This paper introduces an upper limb postural optimization method for enhancing physical ergonomics and force manipulability during bimanual human-robot co-carrying tasks. Existing research typically emphasizes human safety or manipulative efficiency, whereas our proposed method uniquely integrates both aspects to strengthen collaboration across diverse conditions (e.g., different grasping postures of humans, and different shapes of objects). Specifically, the joint angles of a simplified human skeleton model are optimized by minimizing the cost function to prioritize safety and manipulative capability. To guide humans towards the optimized posture, the reference end-effector poses of the robot are generated through a transformation module. A bimanual model predictive impedance controller (MPIC) is proposed for our human-like robot, CURI, to recalibrate the end effector poses through planned trajectories. The proposed method has been validated through various subjects and objects during human-human collaboration (HHC) and human-robot collaboration (HRC). The experimental results demonstrate significant improvement in muscle conditions by comparing the activation of target muscles before and after optimization.

Lower-limb exosuits are particularly relevant for individuals with some degree of mobility impairment, such as post-stroke patients or older adults with reduced movement capabilities. This study aims to investigate the mental workload (MWL) assessment of XoSoft, a lower-limb soft exoskeleton, using and comparing subjective and objective physiological metrics. The NASA-TLX questionnaire, the average percentage change in pupil size (APCPS), and the Baevsky stress index (SI) are compared. The experiments were conducted on 18 healthy subjects while walking and involved mathematical tasks to create a double-task condition. The results show a complex interaction between task difficulty, exoskeleton activation, and pupillary dynamics, suggesting that the subject might reach a saturated condition under a high mental load. Besides, the data indicate that pupil diameter may be an objective mental workload indicator that correlates with subjective NASA-TLX questionnaires. The discordant indications from the stress index suggest how different metrics of the ocular and cardiac levels respond differently to various stimuli and dynamics. Research has also revealed ocular asymmetry, with the right eye more sensitive to cognitive load.

Upper Limb (UL) Rehabilitation in Multiple Scle- rosis (MS) is an open research field due to the complex interplay between cognitive and physical dysfunctions. Virtual Reality (VR) can face such an issue by enriching physical training with engaging features, including biofeedback strategies to self- regulate autonomic functions according to the visualisation of indices like heart rate variability (HRV). In the present work, HRV biofeedback is introduced in a VR-based exergame (a game designed to promote exercising), tailored to rehabilitation of the dominant upper limb in Persons with MS (PwMS). The exergame is based on a dual-task paradigm, integrating a UL motor rehabilitative task with a breathing task. The aim is to investigate how the design developed for the HRV biofeedback affects engagement and performance during the exergame session. As a preliminary study, sixteen able-bodied subjects are tested in a within-subjects design, to assess the quality of the game features and design, before approaching MS patients. Two conditions are presented, with and without biofeedback. The proposed HRV biofeedback has two possible levels, depending on whether or not the desired respiratory rate of six breaths/min is successfully maintained. It is used to control game elements and change difficulty of the session. The main finding of this study is that biofeedback improves both user performance and experience in healthy subjects. These results underline the great potential of this technique to promote engagement. Thus, they point to fostering the rehabilitative effectiveness of repetitive motor tasks and encouraging adherence to the long- term training. Future studies will encompass fine tuning of the experimental setup and include PwMS to further adjust the game to patients' needs and observe the setup compliance to rehabilitation settings.

Literature highlights how virtual and augmented settings offer engaging solutions to improve one's feeling of an artificial limb embodiment. In this paper, we explored the potential of a setting for Spatial Augmented Reality (SAR, where a display augments a surface without making the user wear any visor) in two conditions of a lower limb ownership training involving subjects without disabilities. In the first condition, the subject must contract the quadriceps of a leg for commanding (through electromyography, EMG) a virtual leg (a 3D model of the Hybrid Knee prosthesis) to kick a virtual wall: each collision corresponds to a vibratory feedback on the thigh (a position defined for upcoming tests with transfemural amputees). The second condition adds a social context to engage the user: the subject is asked to cooperate with another (fictional) player to kick on the same virtual wall. Subjective (through questionnaires) and objective (according to the number of kicks as a performance index, and the proprioceptive drift as an embodiment index) assessments have been performed before a rubber leg illusion test. Overall, we observed how the cooperative task can engage the subject to be more active. However, this condition can reduce the impact of the training on the embodiment itself, probably because the social task generates a distraction. Nevertheless, such findings suggest the possibility to alternate these two tasks in the same session to increase the duration of a prosthetic embodiment training.

