AIMC Topic: Thigh

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Unsupervised Machine Learning in Countermovement Jump and Isometric Mid-Thigh Pull Performance Produces Distinct Combat and Physical Fitness Clusters in Male and Female U.S. Marine Corps Recruits.

Military medicine
INTRODUCTION: Several challenges face the U.S. Marine Corps (USMC) and other services in their efforts to design recruit training to augment warfighter mobility and resilience in both male and female recruits as part of an integrated model. Strength ...

Improvements of mid-thigh circumferences following robotic rehabilitation in hemiparetic stroke patients.

Physiotherapy research international : the journal for researchers and clinicians in physical therapy
INTRODUCTION: Stroke has emerged as the leading cause of disability globally. The provision of long-term rehabilitation to stroke survivors poses a health care burden to many countries. Robotic devices have created a major turning point in stroke reh...

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...

Locate the Superficial Femoral Artery with Occlusion by Deep Neural Network Correcting Interpolation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In clinical practice, doctors usually use computed tomography angiography (CTA) to examine lower extremity atherosclerotic occlusive (ASO). Conveniently and accurately locating occlusive superficial femoral artery (SFA) which is difficult to extract ...

A Dual-Accelerometer System for Classifying Physical Activity in Children and Adults.

Medicine and science in sports and exercise
INTRODUCTION: Accurately monitoring 24-h movement behaviors is a vital step for progressing the time-use epidemiology field. Past accelerometer-based measurement protocols are either hindered by lack of wear time compliance, or the inability to accur...

Improving Hip-Worn Accelerometer Estimates of Sitting Using Machine Learning Methods.

Medicine and science in sports and exercise
PURPOSE: This study aimed to improve estimates of sitting time from hip-worn accelerometers used in large cohort studies by using machine learning methods developed on free-living activPAL data.