monolithic haptic feedback device (SoHapS) that was directly manufactured using a low-cost and open-source fused deposition modeling (FDM) 3D printer by employing a combination of soft conductive and nonconductive thermoplastic polyurethane (TPU) materials (NinjaTek, USA). SoHapS consists of a soft bellow actuator and a soft resistive force sensor, which are optimized using finite element modeling (FEM). SoHapS was characterized both mechanically and electrically to assess its performance, and a dynamic model was developed to predict its force output with given pressure inputs. We demonstrated the efficacy of SoHapS in substituting biofeedback with tactile feedback, such as gripping force, and proprioceptive feedback, such as finger flexion-extension positions, in the context of teleoperation. With its intrinsic properties, SoHapS can be integrated into rehabilitation robots and robotic prostheses, as well as augmented, virtual, and mixed reality (AR/VR/MR) systems, to induce various types of bio-mimicked feedback.

This study proposes a new hybrid multi-modal sensory feedback system for prosthetic hands that can provide not only haptic and proprioceptive feedback but also facilitate object recognition without the aid of vision. Modality-matched haptic perception was provided using a mechanotactile feedback system that can proportionally apply the gripping force through the use of a force controller. A vibrotactile feedback system was also employed to distinguish four discrete grip positions of the prosthetic hand. The system performance was evaluated with a total of 32 participants in three different experiments (i) haptic feedback, (ii) proprioceptive feedback and (iii) object recognition with hybrid haptic-proprioceptive feedback. The results from the haptic feedback experiment showed that the participants' ability to accurately perceive applied force depended on the amount of force applied. As the feedback force was increased, the participants tended to underestimate the force levels, with a decrease in the percentage of force estimation. Of the three arm locations (forearm volar, forearm ventral and bicep), and two muscle states (relaxed and tensed) tested, the highest accuracy was obtained for the bicep location in the relaxed state. The results from the proprioceptive feedback experiment showed that participants could very accurately identify four different grip positions of the hand prosthesis (i.e., open hand, wide grip, narrow grip, and closed hand) without a single case of misidentification. In experiment 3, participants could identify objects with different shapes and stiffness with an overall high success rate of 90.5% across all combinations of location and muscle state. The feedback location and muscle state did not have a significant effect on object recognition accuracy. Overall, our study results indicate that the hybrid feedback system may be a very effective way to enrich a prosthetic hand user's experience of the stiffness and shape of commonly manipulated objects.

This article expounds the design and control of a new variable stiffness series elastic actuator (VSSEA). It is established by employing a modular mechanical design approach that allows us to effectively optimize the stiffness modulation characteristics and power density of the actuator. The proposed VSSEA possesses the following features: no limitation in the work range of output link; a wide range of stiffness modulation (∼20 N·m/rad to ∼1 KN·m/rad); low-energy-cost stiffness modulation at equilibrium and nonequilibrium positions; compact design and high torque density (∼36 N·m/kg); and high-speed stiffness modulation (∼3000 N·m/rad/s). Such features can help boost the safety and performance of many advanced robotic systems, e.g., a cobot that physically interacts with unstructured environments and an exoskeleton that provides physical assistance to human users. These features can also enable us to utilize variable stiffness property to attain various regulation and trajectory tracking control tasks only by employing conventional controllers, eliminating the need for synthesizing complex motion control systems in compliant actuation. To this end, it is experimentally demonstrated that the proposed VSSEA is capable of precisely tracking the desired position and force control references through the use of the conventional proportional–integral–derivative controllers.

A single universal robotic gripper with the capacity to fulfill a wide variety of gripping and grasping tasks has always been desirable. A three-dimensional (3D) printed modular soft gripper with highly conformal soft fingers that are composed of positive pressure soft pneumatic actuators along with a mechanical metamaterial was developed. The fingers of the soft gripper along with the mechanical metamaterial, which integrates a soft auxetic structure and compliant ribs, was 3D printed in a single step, without requiring support material and postprocessing, using a low-cost and open-source fused deposition modeling (FDM) 3D printer that employs a commercially available thermoplastic poly (urethane) (TPU). The soft fingers of the gripper were optimized using finite element modeling (FEM). The FE simulations accurately predicted the behavior and performance of the fingers in terms of deformation and tip force. Also, FEM was used to predict the contact behavior of the mechanical metamaterial to prove that it highly decreases the contact pressure by increasing the contact area between the soft fingers and the grasped objects and thus proving its effectiveness in enhancing the grasping performance of the gripper. The contact pressure can be decreased by up to 8.5 times with the implementation of the mechanical metamaterial. The configuration of the highly conformal gripper can be easily modulated by changing the number of fingers attached to its base to tailor it for specific manipulation tasks. Two-dimensional (2D) and 3D grasping experiments were conducted to assess the grasping performance of the soft modular gripper and to prove that the inclusion of the metamaterial increases its conformability and reduces the out-of-plane deformations of the soft monolithic fingers upon grasping different objects and consequently, resulting in the gripper in three different configurations including two, three and four-finger configurations successfully grasping a wide variety of objects.

