It is estimated that in the European Union (EU) the proportion of the population aged over 65 years will rise from 17.1% in 2008 to 30% in 2060 and that the proportion of persons aged over 80 years will rise from 4.4% to 12.1% over the same period (EUROSTAT population projections). Neurological conditions, especially stroke, are a major cause of disability among older people. Incidence of a first stroke in Europe is about 1.1 million and prevalence about 6 million. Currently, about 75% of stroke sufferers survive 1 year after. This proportion will increase in the coming years due to steadily increasing quality in hyper-acute lifesaving practice, follow-up acute and sub-acute care, and lifelong management of these conditions. Despite these positive developments in stroke care, approximately 80% of stroke patients experience long-term reduced manual dexterity, a 72% of those affected by stroke suffer leg weakness, affecting walking, and half of all patients with neurological conditions are unable to perform everyday tasks. Rehabilitation and assistive robotics have the potential to change older people lives improving their recovery and/or supporting them to perform everyday tasks.
The purpose of this special collection is to provide an opportunity for researchers working in academy or industry to show their latest theoretical, technological, and experimental aspects of rehabilitation and assistive robotics. A total of eight articles have been accepted after a strict peer review process.
In the topic of rehabilitation robotics, Fraile et al. present an end-effector rehabilitation robot, a 2-degree-of-freedom planar robotic platform for upper limb rehabilitation in post-stroke patients. In addition, they describe the ergonomic mechanical design, the system control architecture, and the rehabilitation therapies that can be performed by the aforementioned rehabilitation robot. There are other two more papers included in this topic. In the first one, Diez et al. propose a novel multimodal robotic system for upper-limb neurorehabilitation therapies in physical environments, interacting with real objects. This system consists of an end-effector upper-limb rehabilitation robot, a hand exoskeleton, a gaze tracking system, an object tracking system, and electromyography measuring units. Their experimental results show that the proposed system is feasible and safe enough. Wrong detections in electromyography (EMG) are the main cause of failure; however, in the 97% of the trials, it still resulted in successful grasping and releasing. In the second one, Simonetti et al. present the design and development of a modular architecture for delivering upper limb robotic telerehabilitation with the CBM-Motus, a planar unilateral robotic machine. Their architecture allows a therapist to set a therapy session on his or her side and send it to the patient’s side with a standardized communication protocol; the user interacts with the robot that provides an adaptive assistance during the rehabilitation tasks. Moreover, the experimental results with seven healthy subjects show the reliability of the novel architecture and the capability to be easily tailored to the user’s needs with the chosen robotic device.
In the topic of robotic prosthetics, Barone et al. propose a multilevel control of an anthropomorphic robotic hand with prosthetic features. The novel approach is based on two distinct levels consisting of (1) a policy search learning algorithm combined with central pattern generators in the higher level and (2) a parallel force/position control managing slippage events in the lower level. Their experimental results demonstrate that the proposed control has the potential to adapt to changes in the environment and guarantees grasp stability, by avoiding object fall thanks to prompt slippage event detection. Moreover, Sekine et al. present the development of a shoulder prosthesis based on a hybrid actuation system composed of pneumatic elastic actuators (PEAs) and servo motors. Their results show that the joints with PEAs could absorb more impact force, which is very important for safe use, than with motors.
In this special collection, there are two papers in the field of wearable exoskeletons. In the first one, Ning et al. present the design and development of a power-assisted gait orthosis. The paper analysed the gait characteristics with crutches, designed the mechanical architecture, and optimized it using genetic algorithms. Moreover, the performance of the final design is verified under many external conditions, such as no-load, gait movement, long-term continuous movement, and load tests. In the second one, Zhang et al. propose a human–machine force interaction designing architecture for a load-carrying exoskeleton. Their experimental results show that the human–machine interaction force detection at the back and feet and the identification of different body modalities and movement intention are feasible. Moreover, the actual load on the human back is far less than the payload, which shows that their exoskeleton has good power-assisted effect.
The last paper included in this special collection is about a novel algorithm to estimate the instantaneous tremor parameters such as the time-varying dominant frequency in the case of nonsynchronous sampling and to distinguish the tremulous movement from the raw data. The experimental results reported by Wang et al. demonstrate that the proposed solution could detect the unknown dominant frequency and distinguish the tremor components with higher accuracy than the existing procedures.