To offer engaging neurorehabilitation training to stroke patients, robotic exoskeletons have emerged as a beneficial tool to train motor tasks. However, in robotic therapy, the therapists are often limited in how they can interact with the patients. The training programs with exoskeletons are often standardized, not allowing the therapist to directly manipulate them and customize the training for specific patient needs. This paper presents a novel telerehabilitation system incorporating a therapist-in-the-loop haptic interface and immersive virtual reality (IVR), aimed at improving the interaction dynamics between patients and therapists during rehabilitation sessions. We conducted a human factors study involving 36 participants grouped in pairs, assigned as "Leaders" or "Followers," where the Leader had to guide the Follower (positioned in the exoskeleton) to a specific arm pose related to activities of daily living (ADL). This task was done under two conditions: demonstration and teleoperation. In the demonstration condition, the Follower could see the Leader displayed on a 2D screen in front of them showing them visually what was the correct pose whereas in the teleoperation condition, there was no visual aid but the Leader could guide the Follower using the haptic device. The study explored the efficiency, workload, and user experience of both modalities. Results indicated that teleoperation significantly reduced the time to complete tasks and facilitated more efficient and smoother movement patterns. While Leaders experienced reduced workload and increased motivation with the teleoperation condition, Followers reported less workload but also decreased motivation, suggesting a trade-off between task ease and engagement. In conclusion, the teleoperation system improves the ability for the therapist to interact with the exoskeleton but can disengage the patient.

Robotic rehabilitation systems that provide proprioceptive information offer a promising approach to helping stroke survivors regain lost proprioceptive functions. One potential way to provide proprioceptive information is viscosity rendering. However, how the modulated viscosity rendering affects brain activity remains unclear. To investigate the correlation between viscosity rendering and brain activity and to provide a neurological basis for the design of robotic rehabilitation systems, an experimental setup was developed to deliver various viscosity rendering and fixed stiffness rendering during hand movement. In the experiment, twelve healthy participants interacted with virtual bottles with the same bottle stiffness but filled with liquids of different viscosities under the same movement speed, providing different levels of proprioceptive information in the form of force on muscles and joints. Control conditions without viscosity and stiffness rendering were also tested, involving both passive and active hand movements at the same speed. Results showed that stronger mu-ERD and beta-ERD were observed during movements with viscosity and stiffness rendering compared to control conditions. No significant evidence suggested that different viscosity in rendering caused variations in mu-ERD or beta-ERD. Additionally, no significant differences were found between active movement without haptic rendering and passive movement in EEG activities. These findings suggest that while the existence of viscosity and stiffness rendering during movement strengthens brain activity, modulating viscosity rendering does not significantly affect this response. This insight is particularly valuable for designing robotic rehabilitation systems that incorporate viscosity rendering.

Virtual training environments are powerful tools for various applications. To increase the immersion and realism of these environments, several devices have been developed capable of rendering a wide range of haptic sensations. As humans mainly interact with objects using their hands, the main focus of research has been on developing devices capable of providing feedback to the hand and fingers. Currently, most of these devices only provide one form of feedback, either kinesthetic feedback to finger posture or tactile sensations in the form of pressing or skin stretching. These devices seldom provide more than one kind of feedback while remaining compact enough to be wearable with a natural range of motion of the hand. In this work, we present a device that combines an existing kinesthetic feedback glove with a novel tactile fingertip display. The haptic display consists of a cable-driven platform, powered by a stand-alone actuation module. It has been designed to be compact enough for a near-natural range of motion, with the possibility of multi-finger applications in mind. To validate the design, we conducted an experiment with 16 healthy young par- ticipants who were asked to reproduce virtual shapes with their index fingers after exploring those shapes under two different conditions: 1) with purely kinesthetic feedback, and 2) with kinesthetic feedback and tactile feedback. The outcome metrics were the exploration time, reproduction time, and reproduction error. For each testing condition, the workload and motivation of the participants were also evaluated. We found that participants had a lower reproduction error and used more time to reproduce the shapes with the novel haptic display enabled compared to purely kinesthetic feedback. We did not find significant differences in exploration time, workload, or motivation between testing conditions. Thus, the combined feedback provided by our novel device leads to better performance in shape reproduction compared to only kinesthetic feedback. Further, our device is lightweight and compact, potentially enabling multi-finger use which may lead to even greater performance and immersion in virtual object manipulation tasks.

The provision of somatosensory information may play a fundamental role in the recovery of stroke patients. Particularly, tactile information is known to influence motor control by contributing to the perception of the weight, friction, and slip condition of objects. Despite this, the inclusion of tactile information through haptic rendering in robotic neurorehabilitation systems remains largely unexplored. In this study, we present a tactile interface to extend the kinesthetic rendering capabilities of an existing hand rehabilitation robot. The developed solution relies on skin stretch stimulation of the fingerpads, which allows the rendering of interaction forces with tangible virtual objects, e.g., friction, weight, and inertia. In contrast with previous skin stretch devices, our system uses closed-loop force control for accurate force rendering, relying on a custom magnetic field-based three-axis force sensor. A three-axis positioning stage in combination with a reference force sensor was used for calibrating and characterizing the sensor, as well as evaluating the interface response. The sensor achieves shear force accuracies of 0.2 N, influenced by hysteresis and viscoelastic creep effects. The tactile interface achieves a steady-state error of 0.2–0.4N and rise times of 20–70 ms during step response tests. Frequency response tests show that the interface can successfully track signals up to 5–7 Hz. The novel use of force-controlled skin stretch stimulation aims to open a new avenue for the accurate rendering of interaction forces through the tactile sense. Moreover, through purposeful design for usage in the rehabilitation domain, we hope that this study will serve as a stepping stone toward the inclusion of tactile information in robot-assisted therapies.