AI Medical Compendium Topic

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Muscle, Skeletal

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Distinguishing the activity of flexor digitorum brevis and soleus across standing postures with deep learning models.

Gait & posture
BACKGROUND: Electromyographic (EMG) recordings indicate that both the flexor digitorum brevis and soleus muscles contribute significantly to the control of standing balance, However, less is known about the adjustments in EMG activity of these two mu...

Gene ontology defines pre-post- hatch energy dynamics in the complexus muscle of broiler chickens.

BMC genomics
BACKGROUND: Chicken embryos emerge from their shell by the piercing movement of the hatching muscle. Although considered a key player during hatching, with activity that imposes a substantial metabolic demand, data are still limited. The study provid...

Genetic algorithm-based optimal design for fluidic artificial muscle (FAM) bundles.

Bioinspiration & biomimetics
In this paper, we present a design optimization framework for a fluidic artificial muscle (FAM) bundle subject to geometric constraints. The architecture of natural skeletal muscles allows for compact actuation packaging by distributing a substantial...

Learning a Hand Model From Dynamic Movements Using High-Density EMG and Convolutional Neural Networks.

IEEE transactions on bio-medical engineering
OBJECTIVE: Surface electromyography (sEMG) can sense the motor commands transmitted to the muscles. This work presents a deep learning method that can decode the electrophysiological activity of the forearm muscles into the movements of the human han...

Analyzing immune cell infiltrates in skeletal muscle of infantile-onset Pompe disease using bioinformatics and machine learning.

Scientific reports
Pompe disease, a severe lysosomal storage disorder, is marked by heart problems, muscle weakness, and respiratory difficulties. This study aimed to identify novel markers for infantile-onset Pompe disease by analyzing key genes and immune cells infil...

Enhancing postural stability in musculoskeletal quadrupedal locomotion through tension feedback for CPG-based controller.

Bioinspiration & biomimetics
A central pattern generator (CPG)-based controller enhances the adaptability of quadrupedal locomotion, for example, by controlling the trunk posture. The conventional CPG-based controllers with attitude control often utilized the posture angle as fe...

Artificial intelligence-based analysis of lower limb muscle mass and fatty degeneration in patients with knee osteoarthritis and its correlation with Knee Society Score.

International journal of computer assisted radiology and surgery
PURPOSE: Lower-limb muscle mass reduction and fatty degeneration develop in patients with knee osteoarthritis (KOA) and could affect their symptoms, satisfaction, expectation and functional activities. The Knee Society Scoring System (KSS) includes p...

Comparison of Manual vs Artificial Intelligence-Based Muscle MRI Segmentation for Evaluating Disease Progression in Patients With CMT1A.

Neurology
BACKGROUND AND OBJECTIVES: Intramuscular fat fraction (FF), assessed with quantitative MRI (qMRI), has emerged as one of the few responsive outcome measures in CMT1A patients. The main limitation for its use in future therapeutic trials is the time r...

Identification of Spared and Proportionally Controllable Hand Motor Dimensions in Motor Complete Spinal Cord Injuries Using Latent Manifold Analysis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The loss of bilateral hand function is a debilitating challenge for millions of individuals that suffered a motor-complete spinal cord injury (SCI). We have recently demonstrated in eight tetraplegic individuals the presence of highly functional spar...

From Simulation to Reality: Predicting Torque With Fatigue Onset via Transfer Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Muscle fatigue impacts upper extremity function but is often overlooked in biomechanical models. The present work leveraged a transfer learning approach to improve torque predictions during fatiguing upper extremity movements. We developed two artifi...