AIMC Topic: Spinal Cord Injuries

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A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal.

Sensors (Basel, Switzerland)
In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A...

Robot-assisted training with functional electrical stimulation enhances lower extremity function after spinal cord injury.

Artificial organs
INTRODUCTION: Functional electrical stimulation (FES) synchronized with robot-assisted lower extremity training is used in spinal cord injury (SCI) rehabilitation to promote residual function.

A Therapeutic Approach Using the Combined Application of Virtual Reality with Robotics for the Treatment of Patients with Spinal Cord Injury: A Systematic Review.

International journal of environmental research and public health
Spinal cord injury (SCI) has been associated with high mortality rates. Thanks to the multidisciplinary vision and approach of SCI, including the application of new technologies in the field of neurorehabilitation, people with SCI can survive and pro...

Soft robotics and functional electrical stimulation advances for restoring hand function in people with SCI: a narrative review, clinical guidelines and future directions.

Journal of neuroengineering and rehabilitation
BACKGROUND: Recovery of hand function is crucial for the independence of people with spinal cord injury (SCI). Wearable devices based on soft robotics (SR) or functional electrical stimulation (FES) have been employed to assist the recovery of hand f...

Soft Exoskeleton Mimics Human Cough for Assisting the Expectoration Capability of SCI Patients.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
UNLABELLED: This paper describes the design of a bionic soft exoskeleton and demonstrates its feasibility for assisting the expectoration function rehabilitation of patients with spinal cord injury (SCI).

Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome.

PloS one
Artificial intelligence and machine learning (AI/ML) is becoming increasingly more accessible to biomedical researchers with significant potential to transform biomedicine through optimization of highly-accurate predictive models and enabling better ...

Overground robotic training effects on walking and secondary health conditions in individuals with spinal cord injury: systematic review.

Journal of neuroengineering and rehabilitation
Overground powered lower limb exoskeletons (EXOs) have proven to be valid devices in gait rehabilitation in individuals with spinal cord injury (SCI). Although several articles have reported the effects of EXOs in these individuals, the few reviews a...

A deep learning-based toolbox for Automated Limb Motion Analysis (ALMA) in murine models of neurological disorders.

Communications biology
In neuroscience research, the refined analysis of rodent locomotion is complex and cumbersome, and access to the technique is limited because of the necessity for expensive equipment. In this study, we implemented a new deep learning-based open-sourc...

Real-time motion onset recognition for robot-assisted gait rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: Many patients with neurological movement disorders fear to fall while performing postural transitions without assistance, which prevents them from participating in daily life. To overcome this limitation, multi-directional Body Weight Sup...