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Shoulder

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Embedded Machine Learning System for Muscle Patterns Detection in a Patient with Shoulder Disarticulation.

Sensors (Basel, Switzerland)
The integration of artificial intelligence (AI) models in the classification of electromyographic (EMG) signals represents a significant advancement in the design of control systems for prostheses. This study explores the development of a portable sy...

A portable inflatable soft wearable robot to assist the shoulder during industrial work.

Science robotics
Repetitive overhead tasks during factory work can cause shoulder injuries resulting in impaired health and productivity loss. Soft wearable upper extremity robots have the potential to be effective injury prevention tools with minimal restrictions us...

Identification of ChatGPT-Generated Abstracts Within Shoulder and Elbow Surgery Poses a Challenge for Reviewers.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
PURPOSE: To evaluate the extent to which experienced reviewers can accurately discern between artificial intelligence (AI)-generated and original research abstracts published in the field of shoulder and elbow surgery and compare this with the perfor...

Can we screen opportunistically for low bone mineral density using CT scans of the shoulder and artificial intelligence?

The British journal of radiology
OBJECTIVE: To evaluate whether the CT attenuation of bones seen on shoulder CT scans could be used to predict low bone mineral density (BMD) (osteopenia/osteoporosis), and to compare the performance of two machine learning models to predict low BMD.

Editorial Commentary: Experts in Shoulder Surgery Do Not Consistently Detect Artificial Intelligence-Generated Scientific Abstracts.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
There has been exponential growth in the number of artificial intelligence (AI)- and machine learning (ML)-related publications in recent years. For example, in the field of shoulder and elbow surgery, there was a 6-fold increase in the number of pub...

Adaptive enhancement of shoulder x-ray images using tissue attenuation and type-II fuzzy sets.

PloS one
Shoulder X-ray images typically have low contrast and high noise levels, making it challenging to distinguish and identify subtle anatomical structures. While existing image enhancement techniques are effective in improving contrast, they often overl...

Sliding-Window CNN + Channel-Time Attention Transformer Network Trained with Inertial Measurement Units and Surface Electromyography Data for the Prediction of Muscle Activation and Motion Dynamics Leveraging IMU-Only Wearables for Home-Based Shoulder Rehabilitation.

Sensors (Basel, Switzerland)
Inertial Measurement Units (IMUs) are widely utilized in shoulder rehabilitation due to their portability and cost-effectiveness, but their reliance on spatial motion data restricts their use in comprehensive musculoskeletal analyses. To overcome thi...

Shoulder Musculoskeletal Disorder Rehabilitation Using a Robotic Device Based on Electromyography (EMG) Biofeedback: A Retrospective Cohort Study.

Medicina (Kaunas, Lithuania)
: While shoulder injuries represent the musculoskeletal disorders (MSDs) most encountered in physical therapy, there is no consensus on their management. In attempts to provide standardized and personalized treatment, a robotic-assisted device combin...

Deep Learning-Driven Abbreviated Shoulder MRI Protocols: Diagnostic Accuracy in Clinical Practice.

Tomography (Ann Arbor, Mich.)
BACKGROUND: Deep learning (DL) reconstruction techniques have shown promise in reducing MRI acquisition times while maintaining image quality. However, the impact of different acceleration factors on diagnostic accuracy in shoulder MRI remains unexpl...