AIMC Topic: Stroke

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Effectiveness of combined robotics and virtual reality on lower limb functional ability in stroke survivors: A systematic review of randomized controlled trials.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Lower limb impairments are common consequences of stroke. Robotics and virtual reality (VR) play crucial roles in improving lower limb function post-stroke. This review aims to assess the effects of combined robot and VR interventions on lower limb f...

Deep learning-assisted detection and segmentation of intracranial hemorrhage in noncontrast computed tomography scans of acute stroke patients: a systematic review and meta-analysis.

International journal of surgery (London, England)
BACKGROUND: Deep learning (DL)-assisted detection and segmentation of intracranial hemorrhage stroke in noncontrast computed tomography (NCCT) scans are well-established, but evidence on this topic is lacking.

Effect of robot-assisted gait training on improving cardiopulmonary function in stroke patients: a meta-analysis.

Journal of neuroengineering and rehabilitation
OBJECTIVE: Understanding the characteristics related to cardiorespiratory fitness after stroke can provide reference values for patients in clinical rehabilitation exercise. This meta- analysis aimed to investigate the effect of robot-assisted gait t...

Task-Oriented Training by a Personalized Electromyography-Driven Soft Robotic Hand in Chronic Stroke: A Randomized Controlled Trial.

Neurorehabilitation and neural repair
BACKGROUND: Intensive task-oriented training has shown promise in enhancing distal motor function among patients with chronic stroke. A personalized electromyography (EMG)-driven soft robotic hand was developed to assist task-oriented object-manipula...

Mitigating Trunk Compensatory Movements in Post-Stroke Survivors through Visual Feedback during Robotic-Assisted Arm Reaching Exercises.

Sensors (Basel, Switzerland)
Trunk compensatory movements frequently manifest during robotic-assisted arm reaching exercises for upper limb rehabilitation following a stroke, potentially impeding functional recovery. These aberrant movements are prevalent among stroke survivors ...

Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Nature communications
Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to asse...

Predictive modelling and identification of key risk factors for stroke using machine learning.

Scientific reports
Strokes are a leading global cause of mortality, underscoring the need for early detection and prevention strategies. However, addressing hidden risk factors and achieving accurate prediction become particularly challenging in the presence of imbalan...

The independence of impairments in proprioception and visuomotor adaptation after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Proprioceptive impairments are common after stroke and are associated with worse motor recovery and poor rehabilitation outcomes. Motor learning may also be an important factor in motor recovery, and some evidence in healthy adults sugges...

Effects of Rehabilitation Robot Training on Physical Function, Functional Recovery, and Daily Living Activities in Patients with Sub-Acute Stroke.

Medicina (Kaunas, Lithuania)
Stroke often results in sensory deficits, muscular weakness, and diminished postural control, thereby restricting mobility and functional capabilities. It is important to promote neuroplasticity by implementing task-oriented exercises that induce cha...