1,325 research outputs found

    On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

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    Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

    Multimodal human hand motion sensing and analysis - a review

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    Human-robot interaction for assistive robotics

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    This dissertation presents an in-depth study of human-robot interaction (HRI) withapplication to assistive robotics. In various studies, dexterous in-hand manipulation is included, assistive robots for Sit-To-stand (STS) assistance along with the human intention estimation. In Chapter 1, the background and issues of HRI are explicitly discussed. In Chapter 2, the literature review introduces the recent state-of-the-art research on HRI, such as physical Human-Robot Interaction (HRI), robot STS assistance, dexterous in hand manipulation and human intention estimation. In Chapter 3, various models and control algorithms are described in detail. Chapter 4 introduces the research equipment. Chapter 5 presents innovative theories and implementations of HRI in assistive robotics, including a general methodology of robotic assistance from the human perspective, novel hardware design, robotic sit-to-stand (STS) assistance, human intention estimation, and control

    Ground Robotic Hand Applications for the Space Program study (GRASP)

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    This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time

    Elective amputation and bionic substitution restore functional hand use after critical soft tissue injuries

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    Critical soft tissue injuries may lead to a non-functional and insensate limb. In these cases standard reconstructive techniques will not suffice to provide a useful outcome, and solutions outside the biological arena must be considered and offered to these patients. We propose a concept which, after all reconstructive options have been exhausted, involves an elective amputation along with a bionic substitution, implementing an actuated prosthetic hand via a structured tech-neuro-rehabilitation program. Here, three patients are presented in whom this concept has been successfully applied after mutilating hand injuries. Clinical tests conducted before, during and after the procedure, evaluating both functional and psychometric parameters, document the benefits of this approach. Additionally, in one of the patients, we show the possibility of implementing a highly functional and natural control of an advanced prosthesis providing both proportional and simultaneous movements of the wrist and hand for completing tasks of daily living with substantially less compensatory movements compared to the traditional systems. It is concluded that the proposed procedure is a viable solution for re-gaining highly functional hand use following critical soft tissue injuries when existing surgical measures fail. Our results are clinically applicable and can be extended to institutions with similar resources

    Assessment of Hand Gestures Using Wearable Sensors and Fuzzy Logic

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    Hand dexterity and motor control are critical in our everyday lives because a significant portion of the daily motions we perform are with our hands and require some degree of repetition and skill. Therefore, development of technologies for hand and extremity rehabilitation is a significant area of research that will directly help patients recovering from hand debilities sustained from causes ranging from stroke and Parkinson’s disease to trauma and common injuries. Cyclic activity recognition and assessment is appropriate for hand and extremity rehabilitation because a majority of our essential motions are cyclic in their nature. For a patient on the road to regaining functional independence with daily skills, the improvement in cyclic motions constitutes an important and quantifiable rehabilitation goal. However, challenges exist with hand rehabilitation sensor technologies preventing acquisition of long-term, continuous, accurate and actionable motion data. These challenges include complicated and uncomfortable system assemblies, and a lack of integration with consumer electronics for easy readout. In our research, we have developed a glove based system where the inertial measurement unit (IMU) sensors are used synergistically with the flexible sensors to minimize the number of IMU sensors. The classification capability of our system is improved by utilizing a fuzzy logic data analysis algorithm. We tested a total of 25 different subjects using a glove-based apparatus to gather data on two-dimensional motions with one accelerometer and three-dimensional motions with one accelerometer and two flexible sensors. Our research provides an approach that has the potential to utilize both activity recognition and activity assessment using simple sensor systems to help patients recover and improve their overall quality of life

    Get a Grip:Evaluating Grip Gestures for VR Input Using a Lightweight Pen

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    The use of Virtual Reality (VR) in applications such as data analysis, artistic creation, and clinical settings requires high precision input. However, the current design of handheld controllers, where wrist rotation is the primary input approach, does not exploit the human fingers' capability for dexterous movements for high precision pointing and selection. To address this issue, we investigated the characteristics and potential of using a pen as a VR input device. We conducted two studies. The first examined which pen grip allowed the largest range of motion---we found a tripod grip at the rear end of the shaft met this criterion. The second study investigated target selection via 'poking' and ray-casting, where we found the pen grip outperformed the traditional wrist-based input in both cases. Finally, we demonstrate potential applications enabled by VR pen input and grip postures

    On neuromechanical approaches for the study of biological and robotic grasp and manipulation

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    abstract: Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.The electronic version of this article is the complete one and can be found online at: https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-017-0305-
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