Quantitative and Qualitative Evaluation of Exoskeleton Transparency Controllers for Upper-Limb Neurorehabilitation.

High transparency is a fundamental requirement for upper-limb exoskeletons to promote active patient participation. Although various control strategies have been suggested to improve the transparency of these robots, there are still some limitations, such as the need for precise dynamic models and potential safety issues when external forces are applied to the robot. This study presents a novel hybrid controller designed to tackle these limitations by combining a traditional zero-torque controller with an interaction torque observer that compensates for residual undesired disturbances. The transparency of the proposed controller was evaluated using both quantitative-e.g., residual joint torques and movement smoothness-and qualitative measures-e.g., comfort, agency, and perceived resistance-in a pilot study with six healthy participants. The performance of the new controller was compared to that of two conventional controllers: a zero-torque closed-loop controller and a velocity-based disturbance observer. Our preliminary results show that the proposed hybrid controller may be a good alternative to state-of-the-art controllers as it allows participants to perform precise and smooth movements with low interaction joint torques. Importantly, participants rated the new controller higher in comfort and agency, and lower in perceived resistance. This study highlights the importance of incorporating both quantitative and qualitative assessments in evaluating control strategies developed to enhance the transparency of rehabilitation robots.

Development and Validation of a Kinematically Accurate Upper-Limb Exoskeleton Digital Twin for Stroke Rehabilitation.

Rehabilitation robotics combined with virtual reality using head-mounted displays enable naturalistic, immersive, and motivating therapy for people after stroke. There is growing interest in employing digital twins in robotic neurore-habilitation, e.g., in telerehabilitation for virtual coaching and monitoring, as well as in immersive virtual reality applications. However, the kinematic matching of the robot's visualization with the real robot movements is hardly validated, potentially affecting the users' experience while immersed in the virtual environment due to a visual-proprioceptive mismatch. The kinematic mismatch may also limit the validity of assessment measures recorded with the digital twin. We present the development and low-cost kinematic validation of a digital twin of a seven active degrees-of-freedom exoskeleton for stroke rehabilitation. We validated the kinematic accuracy of the digital twin end-effector by performing two tasks-a planar reaching task and a 3D functional task-performed by a single healthy participant. We computed the end-effector position and rotation from the forward kinematics of the robot, the digital twin, and data recorded from the real robot using a low-cost tracking system based on HTC VIVE trackers and compared them pair-wise. We found that the digital twin closely matches the forward kinematics and tracked movement of the real robot and thus provides a reliable platform for future research on digital twins for stroke rehabilitation.

AGREE: an upper-limb robotic platform for personalized rehabilitation, concept and clinical study design.

Rehabilitation exoskeletons can supplement therapist-based training allowing post-stroke patients to perform functional, high-dosage, repetitive exercises. The use of robotic devices allows providing intense rehabilitation sessions and permits clinicians to personalize the therapy according to the patient's need. In this work, we propose an upper-limb rehabilitation system developed within the AGREE project. The platform relies on a four degrees-of-freedom arm exoskeleton, capable of assisting state-of-the-art rehabilitation exercises under different training modalities while behaving transparently to user-generated and therapist-applied forces. The system is provided with a LEDs-matrix mat to guide patients during reaching tasks with visual feedback, an EMG reader to evaluate the patient's involvement during the therapy, and several software tools to help clinicians customize the treatment and monitor the patient's progress. A randomized controlled pilot study aimed at evaluating the usability and the effectiveness of the AGREE rehabilitation platform to improve arm impairment after stroke is currently ongoing.

Comparing Fatigue Reducing Stimulation Strategies During Cycling Induced by Functional Electrical Stimulation: a Case Study with one Spinal Cord Injured Subject.

This case study was designed starting from our experience at CYBATHLON 2020. The specific aim of this work was to compare the effectiveness of different fatigue reducing stimulation strategies during cycling induced by Functional Electrical Stimulation (FES). The compared stimulation strategies were: traditional constant frequency trains (CFTs) at 30 and 40Hz, doublet frequency trains (DFTs) and spatially distributed sequential stimulation (SDSS) on the quadriceps muscles. One Spinal Cord Injured (SCI) subject (39 years, T5-T6, male, ASIA A) was involved in 12 experimental sessions during which the four strategies were tested in a randomized order during FES-induced cycling performed on a passive trike at a constant cadence of 35 RPM. FES was delivered to four muscle groups (quadriceps, gluteal muscles, hamstrings and gastrocnemius) for each leg. The performance was evaluated in terms of saturation time (i.e., the time elapsed from the beginning of the stimulation until the predetermined maximum value of current amplitude is reached) and root mean square error (RMSE) of the actual cadence with respect to the target value. SDSS achieved a statistical lower saturation time and a qualitative higher RMSE of the cadence with respect to CFTs both at 30 and 40Hz.Clinical relevance- Conversely to previous literature, SDSS seems to be ineffective to reduce muscle fatigue during FES-induced cycling. Further experiments are needed to confirm this result.