AIMC Topic: Prosthesis Design

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Deep Learning-based Thigh Muscle Investigation Using MRI For Prosthetic Development for Patients Undergoing Total Knee Replacement (TKR).

Current medical imaging
BACKGROUND: A prosthetic device is designed based on the quantitative analysis of muscle MRI which will improve the muscle control achieved with functional electrical stimulation/ guided robotic exoskeletons. Electromyography (EMG) provides muscle fu...

Comparative study of the glistening between four intraocular lens models assessed by OCT and deep learning.

Journal of cataract and refractive surgery
PURPOSE: To evaluate the glistening in 4 different models of intraocular lenses (IOLs) using optical coherence tomography (OCT) and deep learning (DL).

A Paediatric 3D-Printed Soft Robotic Hand Prosthesis for Children with Upper Limb Loss.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Designing prosthetic hands for children is challenging due to the limited space for electronics and the need of reducing the cost to cater for the constant growth of their hand. In this paper, we proposed an anthropomorphic hand prosthesis for childr...

Self-Contained Neuromusculoskeletal Arm Prostheses.

The New England journal of medicine
We report the use of a bone-anchored, self-contained robotic arm with both sensory and motor components over 3 to 7 years in four patients after transhumeral amputation. The implant allowed for bidirectional communication between a prosthetic hand an...

Robotic prosthesis that maintains flexion posture.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The number of lower limb amputations in Japan has recently been increasing. Lower limb amputation is classified based on the amputated part,and its two main types are below-knee (28.4%) and above-knee (58.8%). Especially for patients with above-knee ...

Obstacle Recognition using Computer Vision and Convolutional Neural Networks for Powered Prosthetic Leg Applications.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this work we combine computer vision and a machine learning algorithm, Convolutional Neural Networks (CNNs), to identify obstacles that powered prosthetic leg users might encounter during walking. Our motivation is that powered prosthetic legs cou...

A Control Architecture for Grasp Strength Regulation in Myocontrolled Robotic Hands Using Vibrotactile Feedback: Preliminary Results.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Nowadays, electric-powered hand prostheses do not provide adequate sensory instrumentation and artificial feedback to allow users voluntarily and finely modulate the grasp strength applied to the objects. In this work, the design of a control archite...

Exploring the Impact of Machine-Learned Predictions on Feedback from an Artificial Limb.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Learning to get by without an arm or hand can be very challenging, and existing prostheses do not yet fill the needs of individuals with amputations. One promising solution is to improve the feedback from the device to the user. Towards this end, we ...