AIMC Topic: Stroke

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Detection and Classification of Stroke Gaits by Deep Neural Networks Employing Inertial Measurement Units.

Sensors (Basel, Switzerland)
This paper develops Deep Neural Network (DNN) models that can recognize stroke gaits. Stroke patients usually suffer from partial disability and develop abnormal gaits that can vary widely and need targeted treatments. Evaluation of gait patterns is ...

Assessment of an Artificial Intelligence Algorithm for Detection of Intracranial Hemorrhage.

World neurosurgery
BACKGROUND: Immediate and accurate detection of intracranial hemorrhages (ICHs) is essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has the potential to provide this, but the assessment of these methods need...

A randomized controlled trial on the effects induced by robot-assisted and usual-care rehabilitation on upper limb muscle synergies in post-stroke subjects.

Scientific reports
Muscle synergies are hypothesized to reflect connections among motoneurons in the spinal cord activated by central commands and sensory feedback. Robotic rehabilitation of upper limb in post-stroke subjects has shown promising results in terms of imp...

Effects of Robotic Neurorehabilitation on Body Representation in Individuals with Stroke: A Preliminary Study Focusing on an EEG-Based Approach.

Brain topography
Patients with stroke can experience a drastic change in their body representation (BR), beyond the physical and psychological consequences of stroke itself. Noteworthy, the misperception of BR could affect patients' motor performance even more. Our s...

Epidemiological Surveillance of the Impact of the COVID-19 Pandemic on Stroke Care Using Artificial Intelligence.

Stroke
BACKGROUND AND PURPOSE: The degree to which the coronavirus disease 2019 (COVID-19) pandemic has affected systems of care, in particular, those for time-sensitive conditions such as stroke, remains poorly quantified. We sought to evaluate the impact ...

Motor Recovery: How Rehabilitation Techniques and Technologies Can Enhance Recovery and Neuroplasticity.

Seminars in neurology
There are now a large number of technological and methodological approaches to the rehabilitation of motor function after stroke. It is important to employ these approaches in a manner that is tailored to specific patient impairments and desired func...

Robot-Based Assessment of HIV-Related Motor and Cognitive Impairment for Neurorehabilitation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
There is a pressing need for strategies to slow or treat the progression of functional decline in people living with HIV. This paper explores a novel rehabilitation robotics approach to measuring cognitive and motor impairment in adults living with H...

The Influence of EMG-Triggered Robotic Movement on Walking, Muscle Force and Spasticity after an Ischemic Stroke.

Medicina (Kaunas, Lithuania)
: Application of the EMG-driven robotic training in everyday therapeutic processes is a modern and innovative form of neurorehabilitation among patients after stroke. Active participation of the patient contributes to significantly higher activation ...

Simulated muscle activity in locomotion: implications of co-occurrence between effort minimisation and gait modularity for robot-assisted rehabilitation therapy.

Computer methods in biomechanics and biomedical engineering
Evolution of gait rehabilitation robotic devices for stroke survivors has aimed at providing transparency to user's efforts and implementing 'assist-as-needed' paradigm. Alteration of muscle activity and synergies recruitment has been noticed in tria...

Systematic review of novel technology-based interventions for ischemic stroke.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
PURPOSE: To identify novel technologies pertinent to the prevention, diagnosis, treatment, and rehabilitation of ischemic stroke, and recommend the technologies that show the most promise in advancing ischemic stroke care.