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Muscles

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Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging-reporting and data system.

European radiology
OBJECTIVES: To compare the diagnostic performance of a novel deep learning (DL) method based on T2-weighted imaging with the vesical imaging-reporting and data system (VI-RADS) in predicting muscle invasion in bladder cancer (MIBC).

The Efficacy of Urinary Continence in Patients Undergoing Robot-Assisted Radical Prostatectomy with Bladder-Prostatic Muscle Reconstruction and Bladder Neck Eversion Anastomosis.

Medicina (Kaunas, Lithuania)
Background and Objectives: To evaluate the efficacy of bladder-prostatic muscle reconstruction and bladder neck eversion anastomosis in the recovery of urinary continence after robot-assisted radical prostatectomy (RARP). Materials and Methods: From ...

Insect-scale jumping robots enabled by a dynamic buckling cascade.

Proceedings of the National Academy of Sciences of the United States of America
Millions of years of evolution have allowed animals to develop unusual locomotion capabilities. A striking example is the legless-jumping of click beetles and trap-jaw ants, which jump more than 10 times their body length. Their delicate musculoskele...

Development of a Wearable Ultrasound Transducer for Sensing Muscle Activities in Assistive Robotics Applications.

Biosensors
Robotic prostheses and powered exoskeletons are novel assistive robotic devices for modern medicine. Muscle activity sensing plays an important role in controlling assistive robotics devices. Most devices measure the surface electromyography (sEMG) s...

On lightmyography based muscle-machine interfaces for the efficient decoding of human gestures and forces.

Scientific reports
Conventional muscle-machine interfaces like Electromyography (EMG), have significant drawbacks, such as crosstalk, a non-linear relationship between the signal and the corresponding motion, and increased signal processing requirements. In this work, ...

Toward a generalizable deep CNN for neural drive estimation across muscles and participants.

Journal of neural engineering
High-density electromyography (HD-EMG) decomposition algorithms are used to identify individual motor unit (MU) spike trains, which collectively constitute the neural code of movements, to predict motor intent. This approach has advanced from offline...

Muscular Damping Distribution Strategy for Bio-Inspired, Soft Motion Control at Variable Precision.

Sensors (Basel, Switzerland)
Bio-inspired and compliant control approaches have been studied by roboticists for decades to achieve more natural robot motion. Independent of this, medical and biological researchers have discovered a wide variety of muscular properties and higher-...

Predicting muscle invasion in bladder cancer based on MRI: A comparison of radiomics, and single-task and multi-task deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Radiomics and deep learning are two popular technologies used to develop computer-aided detection and diagnosis schemes for analysing medical images. This study aimed to compare the effectiveness of radiomics, single-task d...

Myoelectric Pattern Recognition Using Gramian Angular Field and Convolutional Neural Networks for Muscle-Computer Interface.

Sensors (Basel, Switzerland)
In the field of the muscle-computer interface, the most challenging task is extracting patterns from complex surface electromyography (sEMG) signals to improve the performance of myoelectric pattern recognition. To address this problem, a two-stage a...