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Facing above-knee amputation poses a significant hurdle due to its profound impact on walking ability. To overcome this challenge, a complex adaptation strategy is necessary at the neuromuscular level to facilitate safe movement with a prosthesis. Prior research conducted on lower-limb amputees has shown a comparable amount of intricacy exhibited by the neurological system, regardless of the level of amputation and state of walking. This research investigated the differences in muscle synergies among individuals with unilateral transfemoral amputations during walking at three different speeds of transient-state gait. Surface electromyography was recorded from eleven male transfemoral amputees' intact limbs (TFA), and the concatenated non-negative matrix factorization technique was used to identify muscle synergy components, synergy vectors (S), and activation coefficient profiles (C). Results showed varying levels of correlation across paired-speed comparisons in TFA, categorized as poor (S1), moderate (S3 and S4), and strong (S2). Statistically significant differences were observed in all activation coefficients except C3, particularly during the stance phase. This study can assist therapists in understanding muscle coordination in TFA during unsteady gait, contributing to rehabilitation programs for balance and mobility improvement, and designing myoelectric prosthetic systems to enhance their responsiveness to trips or falls. [ABSTRACT FROM AUTHOR]

BACKGROUND: The aim of a robotic exoskeleton is to match the torque and angular profile of a healthy human subject in performing activities of daily living. Power and mass are the main requirements considered in the robotic exoskeletons that need to be reduced so that portable designs to perform independent activities by the elderly users could be adopted. OBJECTIVE: This paper evaluates a systematic approach for the design optimization strategies of elastic elements and implements an actuator design solution for an ideal combination of components of an elastic actuation system while providing the same level of support to the elderly. METHODS: A multi-factor optimization technique was used to determine the optimum stiffness and engagement angle of the spring within its elastic limits at the hip, knee and ankle joints. An actuator design framework was developed for the elderly users to match the torque-angle characteristics of the healthy human with the best motor and transmission system combined with series or parallel elasticity in an elastic actuator. RESULTS: With the optimized spring stiffness, a parallel elastic element significantly reduced the torque and power requirements up to 90% for some manoeuvres for the users to perform ADL. When compared with the rigid actuation system, the optimized robotic exoskeleton actuation system reduced the power consumption of up to 52% using elastic elements. CONCLUSION: A lightweight, smaller design of an elastic actuation system consuming less power as compared to a rigid system was realized using this approach. This will help to reduce the battery size and hence the portability of the system could be better adopted to support elderly users in performing daily living activities. It was established that parallel elastic actuators (PEA) can reduce the torque and power better than series elastic actuators (SEA) in performing everyday tasks for the elderly. [ABSTRACT FROM AUTHOR]

People with mobility impairments have reported that improving their walking is one of the most important goals of their rehabilitation. Novel robotic technologies using powered exoskeletons for the lower limb could potentially offer efficient and less labour-intensive approaches to rehabilitation with shorter recovery times. To gather users' and carers' perspectives of assistive device use to provide information to design personalised and safe mobility rehabilitation technology. Semi-structured interviews were carried out with people with experience of mobility impairments. Iterative data collection was used to gather information about the social phenomena surrounding patient interaction and requirements for assistive devices for mobility impairments. Cycles of continuous data collection and thematic analysis using a theoretical, semantic approach was used to develop key themes within the data. We interviewed eight people: six people with mobility impairments and two carers. We identified five main themes: relationship with assistive technology, requirements for assistive technology, function and goal setting, personal factors to assistive device use and psychosocial factors to assistive device use. There was variability in the importance placed on each theme, particularly in the trade-off between the function and comfort of assistive technology. Patients emphasised the need for assistive technology to be personalised; they reported the ability to stand, control spasticity and involvement in community roles as key goals of their rehabilitation. These results highlight the variation in requirements for assistive technology between people with different mobility impairments; individuals' experiences are unique and future prototypes need to account for different levels of impairments and personal goals. These findings will also inform the user evaluation stage of assistive device testing. The acceptability of assistive devices is dependent upon a number of factors, including personalisation, comfort and function. Future pilot studies should gather qualitative data to determine the acceptability of actual device use. [ABSTRACT FROM AUTHOR]

This paper studies the viability of using a class of phase-changing materials for the design of controlled variable stiffness robotic joints which enable the design of robots that can operate in confined spaces. In such environments, robots need to be able to navigate in proximity or while in contact with their environment to reach one or more manipulated target. Joints with controllable stiffness can substantially enhance functionality of this class of robots where relatively higher joint stiffness is required to support the robot weight against gravity and low stiffness is desired when operating in complex or delicate environments. The research work presented in this paper focuses on examining thermorheological fluids (TRF) to design and manufacture thermally controlled variable stiffness joints. Two phase-changing materials are considered in the study: low-melting-point solder and hot-melt adhesive. Both materials are embedded in a custom designed joint fabricated using 3D printing and silicone casting. Joint stiffness was investigated with both materials and reported here. The results shows that the proposed variable stiffness joints with TRF achieve wide ranges of load-deflection ratio varying between 0.05 N/mm (when thermally activated) to about 10 N/mm (in bonding state). On average, the joint can withstand 20 times its total weight when in the bonding state. Design challenges and durability of TRF-based joints are discussed. [ABSTRACT FROM AUTHOR]

