AIMC Topic: Muscle, Skeletal

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An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from , Decreases HbA1c in a Prediabetic Population.

Nutrients
The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose l...

Development of the Ultralight Hybrid Pneumatic Artificial Muscle: Modelling and optimization.

PloS one
Pneumatic artificial muscles (PAMs) are one of the key technologies in soft robotics, and they enable actuation in mobile robots, in wearable devices and exoskeletons for assistive and rehabilitative purposes. While they recently showed relevant impr...

Inverse identification of hyperelastic constitutive parameters of skeletal muscles via optimization of AI techniques.

Computer methods in biomechanics and biomedical engineering
Studies on the deformation characteristics and stress distribution in loaded skeletal muscles are of increasing importance. Reliable prediction of hyperelastic material parameters requires an inverse process, which possesses challenges. This work pro...

Real-time optimization of an ellipsoidal trajectory orientation using muscle effort with Extremum Seeking Control.

Medical engineering & physics
We present an approach for real-time model-free optimization of the orientation of the elliptical trajectory. The performance is evaluated in simulation and experimental stages. Our model-free approach is based on the use of Extremum Seeking Control ...

Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients.

Sensors (Basel, Switzerland)
Manual segmentation of muscle and adipose compartments from computed tomography (CT) axial images is a potential bottleneck in early rapid detection and quantification of sarcopenia. A prototype deep learning neural network was trained on a multi-cen...

Robot-assisted rehabilitation of hand function after stroke: Development of prediction models for reference to therapy.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
BACKGROUND: Recovery of hand function after stroke represents the hardest target for clinicians. Robot-assisted therapy has been proved to be effective for hand recovery. Nevertheless, studies aimed to refer patients to the best therapy are missing.

Deep Learning for Robust Decomposition of High-Density Surface EMG Signals.

IEEE transactions on bio-medical engineering
Blind source separation (BSS) algorithms, such as gradient convolution kernel compensation (gCKC), can efficiently and accurately decompose high-density surface electromyography (HD-sEMG) signals into constituent motor unit (MU) action potential trai...

A deep learning model for diagnosing dystrophinopathies on thigh muscle MRI images.

BMC neurology
BACKGROUND: Dystrophinopathies are the most common type of inherited muscular diseases. Muscle biopsy and genetic tests are effective to diagnose the disease but cost much more than primary hospitals can reach. The more available muscle MRI is promis...

Recent progress in engineering functional biohybrid robots actuated by living cells.

Acta biomaterialia
Living cells are highly scalable biological actuators found in nature, and they are efficient technological solutions to actuate robotic systems. Recent advancements in biofabrication and tissue engineering have bridged the gap to interface muscle ce...

A Single-Shot Region-Adaptive Network for Myotendinous Junction Segmentation in Muscular Ultrasound Images.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Tracking the myotendinous junction (MTJ) in consecutive ultrasound images is crucial for understanding the mechanics and pathological conditions of the muscle-tendon unit. However, the lack of reliable and efficient identification of MTJ due to poor ...