AIMC Topic: Muscle, Skeletal

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The effect of the 2-UPS/RR ankle rehabilitation robot with coupling biomechanical model on muscle behaviors.

Medical & biological engineering & computing
With the popularization of biomechanical simulation technology, aiming at the rehabilitation of ankle joint injury, we imported simplified model of proposed 2-UPS/RR (two identical unconstraint kinematic branches with a universal-prismatic-spherical ...

Sarcopenia identified by computed tomography imaging using a deep learning-based segmentation approach impacts survival in patients with newly diagnosed multiple myeloma.

Cancer
BACKGROUND: Sarcopenia increases with age and is associated with poor survival outcomes in patients with cancer. By using a deep learning-based segmentation approach, clinical computed tomography (CT) images of the abdomen of patients with newly diag...

Smart Pneumatic Artificial Muscle Using a Bend Sensor like a Human Muscle with a Muscle Spindle.

Sensors (Basel, Switzerland)
Shortage of labor and increased work of young people are causing problems in terms of care and welfare of a growing proportion of elderly people. This is a looming social problem because people of advanced ages are increasing. Necessary in the fields...

Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation.

European radiology
OBJECTIVE: To investigate the utility of an automatic deep learning (DL) method for segmentation of T2 maps in patients with idiopathic inflammatory myopathy (IIM) against healthy controls, and also the association of quantitative T2 values in patien...

A Deep CNN Framework for Neural Drive Estimation From HD-EMG Across Contraction Intensities and Joint Angles.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
OBJECTIVE: Previous studies have demonstrated promising results in estimating the neural drive to muscles, the net output of all motoneurons that innervate the muscle, using high-density electromyography (HD-EMG) for the purpose of interfacing with a...

Biomechanical and Physiological Evaluation of Biologically-Inspired Hip Assistance With Belt-Type Soft Exosuits.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Hip-assisted soft exosuits have been reported for their effect on reducing the metabolic power of human walking. Currently, most studies focus on uni-directional assistance (HF: hip flexion, or HE: hip extension). This paper investigates the effect o...

Finger dexterity measured by the Grooved Pegboard test indexes Parkinson's motor severity in a tremor-independent manner.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
Fine motor impairments are frequent complaints in people with Parkinson's disease (PD). While they may develop at an early stage of the disease, they become more problematic as the disease progresses. Tremors and fine motor symptoms may seem related,...

DeepACSA: Automatic Segmentation of Cross-Sectional Area in Ultrasound Images of Lower Limb Muscles Using Deep Learning.

Medicine and science in sports and exercise
PURPOSE: Muscle anatomical cross-sectional area (ACSA) can be assessed using ultrasound and images are usually evaluated manually. Here, we present DeepACSA, a deep learning approach to automatically segment ACSA in panoramic ultrasound images of the...

3D-printed biomimetic artificial muscles using soft actuators that contract and elongate.

Science robotics
Biomimetic machines able to integrate with natural and social environments will find ubiquitous applications, from biodiversity conservation to elderly daily care. Although artificial actuators have reached the contraction performances of muscles, th...

A self-training teacher-student model with an automatic label grader for abdominal skeletal muscle segmentation.

Artificial intelligence in medicine
Deep learning on a limited number of labels/annotations is a challenging task for medical imaging analysis. In this paper, we propose a novel self-training segmentation pipeline (Self-Seg in short) for segmenting skeletal muscle in CT images. Self-Se...