Background: Assessing residual motor function in motor complete spinal cord injury (SCI) patients using surface electromyography (sEMG) is clinically important. Due to the prolonged loss of motor control and peripheral sensory input, patients may struggle to effectively activate residual motor function during sEMG assessments. The study proposes using virtual reality (VR) technology to enhance embodiment, motor imagery (MI), and memory, aiming to improve the activation of residual motor function and increase the sensitivity of sEMG assessments.
Methods: By Recruiting a sample of 12 patients with AIS A/B and capturing surface electromyographic signals before, druing and after VR training, RESULTS: Most patients showed significant electromyographic improvements in activation frequency and or 5-rank frequency during or after VR training. However, one patient with severe lower limb neuropathic pain did not exhibit volitional electromyographic activation, though their pain diminished during the VR training.
Conclusions: VR can enhance the activation of patients' residual motor function by improving body awareness and MI, thereby increasing the sensitivity of sEMG assessments.
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http://dx.doi.org/10.1186/s12984-025-01587-y | DOI Listing |
Cureus
February 2025
Department of Rehabilitation Medicine, Singapore General Hospital, Singapore, SGP.
Spinal cord injury (SCI) represents a significant medical challenge, leading to profound and often debilitating neurological deficits that adversely affect motor, sensory, and autonomic functions. Traditional rehabilitation strategies, while essential in the management of SCI, often exhibit limited efficacy in restoring lost functions, leaving many individuals with permanent disabilities. In this context, spinal cord stimulation (SCS) emerges as a novel and promising therapeutic approach with the potential to enhance neurological recovery by promoting neural plasticity and activating residual neural pathways.
View Article and Find Full Text PDFUnfallchirurgie (Heidelb)
March 2025
Medizinische Hochschule Hannover, Klinik für Unfallchirurgie, Carl-Neuberg-Straße 1, 30625, Hannover, Deutschland.
The agonist-antagonist myoneural interface (AMI) is an innovative approach to restoring proprioception and achieving more intuitive motor control following limb loss. This cutting-edge technique replicates the natural biomechanical relationship between agonist and antagonist muscles, enabling bidirectional communication between a prosthesis and the user's peripheral nervous system. Through the transposition of neurovascularly pedicled agonist-antagonist muscle pairs, which are reconnected via an adapted tendon suture and positioned within a gliding mechanism, AMI generates proprioceptive feedback during movement.
View Article and Find Full Text PDFJ Neuroeng Rehabil
March 2025
Beijing Children's Hospital, Capital Medical University, Beijing, 100045, China.
Background: Assessing residual motor function in motor complete spinal cord injury (SCI) patients using surface electromyography (sEMG) is clinically important. Due to the prolonged loss of motor control and peripheral sensory input, patients may struggle to effectively activate residual motor function during sEMG assessments. The study proposes using virtual reality (VR) technology to enhance embodiment, motor imagery (MI), and memory, aiming to improve the activation of residual motor function and increase the sensitivity of sEMG assessments.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
Although there are some studies on the automatic evaluation of impairment levels after stroke using machine learning (ML) models, few have delved into the predictive capabilities of raw motion data. In this study, we captured kinematic trajectories of the trunk and affected upper limb from 21 patients with chronic stroke when performing three reaching tasks. Employing ML models, we integrated the recorded trajectories to predict scores of the Fugl-Meyer Assessment of the Upper Extremity (FMA-UE) of stroke patients.
View Article and Find Full Text PDFNetwork
March 2025
Department of Computer Science and Engineering, St. Joseph's College of Engineering, Chennai, India.
PD is a progressive neurodegenerative disorder that leads to gradual motor impairments. Early detection is critical for slowing the disease's progression and providing patients access to timely therapies. However, accurately detecting PD in its early stages remains challenging.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!