Children with physical disabilities often have limited performance in daily activities, hindering their physical development, social development and mental health. Therefore, rehabilitation is essential to mitigate the adverse effects of the different causes of physical disabilities and improve independence and quality of life. In the last decade, robotic rehabilitation has shown the potential to augment traditional physical rehabilitation. However, to date, most robotic rehabilitation devices are designed for adult patients who differ in their needs compared to paediatric patients, limiting the devices’ potential because the paediatric patients’ needs are not adequately considered. With this in mind, the current work reviews the existing literature on robotic rehabilitation for children with physical disabilities, intending to summarise how the rehabilitation robots could fulfil children’s needs and inspire researchers to develop new devices. A literature search was conducted utilising the Web of Science, PubMed and Scopus databases. Based on the inclusion–exclusion criteria, 206 publications were included, and 58 robotic devices used by children with a physical disability were identified. Different design factors and the treated conditions using robotic technology were compared. Through the analyses, it was identified that weight, safety, operability and motivation were crucial factors to the successful design of devices for children. The majority of the current devices were used for lower limb rehabilitation. Neurological disorders, in particular cerebral palsy, were the most common conditions for which devices were designed. By far, the most common actuator was the electric motor. Usually, the devices present more than one training strategy being the assistive strategy the most used. The admittance/impedance method is the most popular to interface the robot with the children. Currently, there is a trend on developing exoskeletons, as they can assist children with daily life activities outside of the rehabilitation setting, propitiating a wider adoption of the technology. With this shift in focus, it appears likely that new technologies to actuate the system (e.g. serial elastic actuators) and to detect the intention (e.g. physiological signals) of children as they go about their daily activities will be required.

Wearables robots have gained attention for the rehabilitation of people with physical disabilities. However, the current technology relies on heavy and bulky actuation components, making it hard to use outside clinical settings. Artificial muscles based on smart materials are trending for soft wearable rehabilitation robots as they present advantages of compliance, are lightweight, and do not require external components. Nevertheless, they present challenges that remain unresolved, preventing widespread adoption. This work reviews the current state of soft wearable rehabilitation robots with artificial muscles based on smart materials (AMSMs). A literature search is conducted utilizing Web of Science and Scopus. Based on the inclusion–exclusion criteria, 15 devices are found using four different smart materials. This study attempts to provide an insight into the distinct biomechanical requirements, the use of smart materials, their limitations, their designs, and possible future research directions, which can provide helpful guidance on the implementation and development of advanced soft wearable rehabilitation robots with AMSMs.

Green sea turtles (Chelonia mydas) can swim up to 50 km per day while only consuming seagrass or microalgae. How the animal accomplishes this vast journey on such low energy intake points to the effectiveness of their swimming technique and is a testament to the power of evolution. Understanding the green sea turtle's ability to accomplish these journeys requires insight into their propulsive strategies. Conducting animal testing to uncover their propulsive strategies brings significant challenges: firstly, the ethical issues of conducting experiments on an endangered animal, and secondly, the animal may not even swim with its regular routine during the experiments. In this work, we develop a new soft-robotic sea turtle that reproduces the real animal's form and function to provide biomechanical insights without the need for invasive experimentation. We found that the green sea turtle may only produce propulsion for approximately 30% of the limb beat cycle, with the remaining 70% exploiting a power-preserving low-drag glide. Due to the animal's large mass and relatively low drag coefficient, losses in swim speed are minimal during the gliding stage. These findings may lead to the creation of a new generation of robotic systems for ocean exploration that use an optimised derivative of the sea turtle propulsive strategy.

Biomechanically, sea turtles could be perceived as birds of the ocean as they glide and flap their forelimbs to produce the necessary forces required for locomotion, making sea turtles an interesting animal to study. However, being an endangered species makes studying the sea turtle's biomechanics a complex problem to solve, both technically and ethically, without causing disturbance. This work develops a novel, non-invasive procedure to develop full three-dimensional kinematics for wild sea turtles by filming the animals in Australia's Great Barrier Reef using underwater drones without disturbing them. We found that the wild animals had very different swimming patterns than previous studies on juveniles in captivity. Our findings show that the flipper goes through a closed-loop trajectory with extended sweeping of the flipper tip towards the centre of the carapace to create a clapping motion. We have named this the “sweep stroke” and in contrast to previously described four-stage models, it creates a five-stage cycle swimming locomotion model. The model presented here could lead to a better comprehension of the sea turtle propulsion methods and their fluid–structure interaction.

Sea turtles gracefully navigate their marine environments by flapping their pectoral flippers in an elegant routine to produce the required hydrodynamic forces required for locomotion. The propulsion of sea turtles has been shown to occur for approximately 30% of the limb beat, with the remaining 70% employing a drag-reducing glide. However, it is unknown how the sea turtle manipulates the flow during the propulsive stage. Answering this research question is a complicated process, especially when conducting laboratory tests on endangered animals, and the animal may not even swim with its regular routine while in a captive state. In this work, we take advantage of our robotic sea turtle, internally known as Cornelia, to offer the first insights into the flow features during the sea turtle’s propulsion cycle consisting of the downstroke and the sweep stroke. Comparing the flow features to the animal’s swim speed, flipper angle of attack, power consumption, thrust and lift production, we hypothesise how each of the flow features influences the animal’s propulsive efforts and cost of transport (COT). Our findings show that the sea turtle can produce extremely low COT values that point to the effectiveness of the sea turtle propulsive technique. Based on our findings, we extract valuable data that can potentially lead to turtle-inspired elements for high-efficiency underwater drones for long-term underwater missions.

Bioimpedance measurements have gained significant attention due to their ability to assess body composition, muscle health, and internal physiological states without the need for intrusive procedures. This review paper explores the advancements and applications of bioimpedance technology, a non-invasive and cost-effective method for real-time monitoring of physiological parameters and physical activities. It discusses key measurement modalities such as bioelectrical impedance analysis (BIA), electrical impedance myography (EIM), and electrical impedance tomography (EIT), highlighting their unique advantages and applications. It also examines the role of biopotential electrodes, both polarizable and non-polarizable, in ensuring accurate physiological measurements. Despite challenges such as low spatial resolution, motion artifacts and sensitivity to electrode placement, the review highlights promising solutions. These include the integration of hybrid sensor systems, machine learning algorithms for signal interpretation, and the development of wearable and flexible electronics. The paper concludes by emphasizing the growing potential of bioimpedance technology in fields such as sports science, rehabilitation, personalized healthcare, fitness monitoring, and human-machine interaction, suggesting a future where continuous physiological monitoring becomes seamlessly embedded in daily life.