One of the major limitations to the use of advanced robotic hands in industries is the complexity of the control system design due to the large number of motors needed to actuate their degrees of freedom. It is our belief that the development of a unified control framework for robotic hands will allow us to extend the use of these devices in many areas. Borrowing the terminology from software engineering, there is a need for middleware solutions to control the robotic hands independently from their specific kinematics and focus only on the manipulation tasks. To simplify and generalize the control of robotic hands, we take inspiration from studies in neuroscience concerning the sensorimotor organization of the human hand. These studies demonstrated that, notwithstanding the complexity of the hand, a few variables are able to account for most of the variance in the patterns of configurations and movements. The reduced set of parameters that humans effectively use to control their hands, which are known in the literature as synergies, can represent the set of words for the unified control language of robotic hands, provided that we solve the problem of mapping human hand synergies to actions of the robotic hands. In this study, we propose a mapping designed in the manipulated object domain in order to ensure a high level of generality with respect to the many dissimilar kinematics of robotic hands. The role of the object is played by a virtual sphere, whose radius and center position change dynamically, and the role of the human hand is played by a hand model referred to as “paradigmatic hand,” which is able to capture the idea of synergies in human hands.

This letter presents the Soft-SixthFinger, a wearable robotic extra-finger designed to be used by chronic stroke patients to compensate for the missing hand function of their paretic limb. The extra-finger is an underactuated modular structure worn on the paretic forearm by means of an elastic band. The device and the paretic hand/arm act like the two parts of a gripper working together to hold an object. The patient can control the flexion/extension of the robotic finger through the eCap, an electromyography-based (EMG) interface embedded in a cap. The user can control the device by contracting the frontalis muscle. Such contraction can be achieved simply moving his or her eyebrows upwards. The Soft-SixthFinger has been designed as tool that can be used by chronic stroke patients to compensate for grasping in many activities of daily living (ADL). It can be wrapped around the wrist and worn as a bracelet when not used. The light weight and the complete wireless connection with the EMG interface guarantee a high portability and wearability. We tested the device with qualitative experiments involving six chronic stroke patients. Results show that the proposed system significantly improves the performances of the patients in the proposed tests and, more in general, their autonomy in ADL.

As a result of several governments closing educational facilities in reaction to the COVID-19 pandemic in 2020, almost 80% of the world’s students were not in school for several weeks. Schools and universities are thus increasing their efforts to leverage educational resources and provide possibilities for remote learning. A variety of educational programs, platforms, and technologies are now accessible to support student learning; while these tools are important for society, they are primarily concerned with the dissemination of theoretical material. There is a lack of support for hands-on laboratory work and practical experience. This is particularly important for all disciplines related to science, technology, engineering, and mathematics (STEM), where labs and pedagogical assets must be continuously enhanced in order to provide effective study programs. In this study, we describe a unique perspective to achieving multi-sensory learning through the integration of virtual and augmented reality (VR/AR) with haptic wearables in STEM education. We address the implications of a novel viewpoint on established pedagogical notions. We want to encourage worldwide efforts to make fully immersive, open, and remote laboratory learning a reality.

Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human-robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user-feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real-world tasks are discussed. In all topic areas, the design of human-oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions.

Supernumerary robotic limbs (SRLs) are wearable robots designed to enhance the sensorimotor abilities of humans. SRLs can be used to compensate for lost functions in patients with motor deficits and, more in general, to augment the sensorimotor capabilities of humans to interact with the environment. The design and control of SRLs present several challenges. SRLs must have high levels of ergonomics and wearability and, depending on the application, they might also require enhanced robustness and strength. Supernumerary robotics differs from collaborative robotics, since SRLs are not collaborative external agents but rather act under the direct command of the operator who, thanks to the use of suitable interfaces, gains the control of some actions of the SRLs. From the control point of view, it is fundamental to find the right trade-off between the degrees of freedom that are under the direct control of the user and the level of robot autonomy. The adoption of feedback interfaces can help the human to better command and use the SRL. In this review, we discuss all these aspects, relating them to the current literature on SRLs. We also present the main applications and the potential of these relatively recent devices, as well as the main neuroscientific questions they rise on the implications of their use on the users’ body schema.