Paper 11: The ‘Belgrade Hand Prosthesis’

Rakić, Mina

doi:10.1243/pime_conf_1968_183_179_02

Cited by 10 publications

(9 citation statements)

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“…Feedback to change system properties refers to the use of feedback as a part of a local loop within the artificial controller. Many designs within this category use feedback to enable shared control [e.g., artificial reflexes (Salisbury and Colman, 1967;Rakic, 1969;Ring and Welbourn, 1969;Kyberd and Chappell, 1994), computer vision based control (Markovic et al, 2014;Marković et al, 2015;Ghazaei et al, 2017)]. Considering the discussion in the section on agency, when these systems work less than perfectly, relinquishment of autonomy to an external agent might cause frustration by users.…”

Section: Other Applications Of Feedbackmentioning

confidence: 99%

A Review of Sensory Feedback in Upper-Limb Prostheses From the Perspective of Human Motor Control

2020

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This manuscript reviews historical and recent studies that focus on supplementary sensory feedback for use in upper limb prostheses. It shows that the inability of many studies to speak to the issue of meaningful performance improvements in real-life scenarios is caused by the complexity of the interactions of supplementary sensory feedback with other types of feedback along with other portions of the motor control process. To do this, the present manuscript frames the question of supplementary feedback from the perspective of computational motor control, providing a brief review of the main advances in that field over the last 20 years. It then separates the studies on the closed-loop prosthesis control into distinct categories, which are defined by relating the impact of feedback to the relevant components of the motor control framework, and reviews the work that has been done over the last 50+ years in each of those categories. It ends with a discussion of the studies, along with suggestions for experimental construction and connections with other areas of research, such as machine learning.

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Section: Other Applications Of Feedbackmentioning

confidence: 99%

A Review of Sensory Feedback in Upper-Limb Prostheses From the Perspective of Human Motor Control

2020

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“…While load-controlled friction is very useful for grasping objects, it has two drawbacks: the squeezing normal force can crush delicate or deformable objects, and the normal force tends to push objects out of the grasp in the case where the gripper cannot reach at least halfway around the object. Examples of such grippers are numerous, including rigid and fully actuated ones [2]- [4], as well as more compliant, underactuated and back drivable grippers [5]- [7]. Extensive reviews are provided in [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Grasping Without Squeezing: Design and Modeling of Shear-Activated Grippers

et al. 2018

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Abstract-Grasping objects that are too large to envelop is traditionally achieved using friction that is activated by squeezing. We present a family of shear-activated grippers that can grasp such objects without the need to squeeze. When a shear force is applied to the gecko-inspired material in our grippers, adhesion is turned on; this adhesion in turn results in adhesion-controlled friction, a friction force that depends on adhesion rather than a squeezing normal force. Removal of the shear force eliminates adhesion, allowing easy release of an object. A compliant shearactivated gripper without active sensing and control can use the same light touch to lift objects that are soft, brittle, fragile, light, or very heavy. We present three grippers, the first two designed for curved objects, and the third for nearly any shape. Simple models describe the grasping process, and empirical results verify the models. The grippers are demonstrated on objects with a variety of shapes, materials, sizes, and weights.

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“…The overall behavior of an EDFS controller is therefore a function of the structure and interconnectedness of the states, the device behavior within each state, and the events and conditions required to transition among states (all of which are interdependent). This approach was initially developed and applied to myoelectric prosthetic hand control in the 1960s ([20], [21]), followed by the more recent work described in [22]–[27]. In [22]–[24], EDFS control approaches were used to modulate grasp within a preselected hand posture based on measured EMG amplitudes.…”

Section: Introductionmentioning

confidence: 99%

A Method for the Control of Multigrasp Myoelectric Prosthetic Hands

Dalley

Varol

Goldfarb

2012

IEEE Trans. Neural Syst. Rehabil. Eng.

107

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This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation.

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Paper 11: The ‘Belgrade Hand Prosthesis’

Cited by 10 publications

References 0 publications

A Review of Sensory Feedback in Upper-Limb Prostheses From the Perspective of Human Motor Control

A Review of Sensory Feedback in Upper-Limb Prostheses From the Perspective of Human Motor Control

Grasping Without Squeezing: Design and Modeling of Shear-Activated Grippers

A Method for the Control of Multigrasp Myoelectric Prosthetic Hands

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