Prosthesis Size Prediction
Prosthesis Size Prediction - Related Videos
08:08
Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
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Cited by 38 •
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 21 •
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...
10:50
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
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Cited by 2 •
2022
We summarize a workflow to computationally model a retinal neuron's behaviors in response to electrical stimulation. The computational model is versatile and includes automation steps that are useful in simulating a range of physiological scenarios and anticipating the outcomes of future in vivo/in vitro studies.
01:25
The Anchoring-and-Adjustment Heuristic
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2020
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000...
FAQs
The core comparison matches patient-specific anatomical measurements with the dimensions of available implant components. Medical imaging or direct clinical assessment supplies the geometry, allowing clinicians to identify the closest available fit rather than relying only on a generic size. This comparison supports a more individualized starting point for surgical planning.
Alignment and component coverage help determine whether a nominally appropriate dimension is clinically suitable. A component may correspond closely to measured anatomy yet provide less favorable alignment or coverage. Including these considerations makes the prediction more than a simple measurement match and helps clinicians recognize potential fit issues before surgery.
Prosthesis size prediction remains an estimate because available implant options may not reproduce patient anatomy exactly, and the operative situation can reveal information not captured beforehand. For that reason, a predicted size should guide preparation and selection, while surgical judgment and intraoperative findings determine the final choice.
A practical workflow begins with collecting anatomical measurements from imaging or clinical assessment. The measurements are then compared with the dimensions of available prosthesis sizes, followed by review of expected alignment and component coverage. Clinicians can use the resulting candidate size to prepare for surgery and flag cases likely to require additional sizing decisions.
Clinicians can apply the approach during preoperative planning when they need to anticipate implant selection and potential sizing challenges. It is especially relevant to personalized care because the comparison is based on the individual patient's geometry rather than a one-size-fits-all assumption. The result can make preparation more focused before entering the operating room.
The main practical benefit is improved readiness: teams can identify a likely implant size, organize the procedure around patient anatomy, and reduce unnecessary intraoperative trial-and-error. The method does not replace operative assessment, however. Final sizing remains dependent on surgical judgment and what clinicians observe during the procedure, preserving flexibility when the predicted fit is inadequate.