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The area of eXplainable Artificial Intelligence (XAI) has shown remarkable progress in the past few years, with the aim of enhancing the transparency and interpretability of the machine learning (ML) and deep learning (DL) models. This review paper ...

Stroke is a serious medical condition that can result in death as it causes a sudden loss of blood supply to large portions of brain. Given the rising prevalence of strokes, it is critical to understand the many factors that contribute to these ...

Recognizing the limitations of traditional therapy can be tedious and demotivating, we explore VR’s dynamic and immersive environment to potentially improve patient engagement and motivation. This approach promises accelerated recovery by ...

As populations age, people require solutions that afford self-management of health conditions, e.g. through virtual assistants (VAs). To design for underrepresented groups such as stroke survivors we need to understand their varying needs in the context ...

Using meteorological data, this study compares Machine Learning approaches such as K-Nearest Neighbors, Support Vector Machine, and Artificial Neural Networks for detecting days with a greater probability of stroke incidence in the region of ...

Objective: Based on the deep learning method, to construct the named entity recognition model of Ming and Qing dynasty stroke medical cases, to extract as comprehensive as possible the effective information in the Ming and Qing dynasty stroke medical ...

Vector graphics includes both filled and stroked paths as the main primitives. While there are many techniques for rendering filled paths on GPU, stroked paths have proved more elusive. This paper presents a technique for performing stroke expansion, ...

Stroke stands as a major global health issue, causing high death and disability rates and significant social and economic burdens. The effectiveness of existing stroke risk assessment methods is questionable due to their use of inconsistent and ...

• Introduced a deep learning system using retinal biomarkers to predict stroke risk.
• Outperformed studies and benchmarks using UK Biobank and DRSSW datasets.
• Identified each retinal biomarker’s unique effectiveness for stroke risk ...

Body-machine interfaces (BoMIs)—systems that control assistive devices (e.g., a robotic manipulator) with a person’s movements—offer a robust and non-invasive alternative to brain-machine interfaces for individuals with neurological injuries. ...

• We developed a novel virtual body-machine interface (BoMI) to control assistive robots.
• We compared motor learning with the virtual BoMI to a physical replica.
• Learning with the virtual platform was similar to the physical ...

We introduce our approach towards development of Digital Twins in Healthcare for both ischemic and haemorrhagic stroke, in relation to aetiology and prevention, treatment, and disease progression. These models start their development as generic ...

Trunk compensation is a common behavior observed in stroke patients during rehabilitation, and it can hinder their recovery outcomes. To address this issue, we developed a new upper-limb rehabilitation robot that takes advantage of both end-...

One of the leading causes of disability and death worldwide is stroke, affecting the arteries leading to and within the brain. To help survivors relearn lost skills, post-stroke rehabilitation becomes a paramount part of their life, focusing on ...

Stroke and traumatic brain injury (TBI) are leading causes of morbidity and mortality, affecting survivors’ mobility and social participation. Although personalized interventions could positively impact survivors' recovery, the effectiveness of such ...

Stroke is a leading cause of acquired disabilities in adults worldwide. After initial treatment in hospital, physical rehabilitation counteracting the effects of stroke continues outside of the clinic with home exercises. However, adherence of these ...

In recent years, many fields have expanded their research methods through the integration of artificial intelligence. In the current medical field, it is widely used in image recognition to diagnose patient symptoms, train clinical prediction models, and ...

Accurate and expeditious segmentation of stroke lesions can greatly assist physicians in making accurate medical diagnoses and administering timely treatments. However, there are two limitations to the current deep learning methods. On the one ...

• The TAG module captures detailed local–global feature representations.
• The MAP module elaborate task-relevant features on the multi dimension.
• Based on the TAG and MAP, a novel u-shaped structure FRPNet is constructed.
• The ...

Atrial fibrillation (AF) is a common cardiac arrhythmia, with stroke being its most detrimental comorbidity. The exact mechanism of AF related stroke (AFS) still needs to be explored. In this study, we integrated proteomics and metabolomics ...

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• 53 proteins showed differential expression in AFS compared to AF.
• 114 metabolites showed differential expression in AFS compared to AF.
• Integrated analysis revealed a strong correlation between DEPs and DEMs.
• 12 biomarkers were ...

Most gait rehabilitation exoskeletons focus only on assisting lower limb motions. However, the pelvis plays an essential role in overground ambulation. This calls for the need of gait training devices that allow full control and assistance of ...

• This paper presents PeXo, a novel treadmill-based pelvic assistance exoskeleton for gait rehabilitation
• PeXo has 5 active and 1 passive DOF at the pelvis, plus haptic self-paced walking speed control.
• PeXo was evaluated on a stroke ...

Despite advances in Venoarterial Extracorporeal Membrane Oxygenation (VA-ECMO), a significant mortality rate persists due to complications. The non-physiological blood flow dynamics of VA-ECMO may lead to neurological complications and ...

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• Interaction between native and cannula flow impacted distribution of emboli.
• Cannula size did not significantly affect oxygen transport.
• VA ECMO support level significantly impacted mixing zones and emboli distribution.

A mobile stroke unit (MSU) is a specialized ambulance, enabling to shorten the time to diagnosis and treatment for stroke patients. In the current paper, we present a simulation-based approach to study the potential impacts of collaborative use of ...