Sensory output produced by a robotic hand during grasping and manipulation evoked real-time nearly natural force and slippage feedback.

Tactile sensing is fundamental for the human hand to achieve high dexterity. Most prosthetic hands are still devoid of tactile sensors, implying that the user cannot perceive external stimulation nor react in a fine manner. As a consequence, unforeseen events, e.g., slippage, are difficult to manage. This article proposes an algorithm to perform slippage detection with tactile sensors integrated into prosthetic hands. The algorithm is based on the filtering of the tactile sensor output; rectification and envelope follow the filtering. A binary signal, relating to slippage, is finally computed. An electrical circuit has been designed and built to elaborate the tactile signals. These have been embedded in a bioinspired fingertip mounted on a prosthetic hand, which has been interfaced with a robotic arm to assess the algorithm capability to identify slippage. Eight different surfaces have been employed, while three sliding velocities have been tested with a random interaction force between the fingertip and the test surfaces. Finally, experiments in a closed-loop configuration have been conducted to demonstrate the algorithm effectiveness in dynamic manipulation. Results proved the adequacy of the algorithm in terms of slippage detection and short latency between onset of slippage, actual detection and hand reaction.

The evolution of technological and surgical techniques has made it possible to obtain an even more intuitive control of multiple joints using advanced prosthetic systems. Targeted Muscle Reinnervation (TMR) is considered to be an innovative and relevant surgical technique for improving the prosthetic control for people with different amputation levels of the limb. Indeed, TMR surgery makes it possible to obtain reinnervated areas that act as biological amplifiers of the motor control. On the technological side, a great deal of research has been conducted in order to evaluate various types of myoelectric prosthetic control strategies, whether direct control or pattern recognition-based control. In the literature, different control performance metrics, which have been evaluated on TMR subjects, have been introduced, but no accepted reference standard defines the better strategy for evaluating the prosthetic control. Indeed, the presence of several evaluation tests that are based on different metrics makes it difficult the definition of standard guidelines for comprehending the potentiality of the proposed control systems. Additionally, there is a lack of evidence about the comparison of different evaluation approaches or the presence of guidelines on the most suitable test to proceed for a TMR patients case study. Thus, this review aims at identifying these limitations by examining the several studies in the literature on TMR subjects, with different amputation levels, and proposing a standard method for evaluating the control performance metrics.

Pedicle screw fixation is a fundamental surgical procedure which requires high accuracy and strength from the surgeon who may be exposed to uncomfortable postures and muscular fatigue. The objective of this paper is to propose a novel approach to robot-aided pedicle screw fixation based on a Surgeon-Robot Shared control that makes the tapping procedure i.e. threading the patient's pedicle, semi-autonomous. The surgeon continues to have a full control over the surgical intervention by i) accurately move the robot end-effector using a hands-on control interface, i.e. the surgical tapper, along a pre-planned axis, ii) continuously controlling the forces exerted onto the patient spine during the tapping phase, iii) modulating the torque about the tapping axis by adequately tuning the tool-bone interaction force along the same axis. Furthermore, the procedure appears to be more comfortable and less tiring for the surgeon. The proposed approach was tested on eight subjects who were asked to perform the tapping procedure onto an anthropomorphic spine phantom. A comparative analysis among the proposed approach and the ones typically adopted in literature to perform pedicle screw placement was carried out. The experimental results demonstrated that proposed approach, with respect to the traditional robot-aided procedure, guarantees comparable accuracy and efficiency in the screw placement and lower fatigue and more comfortable postures for the surgeon.

The abilities of the human hand have always fascinated people, and many studies have been devoted to describing and understanding a mechanism so perfect and important for human activities. Hand loss can significantly affect the level of autonomy and the capability of performing the activities of daily life. Although the technological improvements have led to the development of mechanically advanced commercial prostheses, the control strategies are rather simple (proportional or on/off control). The use of these commercial systems is unnatural and not intuitive, and therefore frequently abandoned by amputees. The components of an active prosthetic hand are the mechatronic device, the decoding system of human biological signals into gestures and the control law that translates all the inputs into desired movements. The real challenge is the development of a control law replacing human hand functions. This paper presents a literature review of the control strategies of prosthetics hands with a multiple-layer or hierarchical structure, and points out the main critical aspects of the current solutions, in terms of human’s functions replicated with the prosthetic device. The paper finally provides several suggestions for designing a control strategy able to mimic the functions of the human hand.