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Abstract Background Cybathlon championship aims at promoting the development of prosthetic and assistive devices capable to meet users’ needs. This paper describes and analyses possible exploitation outcomes of our team’s (REHAB TECH) experience into the Powered Arm Prosthesis Race of the Cybathlon 2020 Global Edition, with the novel prosthetic system Hannes. In detail, we present our analysis on a concurrent evaluation conducted to verify if the Cybathlon training and competition positively influenced pilot’s performance and human-technology integration with Hannes, with respect to a non-runner Hannes user. Methods Two transradial amputees were recruited as pilots (Pilot 1 and Pilot 2) for the Cybathlon competition and were given the polyarticulated myoelectric prosthetic hand Hannes. Due to COVID-19 emergency, only Pilot 1 was trained for the race. However, both pilots kept Hannes for Home Use for seven weeks. Before this period, they both participated to the evaluation of functionality, embodiment, and user experience (UX) related to Hannes, which they repeated at the end of the Home Use and right after the competition. We analysed Pilot 1’s training and race outcomes, as well as changes in the concurrent evaluation, and compared these results with Pilot 2’s ones. Results The Cybathlon training gradually improved Pilot 1’s performances, leading to the sixth place with a single error in task 5. In the parallel evaluation, both pilots had an overall improvement over time, whereas Pilot 2 experienced a deterioration of embodiment. In detail, Pilot 1, who followed the training and raced the Cybathlon, improved in greater way. Conclusion Hannes demonstrated to be a valuable competitor and to perform grasps with human-like behaviors. The higher improvements of Pilot 1, who actively participated in the Cybathlon, in terms of functionality, embodiment and UX, may depend on his training and engagement in the effort of achieving a successful user-prosthesis interaction during the competition. Tasks based on Cybathlon’s ones could improve the training phase of a prosthetic user, stimulating dexterity, prosthetic integration, and user perception towards the prosthesis. Likewise, timed races or competitions could facilitate and accelerate the learning phase, improving the efficiency and efficacy of the process.

IntroductionIn recent years, hand prostheses achieved relevant improvements in term of both motor and functional recovery. However, the rate of devices abandonment, also due to their poor embodiment, is still high. The embodiment defines the integration of an external object – in this case a prosthetic device – into the body scheme of an individual. One of the limiting factors causing lack of embodiment is the absence of a direct interaction between user and environment. Many studies focused on the extraction of tactile information via custom electronic skin technologies coupled with dedicated haptic feedback, though increasing the complexity of the prosthetic system. Contrary wise, this paper stems from the authors' preliminary works on multi-body prosthetic hand modeling and the identification of possible intrinsic information to assess object stiffness during interaction.MethodsBased on these initial findings, this work presents the design, implementation and clinical validation of a novel real-time stiffness detection strategy, without ad-hoc sensing, based on a Non-linear Logistic Regression (NLR) classifier. This exploits the minimum grasp information available from an under-sensorized and under-actuated myoelectric prosthetic hand, Hannes. The NLR algorithm takes as input motor-side current, encoder position, and reference position of the hand and provides as output a classification of the grasped object (no-object, rigid object, and soft object). This information is then transmitted to the user via vibratory feedback to close the loop between user control and prosthesis interaction. This implementation was validated through a user study conducted both on able bodied subjects and amputees.ResultsThe classifier achieved excellent performance in terms of F1Score (94.93%). Further, the able-bodied subjects and amputees were able to successfully detect the objects' stiffness with a F1Score of 94.08% and 86.41%, respectively, by using our proposed feedback strategy. This strategy allowed amputees to quickly recognize the objects' stiffness (response time of 2.82 s), indicating high intuitiveness, and it was overall appreciated as demonstrated by the questionnaire. Furthermore, an embodiment improvement was also obtained as highlighted by the proprioceptive drift toward the prosthesis (0.7 cm).

Enhancing the embodiment of artificial limbs—the individuals' feeling that a virtual or robotic limb is integrated in their own body scheme—is an impactful strategy for improving prosthetic technology acceptance and human-machine interaction. Most studies so far focused on visuo-tactile strategies to empower the embodiment processes. However, novel approaches could emerge from self-regulation techniques able to change the psychophysiological conditions of an individual. Accordingly, this pilot study investigates the effects of a self-regulated breathing exercise on the processes of body ownership underlying the embodiment of a virtual right hand within a Spatially Augmented Respiratory Biofeedback (SARB) setting. This investigation also aims at evaluating the feasibility of the breathing exercise enabled by a low-cost SARB implementation designed for upcoming remote studies (a need emerged during the COVID-19 pandemic). Twenty-two subjects without impairments, and two transradial prosthesis users for a preparatory test, were asked (in each condition of a within-group design) to maintain a normal (about 14 breaths/min) or slow (about 6 breaths/min) respiratory rate to keep a static virtual right hand “visible” on a screen. Meanwhile, a computer-generated sphere moved from left to right toward the virtual hand during each trial (1 min) of 16. If the participant's breathing rate was within the target (slow or normal) range, a visuo-tactile event was triggered by the sphere passing under the virtual hand (the subjects observed it shaking while they perceived a vibratory feedback generated by a smartphone). Our results—mainly based on questionnaire scores and proprioceptive drift—highlight that the slow breathing condition induced higher embodiment than the normal one. This preliminary study reveals the feasibility and potential of a novel psychophysiological training strategy to enhance the embodiment of artificial limbs. Future studies are needed to further investigate mechanisms, efficacy and generalizability of the SARB techniques in training a bionic limb embodiment.