AIMC Topic: Leg

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Deep learning methods for automatic segmentation of lower leg muscles and bones from MRI scans of children with and without cerebral palsy.

NMR in biomedicine
Cerebral palsy is a neurological condition that is known to affect muscle growth. Detailed investigations of muscle growth require segmentation of muscles from MRI scans, which is typically done manually. In this study, we evaluated the performance o...

Classification of Walking Environments Using Deep Learning Approach Based on Surface EMG Sensors Only.

Sensors (Basel, Switzerland)
Classification of terrain is a vital component in giving suitable control to a walking assistive device for the various walking conditions. Although surface electromyography (sEMG) signals have been combined with inputs from other sensors to detect w...

Deep learning-based photoplethysmography classification for peripheral arterial disease detection: a proof-of-concept study.

Physiological measurement
A proof-of-concept study to assess the potential of a deep learning (DL) based photoplethysmography PPG ('DLPPG') classification method to detect peripheral arterial disease (PAD) using toe PPG signals.PPG spectrogram images derived from our previous...

A Model-Based Analysis of Supraspinal Mechanisms of Inter-Leg Coordination in Human Gait: Toward Model-Informed Robot-Assisted Rehabilitation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Stroke survivors are often left suffering from gait instability due to hemiparesis. This gait dysfunction can lead to higher fall rates and an overall decrease in quality of life. Though there are many post-stroke gait rehabilitation methods in use c...

SSCA-Net: Simultaneous Self- and Channel-Attention Neural Network for Multiscale Structure-Preserving Vessel Segmentation.

BioMed research international
Vessel segmentation is a fundamental, yet not well-solved problem in medical image analysis, due to the complicated geometrical and topological structures of human vessels. Unlike existing rule- and conventional learning-based techniques, which hardl...

Fully automated 3D segmentation of MR-imaged calf muscle compartments: Neighborhood relationship enhanced fully convolutional network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automated segmentation of individual calf muscle compartments from 3D magnetic resonance (MR) images is essential for developing quantitative biomarkers for muscular disease progression and its prediction. Achieving clinically acceptable results is a...

Cleaning Up the MESS: Can Machine Learning Be Used to Predict Lower Extremity Amputation after Trauma-Associated Arterial Injury?

Journal of the American College of Surgeons
BACKGROUND: Thirty years after the Mangled Extremity Severity Score was developed, advances in vascular, trauma, and orthopaedic surgery have rendered the sensitivity of this score obsolete. A significant number of patients receive amputation during ...

Precision and accuracy of robot-assisted technology with simplified express femoral workflow in measuring leg length and offset in total hip arthroplasty.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Semi-active robot-assisted total hip arthroplasty (THA) has two options to measure the leg length discrepancy (LLD) and combined offset (CO), the 'enhanced' femoral workflow and the so-called 'express' simplified workflow. The purpose of ...

Pilot study: can machine learning analyses of movement discriminate between leg movements in sleep (LMS) with vs. without cortical arousals?

Sleep & breathing = Schlaf & Atmung
PURPOSE: Clinical and animal studies indicate frequent small micro-arousals (McA) fragment sleep leading to health complications. McA in humans is defined by changes in EEG and EMG during sleep. Complex EEG recordings during the night are usually req...

Robot-Driven Locomotor Perturbations Reveal Synergy-Mediated, Context-Dependent Feedforward and Feedback Mechanisms of Adaptation.

Scientific reports
Humans respond to mechanical perturbations that affect their gait by changing their motor control strategy. Previous work indicates that adaptation during gait is context dependent, and perturbations altering long-term stability are compensated for e...