Prosthetic Control
Prosthetic Control - Related Videos
06:58
A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
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Cited by 34 •
2015
As prosthetic development moves towards the goal of natural control, harnessing amputees’ inherent ability to learn new motor skills may enable proficiency. This manuscript describes a structured rehabilitation protocol, which includes imitation, repetition, and reinforcement learning strategies, for improved multifunctional prosthetic control.
08:04
Customizing a Cryolite Glass Prosthetic Eye
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Cited by 12 •
2019
This manuscript shows each step of customizing a cryolite glass prosthetic eye including some major advantages of the use of cryolite glass for manufacturing an eye prosthesis compared to poly(methyl methacrylate). In addition, this manuscript gives ophthalmologists better insight into the ocularistic care that could improve interprofessional collaboration.
11:16
Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis
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Cited by 15 •
2014
Neural-machine interfaces (NMI) have been developed to identify the user's locomotion mode. These NMIs are potentially useful for neural control of powered artificial legs, but have not been fully demonstrated. This paper presented (1) our designed engineering platform for easy implementation and development of neural control for powered lower limb prostheses and (2) an experimental setup and protocol in a laboratory environment to evaluate neurally-controlled artificial legs on patients with...
07:23
An Optimized Protocol for the Efficient Radiolabeling of Gold Nanoparticles by Using a 125I-labeled Azide Prosthetic Group
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Cited by 5 •
2016
A detailed procedure for the synthesis of a 125I-labeled azide and the radiolabeling of dibenzocyclooctyne (DBCO)-group-conjugated, 13-nm-sized gold nanoparticles using a copper-free click reaction is described.
01:21
Control System Problem
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2024
In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function. When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...
FAQs
The control pathway links signal detection, computation, and actuation. Electrodes or other sensors capture biological activity, embedded algorithms interpret the resulting signals, and the system converts that interpretation into commands for motors, joints, or other actuators. This sequence allows intended actions such as grasping, walking, or position adjustment to be expressed through coordinated artificial-limb movement.
Residual-muscle electromyography, or EMG, provides a way to detect activity that reflects a user’s intended movement. Electrodes measure this activity after limb loss, and computational systems use the signal as an input for control decisions. Because the signal originates from the user’s biological system, it can support more purposeful interaction with the prosthesis.
Sensory feedback can give users information about the state or response of an artificial limb while they operate it. This added information may support user awareness and help connect intended actions with observed prosthetic behavior. In bioengineering, combining command generation with feedback is important because effective control concerns not only producing movement, but also supporting the user’s interaction with it.
A typical operation sequence begins when sensors detect biological signals, such as residual-muscle activity. Computational algorithms then interpret those inputs and translate them into commands. Motors, joints, or other actuators carry out the requested movement, while sensory feedback may provide additional information to the user. Together, these stages connect biological intention with artificial-limb function.
Depending on the system and artificial limb, prosthetic control can support actions including grasping, walking, and position adjustment. These examples span upper- and lower-limb functions and show how control systems can direct different mechanical outputs. The practical goal is to help users perform purposeful actions that contribute to independence and participation in everyday activities.
Current research seeks interfaces that respond more naturally, work reliably, and adapt to changing control needs. Progress in these areas could reduce the cognitive effort required to operate an artificial limb while improving purposeful movement. In bioengineering, this work also advances rehabilitation, assistive technology, and broader human-machine integration by strengthening the connection between biological intent and prosthetic function.