AIMC Topic: Prosthesis Design

Clear Filters Showing 51 to 60 of 161 articles

Computer Vision-Based Grasp Pattern Recognition With Application to Myoelectric Control of Dexterous Hand Prosthesis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To achieve suitable grasps over various objects, a novel computer vision-based classification method assorting objects into different grasp patterns is propose...

Soft robotic in the construction of prosthetic heart valve: a novel approach.

Journal of medical engineering & technology
In this study, we describe the design, fabrication and computational testing of a new prosthetic device for aortic valve replacement. The device is an active stent composed of a silicone rubber during initial prototyping, with adaptation towards a hy...

Detecting total hip replacement prosthesis design on plain radiographs using deep convolutional neural network.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Identifying the design of a failed implant is a key step in the preoperative planning of revision total joint arthroplasty. Manual identification of the implant design from radiographic images is time-consuming and prone to error. Failure to identify...

The Interaction Between Feedback Type and Learning in Routine Grasping With Myoelectric Prostheses.

IEEE transactions on haptics
While prosthetic fitting after upper-limb loss allows for restoration of motor functions, it deprives the amputee of tactile sensations that are essential for grasp control in able-bodied subjects. Therefore, it is commonly assumed that restoring the...

A Deep Learning Framework for Design and Analysis of Surgical Bioprosthetic Heart Valves.

Scientific reports
Bioprosthetic heart valves (BHVs) are commonly used as heart valve replacements but they are prone to fatigue failure; estimating their remaining life directly from medical images is difficult. Analyzing the valve performance can provide better guida...

Design and Speed-Adaptive Control of a Powered Geared Five-Bar Prosthetic Knee Using BP Neural Network Gait Recognition.

Sensors (Basel, Switzerland)
To improve the multi-speed adaptability of the powered prosthetic knee, this paper presented a speed-adaptive neural network control based on a powered geared five-bar (GFB) prosthetic knee. The GFB prosthetic knee is actuated via a cylindrical cam-b...

What microsurgeon, orthopaedic and plastic surgeon should know about bionic hand.

Injury
Hand loss is a catastrophic event that generates significant demands for orthopedics and prosthetics. In the course of history, prostheses evolved from passive esthetic replacements to sophisticated robotic hands. Yet, their actuation and particularl...

Deep Learning in Personalization of Cardiovascular Stents.

Journal of cardiovascular pharmacology and therapeutics
Deep learning (DL) application has demonstrated its enormous potential in accomplishing biomedical tasks, such as vessel segmentation, brain visualization, and speech recognition. This review article has mainly covered recent advances in the principl...

Deep Learning for Automated Classification of Inferior Vena Cava Filter Types on Radiographs.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To demonstrate the feasibility and evaluate the performance of a deep-learning convolutional neural network (CNN) classification model for automated identification of different types of inferior vena cava (IVC) filters on radiographs.