Violin is one of the most complex musical instruments to learn. The learning process requires constant training and many hours of exercise and is primarily based on a student–teacher interaction where the latter guides the beginner through verbal instructions, visual demonstrations, and physical guidance. The teacher’s instruction and practice allow the student to learn gradually how to perform the correct gesture autonomously. Unfortunately, these traditional teaching methods require the constant supervision of a teacher and the interpretation of non-real-time feedback provided after the performance. To address these limitations, this work presents a novel interface (Visual Interface for Bowing Evaluation—VIBE) to facilitate student’s progression throughout the learning process, even in the absence of direct teacher intervention. The proposed interface allows two key parameters of bowing movements to be monitored, namely, the angle between the bow and the string (i.e., α angle) and the bow tilt (i.e., β angle), providing real-time visual feedback on how to correctly move the bow. Results collected on 24 beginners (12 exposed to visual feedback, 12 in a control group) showed a positive effect of the real-time visual feedback on the improvement of bow control. Moreover, the subjects exposed to visual feedback judged the latter as useful to correct their movement and clear in terms of the presentation of data. Although the task was rated as harder when performed with the additional feedback, the subjects did not perceive the presence of a violin teacher as essential to interpret the feedback.

Neurorehabilitation conventionally relies on the interaction between a patient and a physical therapist. Robotic systems can improve and enrich the physical feedback provided to patients after neurological injury, but they under-utilize the adaptability and clinical expertise of trained therapists. In this position paper, we advocate for a novel approach that integrates the therapist’s clinical expertise and nuanced decision-making with the strength, accuracy, and repeatability of robotics: Robot-mediated physical Human–Human Interaction. This framework, which enables two individuals to physically interact through robotic devices, has been studied across diverse research groups and has recently emerged as a promising link between conventional manual therapy and rehabilitation robotics, harmonizing the strengths of both approaches. Although current findings are largely based on pilot studies and conceptual frameworks, integrating therapists’ expertise with the functionalities offered by robotic systems represents a promising direction for improving rehabilitation outcomes. This paper presents the rationale of a multidisciplinary team—including engineers, doctors, and physical therapists—for conducting research that utilizes: a unified taxonomy to describe robot-mediated rehabilitation, a framework of interaction based on social psychology, and a technological approach that makes robotic systems seamless facilitators of natural human-human interaction.

Recent advances in the control of overground exoskeletons are being centered on improving balance support and decreasing the reliance on crutches. However, appropriate methods to quantify the stability of these exoskeletons (and their users) are still under development. A reliable and reproducible balance assessment is critical to enrich exoskeletons’ performance and their interaction with humans. In this work, we present the BenchBalance system, which is a benchmarking solution to conduct reproducible balance assessments of exoskeletons and their users. Integrating two key elements, i.e., a hand-held perturbator and a smart garment, BenchBalance is a portable and low-cost system that provides a quantitative assessment related to the reaction and capacity of wearable exoskeletons and their users to respond to controlled external perturbations. A software interface is used to guide the experimenter throughout a predefined protocol of measurable perturbations, taking into account antero-posterior and mediolateral responses. In total, the protocol is composed of sixteen perturbation conditions, which vary in magnitude and location while still controlling their orientation. The data acquired by the interface are classified and saved for a subsequent analysis based on synthetic metrics. In this paper, we present a proof of principle of the BenchBalance system with a healthy user in two scenarios: subject not wearing and subject wearing the H2 lower-limb exoskeleton. After a brief training period, the experimenter was able to provide the manual perturbations of the protocol in a consistent and reproducible way. The balance metrics defined within the BenchBalance framework were able to detect differences in performance depending on the perturbation magnitude, location, and the presence or not of the exoskeleton. The BenchBalance system will be integrated at EUROBENCH facilities to benchmark the balance capabilities of wearable exoskeletons and their users.

Haptic human-robot-human interaction allows users to feel and respond to one another’s forces while interfacing with separate robotic devices, providing customizable infrastructure for studying physical interaction during motor tasks (e.g., physical rehabilitation). For upper- and lower-limb tracking tasks, previous work has shown that virtual interactions with a partner can improve motor performance depending on the skill level of each partner. However, whether the mechanism explaining these improvements is identical in the upper and lower limbs is an open question. In this work, we investigate the effects of haptic interaction between healthy individuals during a trajectory tracking task involving single-joint movements at the wrist and ankle. We compare tracking performance and muscle activation during haptic conditions where pairs of participants were uni- and bidirectionally connected to investigate the contribution of real-time responses from a partner during the interaction. Findings showed similar improvements in tracking performance during bidirectional interaction for both the wrist and ankle. This was observed despite distinct strategies in muscle co-contraction between joints, as co-contraction was dependent on partner ability for the wrist but not the ankle. For each joint, bidirectional and unidirectional interaction resulted in similar improvements for the worse partner in the dyad. For the better partner, bidirectional interaction resulted in greater improvements than unidirectional interaction. While these results suggest that unidirectional interaction is sufficient for error correction of less skilled individuals during simple motor tasks, they also highlight the mutual benefits of bidirectional interaction which are consistent across the upper and lower limbs.

Human-centred research involving advanced technological solutions is increasingly utilizing complex multi-modal systems. This often necessitates the combined use of various devices, leading to challenges in synchronization and compatibility, and highlighting the need for flexible and modular platforms to facilitate integration. This paper presents the end-to-end development of Central Control Software (CCS), a novel open-source platform that serves as a central hub for seamless integration of various technological equipment, such as hardware devices or software applications. CCS is designed to facilitate the integration of additional modules without affecting the overall functionality due to its modular architecture while keeping the high-level components easily usable by a wide and heterogeneous spectrum of users. The platform has been systematically tested to validate its performance in terms of real-time functioning, reliability, efficiency in resource consumption, scalability with increasing workload, and stability over extended operational periods in different experimental conditions, with varying numbers of connected modules and duration of recording. Moreover, the system was tested for its degree of usability on twenty users with different backgrounds, i.e., ten experts (technical users) and ten non-experts (non-technical users). Participants’ performance was analysed with quantitative measurements and their scores to the System Usability Scale. Results confirmed the fulfillment of the identified requirements and highlighted a high usability score (around 90/100) without statistically significant differences between the two groups, suggesting that it can be easily used by researchers with different backgrounds.

Haptic human-robot-human interaction allows users to feel and respond to one another’s forces while interfacing with separate robotic devices, providing customizable infrastructure for studying physical interaction during motor tasks (i.e., physical rehabilitation). For both upper- and lower-limb tasks, previous work has shown that virtual interactions with a partner can improve motor performance and enhance individual learning. However, whether the mechanism of these improvements generalizes across different human systems is an open question. In this work, we investigate the effects of haptic interaction between healthy individuals during a trajectory tracking task involving single-joint movements at the wrist and ankle. We compare tracking performance and muscle activation during haptic conditions where pairs of participants were uni- and bidirectionally connected, in order to investigate the contribution of real-time responses from a partner during the interaction. Findings indicate similar improvements in tracking performance during the bidirectional interaction for both the wrist and ankle, despite significant differences in how individuals modulated co-contraction. For each joint, bidirectional and unidirectional interaction resulted in similar improvements for the worse partner in the dyad. For the better partner, bidirectional interaction outperformed unidirectional interaction, likely due to changes in movement planning that were not observed in the unidirectional condition. While these results suggest that unidirectional interaction is sufficient for error correction of less skilled individuals during simple motor tasks, they also highlight the mutual benefits of bidirectional interaction which are consistent across the upper and lower limbs.