EMG-based continuous wrist joint motion estimation has been identified as a promising technique with huge potential in assistive robots. Conventional data-driven model-free methods tend to establish the relationship between the EMG signal and wrist motion using machine learning or deep learning techniques, but cannot interpret the functional relationship between neuro-commands and relevant joint motion. In this paper, an EMG-driven musculoskeletal model is proposed to estimate continuous wrist joint motion. This model interprets the muscle activation levels from EMG signals. A muscle-tendon model is developed to compute the muscle force during the voluntary flexion/extension movement, and a joint kinematic model is established to estimate the continuous wrist motion. To optimize the subject-specific physiological parameters, a genetic algorithm is designed to minimize the differences of joint motion prediction from the musculoskeletal model and joint motion measurement using motion data during training. Results show that mean root-mean-square-errors are 10.08°, 10.33°, 13.22° and 17.59° for single flexion/extension, continuous cycle and random motion trials, respectively. The mean coefficient of determination is over 0.9 for all the motion trials. The proposed EMG-driven model provides an accurate tracking performance based on user’s intention. [ABSTRACT FROM AUTHOR]

Purpose: Ambulation is an important objective for people with pathological gaits. Exoskeleton robots can assist these people to complete their activities of daily living. There are exoskeletons that have been presented in literature to assist the elderly and other pathological gait users. This article presents a review of the degree of support required in the elderly and neurological gait disorders found in the human population. This will help to advance the design of robot-assisted devices based on the needs of the end users. Methods: The articles included in this review are collected from different databases including Science Direct, Springer Link, Web of Science, Medline and PubMed and with the purpose to investigate the gait parameters of elderly and neurological patients. Studies were included after considering the full texts and only those which focus on spatiotemporal, kinematic and kinetic gait parameters were selected as they are most relevant to the scope of this review. A systematic review and meta-analysis were conducted. Results: The meta-analysis report on the spatiotemporal, kinematic and kinetic gait parameters of elderly and neurological patients revealed a significant difference based on the type and level of impairment. Healthy elderly population showed deviations in the gait parameters due to age, however, significant difference is observed in the gait parameters of the neurological patients. Conclusion: A level of agreement was observed in most of the studies however the review also noticed some controversies among different studies in the same group. The review on the spatiotemporal, kinematics and kinetic gait parameters will provide a summary of the fundamental needs of the users for the future design and development of robotic assistive devices. The support requirements provide the foundation for designing assistive devices. The findings will be crucial in defining the design criteria for robot assistive devices. [ABSTRACT FROM AUTHOR]

To maximise the efficiency of gait interventions, gait phase and joint kinematics are important for closing the system loop of adaptive robotic control. However, few studies have applied an inertial sensor system including both gait phase detection and joint kinematic measurement. Many algorithms for joint measurement require careful alignment of the inertial measurement unit (IMU) to the body segment. In this paper, we propose a practical gait feedback method, which provides sufficient feedback without requiring precise alignment of the IMUs. The method incorporates a two-layer model to realise simultaneous gait stance and swing phase detection and ankle joint angle measurement. Recognition of gait phases is performed by a high-level probabilistic method using angular rate from the sensor attached to the shank while the ankle angle is calculated using a data fusion algorithm based on the complementary filter and sensor-to-segment calibration. The online performance of the algorithm was experimentally validated when 10 able-bodied participants walked on the treadmill with three different speeds. The outputs were compared to the ones measured by an optical motion analysis system. The results showed that the IMU-based algorithm achieved a good accuracy of the gait phase recognition (above 95%) with a short delay response below 20 ms and accurate angle measurements with root mean square errors below 3.5° compared to the optical reference. It demonstrates that our method can be used to provide gait feedback for the correction of drop foot. [ABSTRACT FROM AUTHOR]

Recognition of movement is a crucial process to assist humans in activities of daily living, such as walking. In this work, a high-level method for the simultaneous recognition of locomotion and gait phases using wearable sensors is presented. A Bayesian formulation is employed to iteratively accumulate evidence to reduce uncertainty, and to improve the recognition accuracy. This process uses a sequential analysis method to autonomously make decisions, whenever the recognition system perceives that there is enough evidence accumulated. We use data from three wearable sensors, attached to the thigh, shank, and foot of healthy humans. Level-ground walking, ramp ascent and descent activities are used for data collection and recognition. In addition, an approach for segmentation of the gait cycle for recognition of stance and swing phases is presented. Validation results show that the simultaneous Bayesian recognition method is capable to recognize walking activities and gait phases with mean accuracies of 99.87% and 99.20%. This process requires a mean of 25 and 13 sensor samples to make a decision for locomotion mode and gait phases, respectively. The recognition process is analyzed using different levels of confidence to show that our method is highly accurate, fast, and adaptable to specific requirements of accuracy and speed. Overall, the simultaneous Bayesian recognition method demonstrates its benefits for recognition using wearable sensors, which can be employed to provide reliable assistance to humans in their walking activities. [ABSTRACT FROM PUBLISHER]

