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Conventional rehabilitation strategies for stroke survivors become difficult when voluntary movements are severely disturbed. Combining passive limb mobilization, robotic devices and EEG-based brain-computer interfaces (BCI) systems might improve treatment and clinical follow-up of these patients, but detailed knowledge of neurophysiological mechanisms involved in functional recovery, which might help for tailoring stroke treatment strategies, is lacking. Movement-related EEG changes (EEG event-related desynchronization (ERD) in $beta$ and $alpha$ bands, an indicator of motor cortex activation traditionally used for BCI systems), were evaluated in a group of 23 paralyzed chronic stroke patients in two unilateral motor tasks alternating paretic and healthy hands ((i) passive movement, using a hand exoskeleton, and (ii) voluntary movement), and compared to nine healthy subjects. In tasks using unaffected hand, we observed an increase of contralesional hemisphere activation for stroke patients group. Unexpectedly, when using paralyzed hand, motor cortex activation was reduced or absent in severely affected group of patients, while patients with moderate motor deficit showed an activation greater than control group. Cortical activation was reduced or absent in damaged hemisphere of all the patients in both tasks. Significant differences related to severity of motor deficit were found in the time course of $alpha$-$beta$ bands power ratio in EEG of contralesional hemisphere while moving affected hand. These findings suggest the presence of different compensation mechanisms in contralesional hemisphere of stroke patients related to the grade of motor disability, that might turn quantitative EEG during a movement task, obtained from a BCI system controlling a robotic device included in a rehabilitation task, into a valuable tool for monitoring clinical progression, evaluating recovery, and tailoring treatment of stroke patients.

Nerve injury can cause lower limb paralysis and gait disorder. Currently lower limb rehabilitation exoskeleton robots used in the hospitals need more power to correct abnormal motor patterns of stroke patients’ legs. These gait rehabilitation robots are powered by cumbersome and bulky electric motors, which provides a poor user experience. A newly developed gait rehabilitation exoskeleton robot actuated by low-cost and lightweight pneumatic artificial muscles (PAMs) is presented in this research. A model-free proxy-based sliding mode control (PSMC) strategy and a model-based chattering mitigation robust variable control (CRVC) strategy were developed and first applied in rehabilitation trainings, respectively. As the dynamic response of PAM due to the compressed air is low, an innovative intention identification control strategy was taken in active trainings by the use of the subject’s intention indirectly through the estimation of the interaction force between the subject’s leg and the exoskeleton. The proposed intention identification strategy was verified by treadmill-based gait training experiments.

A quasi-passive leg exoskeleton is presented for load-carrying augmentation during walking. The exoskeleton has no actuators, only ankle and hip springs and a knee variable-damper. Without a payload, the exoskeleton weighs 11.7 kg and requires only 2 Watts of electrical power during loaded walking. For a 36 kg payload, we demonstrate that the quasi-passive exoskeleton transfers on average 80% of the load to the ground during the single support phase of walking. By measuring the rate of oxygen consumption on a study participant walking at a self-selected speed, we find that the exoskeleton slightly increases the walking metabolic cost of transport (COT) as compared to a standard loaded backpack (10% increase). However, a similar exoskeleton without joint springs or damping control (zero-impedance exoskeleton) is found to increase COT by 23% compared to the loaded backpack, highlighting the benefits of passive and quasi-passive joint mechanisms in the design of efficient, low-mass leg exoskeletons.

An exoskeleton is a wearable robot with joints and links corresponding to those of the human body. With applications in rehabilitation medicine, virtual reality simulation, and teleoperation, exoskeletons offer benefits for both disabled and healthy populations. Analytical and experimental approaches were used to develop, integrate, and study a powered exoskeleton for the upper limb and its application as an assistive device. The kinematic and dynamic dataset of the upper limb during daily living activities was one among several factors guiding the development of an anthropomorphic, seven degree-of-freedom, powered arm exoskeleton. Additional design inputs include anatomical and physiological considerations, workspace analyses, and upper limb joint ranges of motion. Proximal placement of motors and distal placement of cable-pulley reductions were incorporated into the design, leading to low inertia, high-stiffness links, and back-drivable transmissions with zero backlash. The design enables full glenohumeral, elbow, and wrist joint functionality. Establishing the human-machine interface at the neural level was facilitated by the development of a Hill-based muscle model (myoprocessor) that enables intuitive interaction between the operator and the wearable robot. Potential applications of the exoskeleton as a wearable robot include (i) an assistive (orthotic) device for human power amplifications, (ii) a therapeutic and diagnostics device for physiotherapy, (iii) a haptic device in virtual reality simulation, and (iv) a master device for teleoperation.

The basic concepts for exoskeletal systems have been suggested for some time with applications ranging from construction, manufacturing and mining to rescue and emergency services. In recent years, research has been driven by possible uses in medical/rehabilitation and military applications. Yet there are still significant barriers to the effective use and exploitation of this technology. Among the most pertinent of these factors is the power and actuation system and its impact of control, strength, speed and, perhaps most critically, safety. This work describes the design, construction and testing of an ultra low-mass, full-body exoskeleton system having seven degrees of freedom (DOFs) for the upper limbs and five degrees of freedom (DOFs) for each of the lower limbs. This low mass is primarily due to the use of a new range of pneumatic muscle actuators as the power source for the system. The work presented will show how the system takes advantage of the inherent controllable compliance to produce a unit that is powerful, providing a wide range of functionality (motion and forces over an extended range) in a manner that has high safety integrity for the user. The general layout of both the upper and the lower body exoskeleton is presented together with results from preliminary experiments to demonstrate the potential of the device in limb retraining, rehabilitation and power assist (augmentation) operations.

