OBJECTIVE: To develop a deep convolutional neural network (CNN) to automatically segment an axial CT image of the pelvis for body composition measures. We hypothesized that a deep CNN approach would achieve high accuracy when compared to manual segme...
Journal of visualized experiments : JoVE
Jul 1, 2019
Mapping the motor cortex with transcranial magnetic stimulation (TMS) has potential to interrogate motor cortex physiology and plasticity but carries unique challenges in children. Similarly, transcranial direct current stimulation (tDCS) can improve...
IEEE transactions on biomedical circuits and systems
Jun 27, 2019
An accurate description of muscular activity plays an important role in the clinical diagnosis and rehabilitation research. The electromyography (EMG) is the most used technique to make accurate descriptions of muscular activity. The EMG is associate...
Automatic skeletal muscle image segmentation (MIS) is crucial in the diagnosis of muscle-related diseases. However, accurate methods often suffer from expensive computations, which are not scalable to large-scale, whole-slide muscle images. In this p...
Muscle fat infiltration (MFI) of the deep cervical spine extensors has been observed in cervical spine conditions using time-consuming and rater-dependent manual techniques. Deep learning convolutional neural network (CNN) models have demonstrated st...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
May 20, 2019
OBJECTIVE: To compare the effects of active assisted wrist extension training, using a robotic exoskeleton (RW), with simultaneous 5 Hz (rTMS + RW) or Sham rTMS (Sham rTMS + RW) over the ipsilesional extensor carpi radialis motor cortical representat...
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Apr 1, 2019
OBJECTIVES: The purpose of this study was to develop an automatic tracking method for the muscle cross-sectional area (CSA) on ultrasound (US) images using a convolutional neural network (CNN). The performance of the proposed method was evaluated and...
Neuromuscular impairment associated with cerebral palsy (CP) often leads to life-long walking deficits. Our goal was to evaluate the ability of a novel untethered wearable ankle exoskeleton to reduce the severity of gait pathology from CP. In this cl...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Feb 23, 2019
OBJECTIVE: Given the recent advent in machine learning and artificial intelligence on medical data analysis, we hypothesized that the deep learning algorithm can classify resting needle electromyography (n-EMG) discharges.
The muscles of the lower limbs directly influence leg motion, therefore, lower limb muscle exercise is important for persons living with lower limb disabilities. This paper presents a medical assistive robot with leg exoskeletons for locomotion and l...