Sensory feedback is critical in proprioception and balance to orchestrate muscles to perform targeted motion(s). Biofeedback plays a significant role in substituting such sensory data when sensory functions of an individual are reduced or lost such as neurological disorders including stroke causing loss of sensory and motor functions requires compensation of both motor and sensory functions. Biofeedback substitution can be in the form of several means: mechanical, electrical, chemical and/or combination. This study proposes a soft monolithic haptic biofeedback device prototyped and pilot tests were conducted with healthy participants that balance and proprioception of the wearer were improved with applied mechanical stimuli on the lower limb(s). The soft monolithic haptic biofeedback device has been developed and manufactured using fused deposition modelling (FDM) that employs soft and flexible materials with low elastic moduli. Experimental results of the pilot tests show that the soft haptic device can effectively improve the balance of the wearer as much as can provide substitute proprioceptive feedback which are critical elements in robotic rehabilitation.

Equipping prosthetic devices with sensory feedback capability is a continuing research challenge to increase their control and embodiment, and to decrease their rejection by their users. Electrotactile stimulation is one of the non-invasive sensory feedback techniques with a low power, light-weight and relatively easy to control stimulation mechanism to provide the feedback. Currently, there are two electrode setups used in the literature, concentric electrodes and separated electrodes, to apply the electrotactile stimulation to deliver tactile feedback. There is minimal data available in the literature to compare the two electrode setups. This study compares the impact of the electrode arrangements on the dynamic range, just noticeable difference (JND), comfort level, degree of localisation, intensity and type of sensation induced, and the resulting EMG interference from the electrotactile stimulation. The experimental results presented suggest that the concentric electrodes induce a more comfortable and realistic sensation with a reduction in the probability of inducing undesired feeling of pain, pinch or pinprick sensations. Further, the concentric electrodes result in an increased localisation of the induced sensation whilst maintaining a similar dynamic range and JND. EMG interference was shown to be lower for the concentric electrodes.

Passive vibration control using polymer composites has been extensively investigated by the engineering community. In this paper, a new kind of vibration dampening polymer composite was developed where oriented nylon 6 fibres were used as the reinforcement, and 3D printed unoriented nylon 6 was used as the matrix material. The shape of the reinforcing fibres was modified to a coiled structure which transformed the fibres into a smart thermoresponsive actuator. This novel self-reinforced composite was of high mechanical robustness and its efficacy was demonstrated as an active dampening system for oscillatory vibration of a heated vibrating system. The blocking force generated within the reinforcing coiled actuator was responsible for dissipating vibration energy and increase the magnitude of the damping factor compared to samples made of non-reinforced nylon 6. Further study shows that the appropriate annealing of coiled actuators provides an enhanced dampening capability to the composite structure. The extent of crystallinity of the reinforcing actuators is found to directly influence the vibration dampening capacity.

Compared to the traditional industrial robots that use rigid actuators, the advanced robotic systems are mobile and physically interact with unknown and dynamic environments. Therefore, they need intrinsically safe and compact actuators. In the last two decades, Series Elastic Actuators (SEAs) have been one of the most popular compliant actuators in advanced robotic applications due to their intrinsically safe and compact mechanical structures. The mobility and functionality of the advanced robotic systems are highly related to the torque-density of their actuators. For example, the amount of assistance an exoskeleton robot can provide is determined by the trade-off between the weight and output-torque, i.e., torque-density, of its actuators. As the torque outputs of the actuators are increased, the exoskeleton can expand its capacity yet it generally becomes heavier and bulkier. This has significant impact on the mobility of the advanced robotic systems. Therefore, it is essential to design light-weight actuators which can provide high-output torque. However, this still remains a big challenge in engineering. To this end, this paper proposes a high-torque density SEA for physical robot environment interaction (p-REI) applications. The continuous (peak) output-torque of the proposed compliant actuator is 147Nm (467 Nm) and its weight is less than 2.5kg. It is shown that the weight can be lessened to 1.74, but it comes at cost. The performance of the proposed compliant actuator is experimentally verified.

