Survey report on neural-machine interface for multifunctional upper limb prostheses
نویسندگان
چکیده
منابع مشابه
Neural machine interfaces for controlling multifunctional powered upper-limb prostheses.
This article investigates various neural machine interfaces for voluntary control of externally powered upper-limb prostheses. Epidemiology of upper limb amputation, as well as prescription and follow-up studies of externally powered upper-limb prostheses are discussed. The use of electromyographic interfaces and peripheral nerve interfaces for prosthetic control, as well as brain machine inter...
متن کاملSensory feedback for upper limb prostheses.
In this chapter, we discuss the neurophysiological basis of how to provide sensory feedback to users with an upper limb prosthesis and discuss some of the theoretical issues that need to be considered when directly stimulating neurons in the somatosensory system. We focus on technologies that are currently available and discuss approaches that are most likely to succeed in providing natural per...
متن کاملExpert opinions on success factors for upper-limb prostheses.
The goal of this study was to gather the opinions of prosthetics experts on the most important factors for the successful use of upper-limb (UL) prostheses, compare them with those of prosthesis users, and ultimately direct research efforts in this field. UL prosthetics experts were asked to compare the importance of the comfort, function, and cosmesis of a prosthetic device for a transhumeral ...
متن کاملElectromyography Pattern-Recognition-Based Control of Powered Multifunctional Upper-Limb Prostheses
The human history has been accompanied by accidental trauma, war, and congenital anomalies. Consequently, amputation and deformity have been dealt with, one way or another, throughout the ages. More than one million individuals in the United States today are living with limb amputations (Adams et al., 1999), in which there are approximately 100,000 patients with an upper limb amputation. The wa...
متن کاملTarget Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses.
Despite high classification accuracies (~95%) of myoelectric control systems based on pattern recognition, how well offline measures translate to real-time closed-loop control is unclear. Recently, a real-time virtual test analyzed how well subjects completed arm motions using a multiple-degree of freedom (DOF) classifier. Although this test provided real-time performance metrics, the required ...
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ژورنال
عنوان ژورنال: Journal of Life Support Engineering
سال: 2006
ISSN: 1341-9455,1884-5827
DOI: 10.5136/lifesupport.18.supplement_159