AIMC Topic: Prosthesis Design

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CyberLimb: a novel robotic prosthesis concept with shared and intuitive control.

Journal of neuroengineering and rehabilitation
BACKGROUND: Existing assistive technologies attempt to mimic biological functions through advanced mechatronic designs. In some occasions, the information processing demands for such systems require substantial information bandwidth and convoluted co...

Three-dimensional deep learning to automatically generate cranial implant geometry.

Scientific reports
We present a 3D deep learning framework that can generate a complete cranial model using a defective one. The Boolean subtraction between these two models generates the geometry of the implant required for surgical reconstruction. There is little or ...

A decade retrospective of medical robotics research from 2010 to 2020.

Science robotics
Robotics is a forward-looking discipline. Attention is focused on identifying the next grand challenges. In an applied field such as medical robotics, however, it is important to plan the future based on a clear understanding of what the research com...

Cutaneous Ionogel Mechanoreceptors for Soft Machines, Physiological Sensing, and Amputee Prostheses.

Advanced materials (Deerfield Beach, Fla.)
Touch sensing has a central role in robotic grasping and emerging human-machine interfaces for robot-assisted prosthetics. Although advancements in soft conductive polymers have promoted the creation of diverse pressure sensors, these sensors are dif...

Value of 3D preoperative planning for primary total hip arthroplasty based on artificial intelligence technology.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate preoperative planning is an important step for accurate reconstruction in total hip arthroplasty (THA). Presently, preoperative planning is completed using either a two-dimensional (2D) template or three-dimensional (3D) mimics s...

A deep learning application to approximate the geometric orifice and coaptation areas of the polymeric heart valves under time - varying transvalvular pressure.

Journal of the mechanical behavior of biomedical materials
Machine learning and deep learning frameworks have been presented as a substitute for lengthy computational analysis, such as finite element analysis, computational fluid dynamics, and fluid-structure interaction. In this study, our objective was to ...

Restoration of sensory information via bionic hands.

Nature biomedical engineering
Individuals who have lost the use of their hands because of amputation or spinal cord injury can use prosthetic hands to restore their independence. A dexterous prosthesis requires the acquisition of control signals that drive the movements of the ro...

Replicating dynamic humerus motion using an industrial robot.

PloS one
Transhumeral percutaneous osseointegrated prostheses provide upper-extremity amputees with increased range of motion, more natural movement patterns, and enhanced proprioception. However, direct skeletal attachment of the endoprosthesis elevates the ...

Customised Selection of the Haptic Design in C-Loop Intraocular Lenses Based on Deep Learning.

Annals of biomedical engineering
In order to increase the probability of having a successful cataract post-surgery, the customisation of the haptic design of the intraocular lens (IOL) according to the characteristics of the patient is recommended. In this study, we present two pred...

Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand.

Journal of neuroengineering and rehabilitation
BACKGROUND: State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently...