Myoelectric Prosthesis
Myoelectric Prosthesis - Related Videos
08:08
Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
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Cited by 35 •
2014
Body segmental inertial properties are required for inverse dynamics modeling. Using an oscillation and reaction board technique, inertial properties of below-knee prostheses were measured. Using direct measures of prosthesis inertia in the inverse dynamics model of the prosthetic leg resulted in lower magnitudes of resultant joint forces and moments.
08:46
A Standardized Method for Measuring Internal Lung Surface Area via Mouse Pneumonectomy and Prosthesis Implantation
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Cited by 22 •
2017
Internal lung surface area (ISA) is a critical criterion for assessing lung morphology and physiology in lung diseases and injury-induced alveolar regeneration. We describe here a standardized method that can minimize the measurement bias for ISA in both lung pneumonectomy and prosthesis implantation mouse models.
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...
10:00
Techniques for Processing Eyes Implanted with a Retinal Prosthesis for Localized Histopathological Analysis: Part 2 Epiretinal Implants with Retinal Tacks
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Cited by 23 •
2015
Here we describe histological techniques for visualising ocular tissue directly adjacent to a metal epiretinal tack and retinal prosthesis.
12:01
Techniques for Processing Eyes Implanted With a Retinal Prosthesis for Localized Histopathological Analysis
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Cited by 13 •
2013
Techniques for visualizing retinal cytoarchitecture directly adjacent to individual electrodes within a retinal stimulator.
FAQs
Residual muscle contractions generate electromyographic signals that surface electrodes detect at the limb interface. The quality and consistency of those signals influence how reliably the controller distinguishes intended commands, such as movement associated with grasping or reaching. Stronger signal interpretation can support more precise motor responses, whereas inconsistent signals may reduce control effectiveness during routine activities.
A myoelectric prosthesis uses detected muscle activity and electrically driven motors rather than relying primarily on a body-powered harness. This changes how the user initiates movement and can reduce reliance on harness-based operation. The comparison is clinically relevant because the choice of control approach affects how users interact with the artificial limb during grasping, reaching, and daily tasks.
Improved sensors can capture residual muscle activity more effectively, giving the controller better information for translating contractions into movement commands. Machine learning is important because it can support more intuitive interpretation of changing electromyographic signals. Together, these advances are intended to improve control precision and may contribute to greater comfort and user acceptance.
Fitting determines how effectively the prosthesis and its surface electrodes work with the user’s residual limb and available muscle activity. Training helps the user produce signals that the controller can interpret for intended movements. Because both signal quality and user interaction affect performance, fitting and training are central to achieving dependable control rather than simply providing the hardware.
Evaluation should consider signal quality, the quality of the fitting, the user’s training, and how intuitive the control feels. These factors influence whether commands are translated into useful movement and whether the device remains practical for daily use. User acceptance is also an important outcome, because technical capability alone does not ensure that the prosthesis will be used successfully.
In medicine, these prostheses can support functional movements such as grasping and reaching, along with routine activities. The motors operate components of the prosthetic hand, arm, or other limb system in response to interpreted muscle signals. The practical outcome depends on control quality, but the intended role is to help restore useful function after limb loss.
Clinicians may consider this approach when externally powered movement could help a person perform useful tasks with less reliance on a body-powered harness. Its medical relevance lies in supporting functional recovery through grasping, reaching, and routine activities. Decisions should also account for fitting, signal quality, training demands, intuitive control, comfort, precision, and the user’s acceptance of the device.