Soft robotic hands with monolithic structure have shown great potential to be used as prostheses due to their advantages to yield light weight and compact designs as well as its ease of manufacture. However, existing soft prosthetic hands design were often not geared towards addressing some of the practical requirements highlighted in prosthetics research. The gap between the existing designs and the practical requirements significantly hampers the potential to transfer these designs to real-world applications. This work addressed these requirements with the consideration of the trade-off between practicality and performance. These requirements were achieved through exploiting the monolithic 3D printing of soft materials which incorporates membrane enclosed flexure joints in the finger designs, synergy-based thumb motion and cable-driven actuation system in the proposed hand prosthesis. Our systematic design (tentatively named X-Limb) achieves a weight of 253gr, three grasps types (with capability of individual finger movement), power-grip force of 21.5N, finger flexion speed of 1.3sec, a minimum grasping cycles of 45,000 (while maintaining its original functionality) and a bill of material cost of 200 USD (excluding quick disconnect wrist but without factoring in the cost reduction through mass production). A standard Activities Measure for Upper-Limb Amputees benchmark test was carried out to evaluate the capability of X-Limb in performing grasping task required for activities of daily living. The results show that all the practical design requirements are satisfied, and the proposed soft prosthetic hand is able to perform all the real-world grasping tasks of the benchmark tests, showing great potential in improving life quality of individuals with upper limb loss.

Sensory feedback is a highly researched area for upper limb prosthetics, for which the stimulation is applied to either the upper arm or lower arm with minimal justification for the chosen site. In this study, we compare the recognition of three stimulation sites and their sensitivities to the stimulation applied to the upper and lower arm sites from a mechanotactile stimulation device. Our stimulation device is a crank-based mechanotactile feedback system, which applies a combination of a pressure applied in the normal direction and tangential direction to the skin at the stimulation sites on the lower arm and upper arm. The recognition rate for six grip patterns was found to be not statistically different between the upper and lower sites. Further, through Just Noticeable Difference (JND) measurements, there was no statistical difference between the sensitivities of the upper arm and lower arm at four stimulation sites. This study contributes to the literature from the point of view of identifying the upper arm as the alternative site of mechanotactile feedback for transradial prosthetic hand users in comparison to the lower arm, which is primarily used for EMG electrodes to identify the user's intention to control their robotic prosthetic hand.

In this work, a 3D printed modular soft gripper with highly conformal soft fingers was developed. A soft auxetic structure with compliant ribs is 3D printed simultaneously with each soft pneumatic finger for conformal grasping. The fingers of the soft gripper were printed monolithically, without requiring support material and postprocessing, using a low-cost and open-source fused deposition modeling (FDM) 3D printer that employs a commercially available thermoplastic polyurethane (TPU). The soft fingers of the gripper were optimized using finite element modeling (FEM). The FE simulations accurately predicted the performance of the fingers in terms of deformation and blocked force. Also, FEM was used to predict the behavior of the auxetic structure and its compliant ribs to prove that it highly decreases the contact pressure by increasing the contact area between the soft fingers and the grasped objects. The contact pressure can be decreased by up to 8 times with the implementation of the auxetic structure. Also, the configuration of the highly conformal gripper can be easily modulated by changing the number of fingers attached to its base to tailor it for specific manipulation tasks. A wide variety of objects with different weights, shapes, sizes, textures and stiffnesses can be grasped using the soft modular gripper.

Rehabilitation robotics is one of the major subfields in robotics that is growing rapidly. Neurological disorders, such as stroke, reduce the strength of muscles and the sensation of limbs of a stroke survivor. Soft haptics can be utilized to develop highly compliant soft biofeedback systems that comprise of soft sensors and actuators. Soft sensors are adaptable, conformal and safe for use in devices involving human-machine interaction. This study presents a soft 3D printed resistive force sensor that can be directly manufactured using a low-cost and open-source fused deposition modeling (FDM) 3D printer that uses a commercially available conductive thermoplastic poly(urethane) (TPU). Finite element modeling (FEM) is used to predict accurately the behavior of a single soft resistive sensor under applied mechanical loads. The electrical and mechanical characterization results of the sensor correlate the numerical results with reasonable accuracy. Under an applied mechanical deformation, there is a linear relationship between the output resistance of the sensor and the force generated. This soft force sensor can be tailored to biofeedback systems where it can be implemented and customized using 3D printing.

This paper deals with the robust force and position control problems of Series Elastic Actuators. It is shown that a Series Elastic Actuator's force control problem can be described by a second-order dynamic model which suffers from only matched disturbances. However, the position control dynamics of a Series Elastic Actuator is of fourth-order and includes matched and mismatched disturbances. In other words, a Series Elastic Actuator's position control is more complicated than its force control, particularly when disturbances are considered. A novel robust motion controller is proposed for Series Elastic Actuators by using Disturbance Observer and Sliding Mode Control. When the proposed robust motion controller is implemented, a Series Elastic Actuator can precisely track desired trajectories and safely contact with an unknown and dynamic environment. The proposed motion controller does not require precise dynamic models of the actuator and environment. Therefore, it can be applied to many different advanced robotic systems such as compliant humanoids and exoskeletons. The validity of the motion controller is experimentally verified.