Recent literature suggests that self-regulation techniques like biofeedback can be used to enhance the embodiment of artificial limbs. In this study, we developed and preliminarily tested an embodiment training protocol based on a Spatial Augmented Respiratory Cardiofeedback (SARC) implemented through a computer screen - visualizing a 3D model of a prosthetic hand (Hannes) - and a thoracic band for monitoring the Heart Rate Variability (HRV) of the users. The feedback was based on the respiratory-driven modulation of a composite index of the individuals’ cardiac autonomic state after an initial calibration based on slow breathing (at a rate perceived as “comfortable”). Alongside the assessment of the SARC use feasibility, this pilot study evaluates the virtual hand embodiment obtained in two task conditions. In both conditions, the virtual limb gradually appears when the cardiofeedback exercise is performed correctly. Otherwise, the virtual limb parts gradually disappear (“unstable” condition) or they remain visible (cumulative” condition). In the latter case, the virtual hand maintains its “reality-based” stability, supporting the subject’s motivation. Ten volunteers without disabilities were presented both conditions on 10 trials each (2min per trial). Their experience and their proprioceptive drift (estimating their real hand position as close to the artificial one) were assessed as measures of virtual prosthesis embodiment. The questionnaire results preliminarily highlight the feasibility of the SARC. Furthermore, a significantly stronger drift for the virtual prosthesis occurred in the cumulative condition, orienting further investigations.

Shared control and shared autonomy play an important role in assistive technologies, allowing the offloading of the cognitive burden required for control from the user to the intelligent robotic device. In this context, electrophysiological measures of error detection, directly measured from a person's brain activity as Error-related Potentials (ErrPs), can be exploited to provide passive adaptation of an external semi-autonomous system to the human. This concept was implemented in an online robot learning task, where user's evaluation of the robot's actions, in terms of detected ErrP, was exploited to update a reward function in a Reinforcement Learning (RL) framework. Results from both simulated and experimental studies show that the introduction of human evaluation in the robot learning loop allows for: (1) the acceleration of optimal policy learning in a target reaching task, (2) the introduction of a further degree of control in robot learning, namely identification of one among multiple targets, according to the user's will. Overall, presented results support the potential of human-robot co-adaptive and co-operative strategies to develop human-centered assistive technologies.

Error-related electroencephalographic (EEG) potentials (ErrPs) have been explored to improve the reliability of modern Brain-Computer Interfaces (BCIs), thanks to the information they carry about user awareness of erroneous responses. ErrPs detection on a single-trial basis has been successfully demonstrated, and proved to effectively enhance human-computer interaction and BCI performance. Previous studies tested ErrPs elicited by providing either visual or tactile feedback, showing similar results for all feedback modalities. In the present work, we tested: 1) whether the addition of tactile feedback can improve the detection of ErrP, when used in combination and not alternatively to visual feedback; 2) whether a mismatch between the two different sensory channels can enhance ErrP detection. Results on a study carried out on 12 healthy subjects show that the addition of tactile stimuli significantly affects single-trial ErrP recognition (AUC increment of 4.3%) without significant difference in case of concordant or discordant visual and tactile stimuli.

