An early hypothesis in robot-assisted stroke therapy was that sensorimotor stimulation through robotic assistance is beneficial for recovery. Despite 25 years of upper-limb rehabilitation robotics research, this hypothesis remains untested barring a few studies with small sample sizes. This review aims to provide a critical summary of the current state of this hypothesis by collating evidence from rehabilitation robotics and other related therapeutic approaches. The review starts with a causal model to expose the various direct and indirect routes through which robotic assistance can aid sensorimotor recovery. The indirect routes include the influence of robotic assistance on therapy intensity, patient motivation, and active participation. The direct route is through changes in cortical networks through Hebbian(-like) learning and changes in peripheral tissue properties. There is currently mixed evidence for the direct causal effect of robotic assistance on recovery from the upper-limb rehabilitation robotics literature. However, evidence from the neuromuscular electrical stimulation literature provides some support for this causal role. Based on the data at hand, we hypothesize that the enhanced movement-related sensory feedback from robotic assistance has a direct, possibly small, causal role in the sensorimotor recovery of the upper-limb, and this effect might be detectable with high-intensity therapy. Large, high-intensity, controlled studies are warranted to support or refute the role of robotic assistance on recovery, which is both scientifically and practically important.

Traditional end-effector robots for arm rehabilitation are usually attached a­t the hand, primarily focusing on coordinated multi-joint training. Therapy at an individual joint level of the arm for severely impaired stroke survivors is not always possible with existing end-effector robots. The Arm Rehabilitation Robot (AREBO)—an end-effector robot—was designed to provide both single and multi-joint assisted training while retaining the advantages of traditional end-effector robots, such as ease of use and cost-effectiveness (compared to exoskeletons). This work presents the design, optimization, and characterization of AREBO for training single-joint movements of the arm. The AREBO has three actuated and three unactuated degrees of freedom, allowing it to apply forces in any arbitrary direction at its endpoint and self-align to arbitrary orientations within its workspace. The AREBO’s link lengths were optimized to maximize its workspace and manipulability. The AREBO provides single-joint training in both unassisted and adaptive weight support modes using a human arm model to estimate the human arm's kinematics and dynamics without using additional sensors. The characterization of the robot’s controller and the algorithm for estimating the human arm parameters were performed using a two degrees of freedom mechatronic model of the human shoulder joint. The results demonstrate that: (a) the movements of the human arm can be estimated using a model of the human arm and robot’s kinematics, (b) the AREBO has similar transparency to that of existing arm therapy robots in the literature, and (c) the adaptive weight support mode control can adapt to different levels of impairment in the arm. This work demonstrates how an appropriately designed end-effector robot can be used for single-joint training, which can be easily extended to multi-joint training. Future work will focus on the evaluation of the system on patients with any neurological condition requiring arm training.

Robot-assisted rehabilitation has emerged as a promising approach for enhancing motor function in stroke survivors. However, the feasibility and effectiveness of home-based robotic training in this population are underexplored, especially in low/middle-income countries. This feasibility study aimed to address this gap by examining the feasibility and effectiveness of independent home-based training using PLUTO, a robotic device for hand training. A total of 7 chronic stroke survivors were recruited, with 5 completing the study. The results revealed high engagement and adherence to the home-based training program, with participants averaging 1659.8 minutes of training over 24.8 days. The PLUTO system demonstrated excellent usability and elicited positive user perceptions. Significant improvements were observed in functional outcomes, as evidenced by a noteworthy increase in Fugl-Meyer Assessment scores (mean increase of 6.2 points, exceeding the minimal clinically important difference (MCID) of 5.35 points). Furthermore, participants showed improvements in the ABILHAND measure (mean improvement of 1.24 logits, surpassing the MCID of 0.2 logits) and the Barthel Index (mean increase of 8.8 points). These findings demonstrate the feasibility and effectiveness of home-based robotic rehabilitation for chronic stroke survivors. This has implications for expanding access to rehabilitation services in low- and middle-income countries, enhancing patient engagement and adherence, and improving functional outcomes. Larger controlled studies are warranted to evaluate the effectiveness of home-based robotic rehabilitation programs.