Experimental evaluation of the impact of sEMG interfaces in enhancing embodiment of virtual myoelectric prostheses.

Introduction: Despite recent technological advances that have led to sophisticated bionic prostheses, attaining embodied solutions still remains a challenge. Recently, the investigation of prosthetic embodiment has become a topic of interest in the research community, which deals with enhancing the perception of artificial limbs as part of users' own body. Surface electromyography (sEMG) interfaces have emerged as a promising technology for enhancing upper-limb prosthetic control.

Spatial and Temporal Analysis of Normal and Shear Forces During Grasping, Manipulation and Social Activities.

Extensive research has established and widely acknowledged the important contribution of human hand sensory receptors in providing tactile feedback. The absence of these receptors results in a poor perception of the environment, impairing our efficient manipulation skills. Although the literature emphasizes the significance of normal forces in human grasping, further investigations should point toward the role of shear forces in this process.

6IMPOSE: bridging the reality gap in 6D pose estimation for robotic grasping.

6D pose recognition has been a crucial factor in the success of robotic grasping, and recent deep learning based approaches have achieved remarkable results on benchmarks. However, their generalization capabilities in real-world applications remain unclear. To overcome this gap, we introduce 6IMPOSE, a novel framework for sim-to-real data generation and 6D pose estimation.

Functional assessment of current upper limb prostheses: An integrated clinical and technological perspective.

Although recent technological developments in the field of bionic upper limb prostheses, their rejection rate remains excessively high. The reasons are diverse (e.g.

The SoftHand Pro platform: a flexible prosthesis with a user-centered approach.

Background: Among commercially-available upper-limb prostheses, the two most often used solutions are simple hook-style grippers and poly-articulated hands, which present a higher number of articulations and show a closer resemblance to biological limbs. In their majority, the former type of prostheses is body-powered, while the second type is controlled by myoelectric signals. Body-powered grippers are easy to control and allow a simple form of force feedback, frequently appreciated by users.

Comparison between rigid and soft poly-articulated prosthetic hands in non-expert myo-electric users shows advantages of soft robotics.

Notwithstanding the advancement of modern bionic hands and the large variety of prosthetic hands in the market, commercial devices still present limited acceptance and percentage of daily use. While commercial prostheses present rigid mechanical structures, emerging trends in the design of robotic hands are moving towards soft technologies. Although this approach is inspired by nature and could be promising for prosthetic applications, there is scant literature concerning its benefits for end-users and in real-life scenarios.

Usability Assessment of Body Controlled Electric Hand Prostheses: A Pilot Study.

Poly-articulated hands, actuated by multiple motors and controlled by surface myoelectric technologies, represent the most advanced aids among commercial prostheses. However, simple hook-like body-powered solutions are still preferred for their robustness and control reliability, especially for challenging environments (such as those encountered in manual work or developing countries). This study presents the mechatronic implementation and the usability assessment of the SoftHand Pro-Hybrid, a family of poly-articulated, electrically-actuated, and body-controlled artificial hands, which combines the main advantages of both body-powered and myoelectric systems in a single device.

An Adaptive Multi-Modal Control Strategy to Attenuate the Limb Position Effect in Myoelectric Pattern Recognition.

Over the last few decades, pattern recognition algorithms have shown promising results in the field of upper limb prostheses myoelectric control and are now gradually being incorporated in commercial devices. A widely used approach is based on a classifier which assigns a specific input value to a selected hand motion. While this method guarantees good performance and robustness within each class, it still shows limitations in adapting to different conditions encountered in real-world applications, such as changes in limb position or external loads.

Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand.

Background: State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently, the translation of neuroscientific theories (i.

Evaluation of a Simultaneous Myoelectric Control Strategy for a Multi-DoF Transradial Prosthesis.

While natural movements result from fluid coordination of multiple joints, commercial upper-limb prostheses are still limited to sequential control of multiple degrees of freedom (DoFs), or constrained to move along predefined patterns. To control multiple DoFs simultaneously, a probability-weighted regression (PWR) method has been proposed and has previously shown good performance with intramuscular electromyographic (EMG) sensors. This study aims to evaluate the PWR method for the simultaneous and proportional control of multiple DoFs using surface EMG sensors and compare the performance with a classical direct control strategy.

Exploring Stiffness Modulation in Prosthetic Hands and Its Perceived Function in Manipulation and Social Interaction.

To physically interact with a rich variety of environments and to match situation-dependent requirements, humans adapt both the force and stiffness of their limbs. Reflecting this behavior in prostheses may promote a more natural and intuitive control and, consequently, improve prostheses acceptance in everyday life. This pilot study proposes a method to control a prosthetic robot hand and its impedance, and explores the utility of variable stiffness when performing activities of daily living and physical social interactions.

An Objective Functional Evaluation of Myoelectrically-Controlled Hand Prostheses: A Pilot Study Using the Virtual Peg Insertion Test.

Assessing upper limb prostheses and their influence when performing goal-directed activities is essential to compare the quality of different devices and optimize their control settings. Currently available assessments are often subjective, insensitive, and cannot provide a detailed evaluation of prostheses and their usage. The goal of this pilot study was to explore the feasibility of using the Virtual Peg Insertion Test (VPIT) to provide an in-depth assessment of a prosthesis and its functional performance.

Design and Assessment of Control Maps for Multi-Channel sEMG-Driven Prostheses and Supernumerary Limbs.

Proportional and simultaneous control algorithms are considered as one of the most effective ways of mapping electromyographic signals to an artificial device. However, the applicability of these methods is limited by the high number of electromyographic features that they require to operate-typically twice as many the actuators to be controlled. Indeed, extracting many independent electromyographic signals is challenging for a number of reasons-ranging from technological to anatomical.

SoftHand at the CYBATHLON: a user's experience.

Background: Roughly one-quarter of upper limb prosthesis users reject their prosthesis. Reasons for rejection range from comfort, to cost, aesthetics, function, and more. This paper follows a single user from training with and testing of a novel upper-limb myoelectric prosthesis (the SoftHand Pro) for participation in the CYBATHLON rehearsal to training for and competing in the CYBATHLON 2016 with a figure-of-nine harness controlled powered prosthesis (SoftHand Pro-H) to explore the feasibility and usability of a flexible anthropomorphic prosthetic hand.

Preliminary results toward a naturally controlled multi-synergistic prosthetic hand.

Robotic hands embedding human motor control principles in their mechanical design are getting increasing interest thanks to their simplicity and robustness, combined with good performance. Another key aspect of these hands is that humans can use them very effectively thanks to the similarity of their behavior with real hands. Nevertheless, controlling more than one degree of actuation remains a challenging task.