Brain-computer interfaces (BCIs) offer high potential for enhancing training in many tasks, especially those that require maintaining high levels of concentration such as surgery. Training focus and attention can play a critical role in surgery since concentration on the task at hand is fundamental to prevent life-threatening errors. In this paper we propose a new method for concentration training in the context of robot-assisted laser microsurgery associated to a feedback design that makes the interaction more intuitive. This approach couples augmented reality (AR) features to both BCI-based on-line measurement of the user's mental focus and the control of the surgical robot. The methodology is described as a brain-controlled augmented reality (BcAR) training system. AR is used to maintain the surgeon's perceptual contact with the real operating setting, while focus stimulation is provided by modifying features of an AR item based on real-time monitoring of the user's mental state. In this research a low-cost EEG device is used and the BcAR is implemented in the form of an AR scalpel that behaves as a "retractable" knife according to the user's mental focus: low concentration levels retract the knife and prevent cutting. This design provides directional compatibility between the AR feedback animation and the spontaneous motion of user's attention along the AR tool, resulting in an intuitive system with real impact on the training outcome. This is demonstrated through user trials and comparison with training based on simple AR feedback (no EEG). Results demonstrate the potential of the approach, showing a significant improvement in post-training task execution time without any detriment to user experience. Subjective questionnaires also confirmed the critical role of directional compatibility in the AR feedback. Such findings allow the identification of further improvements and novel potential applications of this interaction paradigm.

Several studies showed the potential of interaction technologies for assisting the performance of users during motor tasks. In particular, repetitive exercises can take advantage of novel interaction strategies in order to sustain the users efforts to maintain the target level of performance. This paper introduces a paradigm for performing a drag and drop movement of Augmented Reality 3D objects from marker to marker, using a smartphone. This interaction paradigm permits to perform repetitive exercises which can be implemented in upper limb motor training and rehabilitation tasks. After introducing the interaction paradigm, the paper describes the methodology and the results of a pilot study about the effects of AR dynamic features on the users movements and experience during repetitive motor tasks.

Innovative design features of user interfaces could assist a patient during the accomplishment of repetitive physical exercises in training and rehabilitation. Dual task paradigms can induce a change in attentional focus allocation, moving focus away from a body part which is affected by fatigue. This study proposes an interface which integrates the motion tracking capabilities of a Kinect with the touch screen input data and vibration feedback of a smart phone. This interface is exploited to design and evaluate a dual task paradigm tested through an experimental study. Purpose of such paradigm is to support upper arm rehabilitation, by generating a distraction from the target area of the limb during repetitive tasks. The data collected during the experiments and the interface itself will be analyzed and discussed.

State-of-the-art laser phonomicrosurgery (LP) used for the treatment of laryngeal abnormalities involves complex otolaryngological surgical techniques. It relies heavily on surgeon dexterity, requiring significant psychomotor skills. Equipment scale and size, laser operative distance, and the anatomically small nature of the vocal folds all combine to compound the surgical challenges. An objective measurement is therefore necessary to understand the impact of equipment design, its usability, surgeon skill, and learning, on performing LP effectively. This paper introduces imaging based feature extraction as a method to establish metrics to assess surgical performance in LP. Experimental analysis demonstrates the utility of these metrics in measuring surgical task execution vis-à-vis the task objectives. The metrics also provide for a combined rating scale giving a robust quantitative classification of the levels of surgical performance.

Robot-assisted surgical procedures, such as Laser Phonomicrosurgery (LP), suffer from susceptibility to variation in surgeon skill and equipment characteristics. Ergonomic and human-centered approaches acquire increased importance in the design of surgeon-machine interfaces. This paper proposes a protocol for comparative evaluation of surgeon-machine interfaces based on two criteria: (i) the subjective evaluation of their usability using questionnaires, and (ii) the objective evaluation of their performance using an imaging-based feature extraction method. Two interfaces in LP, the traditional (“AcuBlade”) interface and the novel (“Virtual Scalpel”) interface, were evaluated to demonstrate the effectiveness of the proposed scheme. A series of experimental trials were conducted using the interfaces in surgery-like tasks in a controlled environment. The subjective evaluation pointed to the superiority of the Virtual Scalpel interface (score: 83.06) in terms of confidence and ease of use, and learnability, over the AcuBlade interface (score: 65.56). The objective evaluation showed the Virtual Scalpel interface having an overall score (55.96) significantly superior to the AcuBlade (51.37). It is thus shown that the multidimensional evaluation approach allowed to clearly distinguish between levels of perceived usability and effective performance of surgeon-machine interfaces from a user-centered perspective.