Human–robot integration, in particular human augmentation, outlines the future of robotics. Although autonomous robotic systems perform remarkably in structured environments (e.g. factories), integrated human–robotic systems are superior to any autonomous robotic systems in unstructured environments that demand significant adaptation. In our research work at Berkeley, we have separated the technology associated with human power augmentation into lower extremity exoskeletons and upper extremity exoskeletons. The reason for this was two-fold: firstly, we could envision a great many applications for either a stand-alone lower or upper extremity exoskeleton in the immediate future. Secondly, and more importantly for the division is that the exoskeletons are in their early stages, and further research still needs to be conducted to ensure that the upper extremity exoskeleton and lower extremity exoskeleton can function well independently before we can venture an attempt to integrate them. With this in mind, we proceeded with the designs of the lower and upper extremity exoskeleton separately, with little concern for the development of an integrated exoskeleton. This article first gives a description of the upper extremity exoskeleton efforts and then will proceed with the more detailed description of the lower extremity exoskeleton.

Self-Balanced lower limb exoskeleton (SBLLE) is designed for rehabilitation and walking assistance for dyskinesia persons with spinal or lower limb muscle injury to regain the locomotion ability in daily activities. In this paper, an innovative feedback control strategy for a fully actuated SBLLE is presented, which helps users to walk stably without crutches or other assistive devices. Exoskeleton is approximated as a simplified center of mass (CoM) model. Based on this simplified dynamic model, the trajectory generation and walking feedback control strategy, which enhances the locomotion stability, is introduced. The proposed strategy is implemented on our exoskeleton, AutoLEE-II, and its stability and dynamic performance are demonstrated in the stable walking simulations and experiments for exoskeleton with a female subject.

Gait recognition is one of the key technologies for exoskeleton robot control. The recognition accuracy and robustness of existing gait recognition methods cannot well meet the needs of real-time control. There is still room for improvement in fine-grained gait recognition. In this regard, this paper proposes a gait recognition method based on the MiniRocket and inertial measurement units. In this paper, a human lower limb posture information collection device is developed to collect ten kinds of gait data of human lower limbs (walking, standing, running, backing off, going upstairs, going downstairs, going uphill, going downhill, stand at ease and squat). The MiniRocket algorithm was used to build a human gait recognition model, and the effects of algorithm parameters and the size of the window and shift on the performance of gait recognition were discussed, and user-independent experiments and user-dependent experiments were carried out, respectively, and compared with four algorithms of TST, TCN, RNN and LSTM. The experimental results show that the MiniRocket algorithm has an average recognition accuracy of 94.87% and 97.67% in the user-independent experiment and the user-dependent experiment, which is better than the other four algorithms. And the effectiveness of the method in the IMUs-based human gait recognition problem is shown, which provides some implications for fine-grained gait recognition.

This study developed an underactuated lower extremity exoskeleton system to carry a heavy load. To synchronize that system with a user, a feasible modular-type wearable system and its corresponding sensor systems are proposed. To operate the system with a user, human walking analysis and intention signal acquisition methods for actuating the proposed system are developed. In particular, a sensing data estimation strategy is applied to correctly synchronize the exoskeleton system with a user. Finally, several experiments were performed to evaluate the performance of the proposed exoskeleton system by measuring the electromyography signal of the wearers muscles.

This paper presents a 3 DOF (Degrees Of Freedom) planar hopping machine running in a simulation software environment. The purpose is to use this approach to study the control, simulation and design of legged robots and exoskeletons. The control system allows the machine hopping in place after fall with his leg a little inclined, then hopping forward, then hopping backward and then stop hopping in place. Hopping machines are the most simplified dynamic model capable of representing the elastic behaviour of the legs of mammals and insects in running and hopping. The results of the simulation presented shown that pelvic tilt observed in human running is also observed in the hopping machine running model. This encourages the modelling of anthropomorphic legs for use in human running simulations with hopping machine models and control strategies.

Research on lower-limb exoskeletons and active orthoses is a growing field in service robotics. Nowadays commercial active orthoses present stiff joints but for the intrinsic human-machine interaction task, these actuators need to exhibit compliance. Moreover, they must be powerful enough to move the user limbs while keeping small size for not to bother the user motion and show an aesthetic appearance. In this paper we present the development and main characteristics of a joint prototype with variable stiffness that achieve these requirements. This actuated joint has been implemented in the knee of ATLAS active orthosis. A state machine control scheme takes advantage of the leg dynamics and of the actuator features, achieving a natural, compliant gait without the need of commanding a CGA based pattern. A reduction in the energy expenditure while keeping compliant to accommodate unexpected disturbances is obtained.

Low volume industrial productions are rarely highly automated because of the related costs. Variable production requires flexible automation with close human robot interaction. An exoskeleton may exactly provide these features to enhance industrial production. This article highlights the difficulties related to using exoskeletons in an industrial setting. Moreover, it introduces the Robo-Mate project – an EU funded project – targeted to address the application of an exoskeleton in industry.

This paper presents investigations for development of an assistive exoskeleton device for elderly mobility. This exoskeleton is designed to enhance the lower limb and provide support torque in order to augment the torque of knee and hip during the walking cycle. PID Control is designed and implemented in this work. Due to the complexity in identifying the lower limb musculoskeletal system with traditional mathematical approaches, the visual Nastran 4D software is used for development of simulation model of the exoskeleton and a humanoid. Simulation results demonstrating the performance of the adopted approach are presented and discussed.

This work presented in this paper focuses on development of assistive robotic control approach for the upper extremities. A set-point tracking position control structure with proportional, integral and derivative (PID) controller is considered. A spiral dynamic optimization algorithm is utilized for tuning of the PID gains. The control strategy is tested and evaluated within simulation model of upper extremities. The results show that good position tracking performance is achieved with the developed control approach.