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Neurological Rehabilitation

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A genetic algorithm-based method to modulate the difficulty of serious games along consecutive robot-assisted therapy sessions.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: One of the biggest challenges during neurorehabilitation therapies is finding an appropriate level of therapy intensity for each patient to ensure the recovery of movement of the affected limbs while maintaining motivation. ...

Robotic task specific training for upper limb neurorehabilitation: a mixed methods feasibility trial reporting achievable dose.

Disability and rehabilitation
PURPOSE: Robotic devices for upper-limb neurorehabilitation allow an increase in intensity of practice, often relying on video game-based training strategies with limited capacity to individualise training and integrate functional training. This stud...

Opportunities, Risks, Strengths and Weaknesses of Robotic Systems in Early Neurological Rehabilitation.

Studies in health technology and informatics
Given the conference's focus on innovative healthcare solutions, our investigation into robotic assistance systems highlights crucial advancements in early motor rehabilitation, aligning closely with emerging healthcare priorities. In combination wit...

Proprioception enhancement for robot assisted neural rehabilitation: a dynamic electrical stimulation based method and preliminary results from EEG analysis.

Journal of neural engineering
In recent years, the robot assisted (RA) rehabilitation training has been widely used to counteract defects of the manual one provided by physiotherapists. However, since the proprioception feedback provided by the robotic assistance or the manual me...

Effectiveness of robotic rehabilitation for gait and balance in people with multiple sclerosis: a systematic review.

Journal of neurology
This review investigated the effectiveness of robotic-assisted gait training (RAGT) in improving gait and balance performance in adults with multiple sclerosis (MS). Databases and registers were searched from inception to December 2023 to identify ra...

Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robot-Assisted Gait Rehabilitation (RAGR) is an established clinical practice to encourage neuroplasticity in patients with neuromotor disorders. Nevertheless, tasks repetition imposed by robots may induce boredom, affecting clinical outc...

Assessment of wearable robotics performance in patients with neurological conditions.

Current opinion in neurology
PURPOSE OF REVIEW: While wearable robotics is expanding within clinical settings, particularly for neurological rehabilitation, there is still a lack of consensus on how to effectively assess the performance of these devices. This review focuses on t...

A deep learning model for assistive decision-making during robot-aided rehabilitation therapies based on therapists' demonstrations.

Journal of neuroengineering and rehabilitation
BACKGROUND: A promising approach to improving motor recovery during rehabilitation is the use of robotic rehabilitation devices. These robotic devices provide tools to monitor the patient's recovery progress while providing highly standardized and in...

Neurorehabilitation in spinal cord injury: Increased cortical activity through tDCS and robotic gait training.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: This study investigates the neurophysiological outcomes of combining robot-assisted gait training (RAGT) with active transcranial direct current stimulation (tDCS) on individuals with spinal cord injury (SCI).

Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions.

Journal of neuroengineering and rehabilitation
Robotic technology is expected to transform rehabilitation settings, by providing precise, repetitive, and task-specific interventions, thereby potentially improving patients' clinical outcomes. Artificial intelligence (AI) and machine learning (ML) ...