Tethered mobile robots are ideal for electrically noisy environments and for time-consuming tasks that require robust data communication and uninterrupted power delivery. However, tethers may become entangled in cluttered environments, leading to immobilisation and consequent mission failure. This work addresses real-time monitoring of tethers to detect tether entanglement, perform disentanglement through tether following and localise within line of sight. Experimental hardware is proposed to implement the tether monitoring techniques. Experiments are performed for single and dual mobile robots to search a target environment and entanglement detection is shown to be successful using quantitative metrics such as mean localization error. [ABSTRACT FROM PUBLISHER]

In this paper, an experimental set-up for the measurement of actuation properties of shape memory alloy wire actuators is presented. A test rig is designed and developed to characterise shape memory alloy wire actuators. The test rig is equipped with force, displacement and temperature sensors. The test rig is validated by measuring the strain of bi-atomic nickel–titanium shape memory alloy actuators by supplying various actuation currents. At 420 mA, the 0.15-mm-diameter nickel–titanium actuators underwent 3.25% strain which lies within the guideline range (3%-4%) reported by the manufacturer of the actuators. [ABSTRACT FROM AUTHOR]

This article presents a virtual prototyping study of a semi-active lower limb prosthesis to improve the functionality of an amputee during prosthesis–environment interaction for level ground walking. Articulated ankle–foot prosthesis and a single-axis semi-active prosthetic knee with active and passive operating modes were considered. Data for level ground walking were collected using a photogrammetric method in order to develop a base-line simulation model and with the hip kinematics input to verify the proposed design. The simulated results show that the semi-active lower limb prosthesis is able to move efficiently in passive mode, and the activation time of the knee actuator can be reduced by approximately 50%. Therefore, this semi-active system has the potential to reduce the energy consumption of the actuators required during level ground walking and requires less compensation from the amputee due to lower deviation of the vertical excursion of body centre of mass. [ABSTRACT FROM AUTHOR]

Although significant progress has been made in the development of robots with serpentine properties, the issues of motion control and adaptation to environmental constraints still require substantial research. This is particularly true for search and rescue applications, where reliable operation in extremely difficult terrain is essential. This paper presents a novel robot design based on the mechanics and neural control of locomotion in Caenorhabditis elegans, a tiny nematode worm. Equipped with an extremely simple yet powerful neurally-inspired decentralized control system, the robot presented here is capable of effective serpentine locomotion. More importantly, it exhibits sensorless path finding, in which obstacles in the environment are overcome, based purely on proprioceptive feedback encoding body shape. Indeed, the robot lacks any form of external sensory capability. The design and implementation of the prototype robot and its control strategy are discussed. In order to validate the control strategy for path finding, experiments and analyses have been performed. The results show that the robot can find its path successfully in the majority of cases. The current limitations have also been discussed. [ABSTRACT FROM PUBLISHER]

By blending electrically conducting carbon black particles and silica into poly(bisphenol A-co-epichlorohydrin) epoxy resin polymer, conductive nanocomposites were prepared by printing onto transparency films and curing. Application of a milling procedure prior to application is beneficial for the reduction of cracks in the subsequent nanocomposites. Electrical conduction of nanocomposite is CB content dependent. A percolation region (19-24% CB on mass of resin) exists where the nanocomposite exhibits a transition from an electrical insulator to conductor. Nanocomposites with 14% and 19% CB on mass of resin demonstrated greatest sensitivity to changes in bending angle, attributed to greater localized changes in the conductive paths within a semi-conducting sensor. Good reproducibility was observed as a result of molecular interactions between CB particles and the epoxy resin. [ABSTRACT FROM AUTHOR]

This work presents an insight into the conductivity-carbon black (CB) concentration relationship of nanocomposites. High conductivity is observed above 14% CB loading (% on mass of epoxy resin), indicating the generation of conductive networks throughout the nanocomposites. Observation of the relationship between the natural logarithm of conductivity values versus CB loading shows a remarkable increase in conductivity when the CB loading increases from 19 to 24%. In this region (percolation) a relatively small increase in CB loading produces a large increase in conductivity. When the quantity of CB is low (<14%), the resistivity of the nanocomposite is only slightly different from that of the base polymer; further increase in CB loading beyond the critical concentration region (>24%) causes marginal change in conductivity. The uniformity of the nanocomposites is evidenced by both microstructure (Si-mapping) and macro-property (resistance versus distance relationship) analyses. [ABSTRACT FROM AUTHOR]

Composite material has attracted increasingly remarked interest over the last few decades and set it apart in its own class due to its distinct properties. World annual production is over 10 million tonnes and the market has in recent years been growing at 5–10% per annum. Among these materials, one subgroup, conductive polymer composite, has figured out and its importance is increasing in years to come. When used as conductive material, it possesses the merits of light weight, ease of manufacturing and chemical resistance. This review focuses on the electrical properties of carbon based conductive polymer composites. Special emphases are placed on the percolation phenomenon, the factors that affect the percolation threshold as well as related theoretical research work. Then mechanisms of electric conduction and factors influencing conductive properties are addressed. [ABSTRACT FROM AUTHOR]