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      Improving Fine Control of Grasping Force during Hand–Object Interactions for a Soft Synergy-Inspired Myoelectric Prosthetic Hand

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          Abstract

          The concept of postural synergies of the human hand has been shown to potentially reduce complexity in the neuromuscular control of grasping. By merging this concept with soft robotics approaches, a multi degrees of freedom soft-synergy prosthetic hand [SoftHand-Pro (SHP)] was created. The mechanical innovation of the SHP enables adaptive and robust functional grasps with simple and intuitive myoelectric control from only two surface electromyogram (sEMG) channels. However, the current myoelectric controller has very limited capability for fine control of grasp forces. We addressed this challenge by designing a hybrid-gain myoelectric controller that switches control gains based on the sensorimotor state of the SHP. This controller was tested against a conventional single-gain (SG) controller, as well as against native hand in able-bodied subjects. We used the following tasks to evaluate the performance of grasp force control: (1) pick and place objects with different size, weight, and fragility levels using power or precision grasp and (2) squeezing objects with different stiffness. Sensory feedback of the grasp forces was provided to the user through a non-invasive, mechanotactile haptic feedback device mounted on the upper arm. We demonstrated that the novel hybrid controller enabled superior task completion speed and fine force control over SG controller in object pick-and-place tasks. We also found that the performance of the hybrid controller qualitatively agrees with the performance of native human hands.

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          Most cited references39

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          Restoring natural sensory feedback in real-time bidirectional hand prostheses.

          Hand loss is a highly disabling event that markedly affects the quality of life. To achieve a close to natural replacement for the lost hand, the user should be provided with the rich sensations that we naturally perceive when grasping or manipulating an object. Ideal bidirectional hand prostheses should involve both a reliable decoding of the user's intentions and the delivery of nearly "natural" sensory feedback through remnant afferent pathways, simultaneously and in real time. However, current hand prostheses fail to achieve these requirements, particularly because they lack any sensory feedback. We show that by stimulating the median and ulnar nerve fascicles using transversal multichannel intrafascicular electrodes, according to the information provided by the artificial sensors from a hand prosthesis, physiologically appropriate (near-natural) sensory information can be provided to an amputee during the real-time decoding of different grasping tasks to control a dexterous hand prosthesis. This feedback enabled the participant to effectively modulate the grasping force of the prosthesis with no visual or auditory feedback. Three different force levels were distinguished and consistently used by the subject. The results also demonstrate that a high complexity of perception can be obtained, allowing the subject to identify the stiffness and shape of three different objects by exploiting different characteristics of the elicited sensations. This approach could improve the efficacy and "life-like" quality of hand prostheses, resulting in a keystone strategy for the near-natural replacement of missing hands.
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            Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects.

            To be successful, precision manipulation of small objects requires a refined coordination of forces excerted on the object by the tips of the fingers and thumb. The present paper deals quantitatively with the regulation of the coordination between the grip force and the vertical lifting force, denoted as the load force, while small objects were lifted, positioned in space and replaced by human subjects using the pinch grip. It was shown that the grip force changed in parallel with the load force generated by the subject to overcome various forces counteracting the intended manipulation. The balance between the two forces was adapted to the friction between the skin and the object providing a relatively small safety margin to prevent slips, i.e. the more slippery the object the higher the grip force at any given load force. Experiments with local anaesthesia indicated that this adaptation was dependent on cutaneous afferent input. Afferent information related to the frictional condition could influence the force coordination already about 0.1 s after the object was initially gripped, i.e. approximately at the time the grip and load forces began to increase in parallel. Further, "secondary", adjustments of the force balance could occur later in response to small short-lasting slips, revealed as vibrations in the object. The new force balance following slips was maintained, indicating that the relationship between the two forces was set on the basis of a memory trace. Its updating was most likely accounted for by tactile afferent information entering intermittently at inappropriate force coordination, e.g. as during slips. The latencies between the onset of such slips and the appearance of the adjustments (0.06-0.08 s) clearly indicated that the underlying neural mechanisms operated highly automatically.
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              Sensory feedback in upper limb prosthetics.

              One of the challenges facing prosthetic designers and engineers is to restore the missing sensory function inherit to hand amputation. Several different techniques can be employed to provide amputees with sensory feedback: sensory substitution methods where the recorded stimulus is not only transferred to the amputee, but also translated to a different modality (modality-matched feedback), which transfers the stimulus without translation and direct neural stimulation, which interacts directly with peripheral afferent nerves. This paper presents an overview of the principal works and devices employed to provide upper limb amputees with sensory feedback. The focus is on sensory substitution and modality matched feedback; the principal features, advantages and disadvantages of the different methods are presented.
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                Author and article information

                Contributors
                Journal
                Front Neurorobot
                Front Neurorobot
                Front. Neurorobot.
                Frontiers in Neurorobotics
                Frontiers Media S.A.
                1662-5218
                10 January 2018
                2017
                : 11
                : 71
                Affiliations
                [1] 1Neural Control of Movement Laboratory, School of Biological and Health Systems Engineering, Arizona State University , Tempe, AZ, United States
                [2] 2Mechanical and Aerospace Engineering, University of Central Florida , Orlando, FL, United States
                Author notes

                Edited by: Keum-Shik Hong, Pusan National University, South Korea

                Reviewed by: Kyujin Cho, Seoul National University, South Korea; Lorenzo Masia, Nanyang Technological University, Singapore

                *Correspondence: Qiushi Fu, qiushi.fu@ 123456ucf.edu
                Article
                10.3389/fnbot.2017.00071
                5767584
                29375360
                fc133d23-4b97-42e0-9764-773489d15ea4
                Copyright © 2018 Fu and Santello.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 31 October 2017
                : 18 December 2017
                Page count
                Figures: 9, Tables: 3, Equations: 0, References: 49, Pages: 15, Words: 10919
                Funding
                Funded by: Defense Advanced Research Projects Agency 10.13039/100000185
                Award ID: W911NF-17-1-0049
                Categories
                Neuroscience
                Original Research

                Robotics
                neuroprosthetics,hand function assessment,object manipulation,grasping,haptic feedback,force control

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