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Spinal Cord Injuries

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Empowering High-Level Spinal Cord Injury Patients in Daily Tasks With a Hybrid Gaze and FEMG-Controlled Assistive Robotic System.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Individuals with high-level spinal cord injuries often face significant challenges in performing essential daily tasks due to their motor impairments. Consequently, the development of reliable, hands-free human-computer interfaces (HCI) for assistive...

Assessing the Effect of Cervical Transcutaneous Spinal Stimulation With an Upper Limb Robotic Exoskeleton and Surface Electromyography.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Transcutaneous spinal stimulation (TSS) is a promising rehabilitative intervention to restore motor function and coordination for individuals with spinal cord injury (SCI). The effects of TSS are most commonly assessed by evaluating muscle response t...

A Multimodal Assistive-Robotic-Arm Control System to Increase Independence After Tetraplegia.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Following tetraplegia, independence for completing essential daily tasks, such as opening doors and eating, significantly declines. Assistive robotic manipulators (ARMs) could restore independence, but typically input devices for these manipulators r...

Prediction of gait recovery using machine learning algorithms in patients with spinal cord injury.

Medicine
With advances in artificial intelligence, machine learning (ML) has been widely applied to predict functional outcomes in clinical medicine. However, there has been no attempt to predict walking ability after spinal cord injury (SCI) based on ML. In ...

Deep learning classification of EEG-based BCI monitoring of the attempted arm and hand movements.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: The primary objective of this research is to improve the average classification performance for specific movements in patients with cervical spinal cord injury (SCI).

Dynamic changes in pyroptosis following spinal cord injury and the identification of crucial molecular signatures through machine learning and single-cell sequencing.

Journal of pharmaceutical and biomedical analysis
The pathological cascade of spinal cord injury (SCI) is highly intricate. The onset of neuroinflammation can exacerbate the extent of damage. Pyroptosis is a form of inflammation-linked programmed cell death (PCD), the inhibition of pyroptosis can pa...

Kinematics-Based Predictions of External Loads during Handcycling.

Sensors (Basel, Switzerland)
The increased risk of cardiovascular disease in people with spinal cord injuries motivates work to identify exercise options that improve health outcomes without causing risk of musculoskeletal injury. Handcycling is an exercise mode that may be bene...

A deep learning approach for cervical cord injury severity determination through axial and sagittal magnetic resonance imaging segmentation and classification.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
STUDY DESIGN: Cross-sectional Database Study.

Data-driven prediction of spinal cord injury recovery: An exploration of current status and future perspectives.

Experimental neurology
Spinal Cord Injury (SCI) presents a significant challenge in rehabilitation medicine, with recovery outcomes varying widely among individuals. Machine learning (ML) is a promising approach to enhance the prediction of recovery trajectories, but its i...