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Post-stroke functional assessments based on rehabilitation games and their correlation with clinical scales: A scoping review
AbstractConsidering that stroke is one of the main causes of adult impairment and the growing interest in Virtual Reality (VR) as a potential assessment and treatment tool for the rehabilitation of stroke patients, a scoping review was conducted to check whether user ’s motion data obtained from VR games and simulations can be clinically valid. This was done by reviewing studies on parameters for assessing the functional skills and rehabilitation progress using data from VR games or simulations. Then, identifying the most widely used and validated parameters f or the quantification of motor ability in a virtual environme...
Source: Medical and Biological Engineering and Computing - September 19, 2023 Category: Biomedical Engineering Source Type: research

Cardiac disease prediction using AI algorithms with SelectKBest
AbstractAtherosclerotic cardiovascular disease (ASCVD), which includes coronary heart disease (CHD) and ischemic stroke, is the leading cause of mortality globally. According to the European Society of Cardiology (ESC), 26 million people worldwide have heart disease, with 3.6 million diagnosed each year. Early detection of heart disease will aid in lowering the mortality rate. The lack of diversity in training data and the difficulty in comprehending the findings of complicated AI models are the key issues in current research for heart disease prediction using artificial intelligence. To overcome this, in this paper, cardi...
Source: Medical and Biological Engineering and Computing - September 8, 2023 Category: Biomedical Engineering Source Type: research

Effect of tDCS on corticomuscular coupling and the brain functional network of stroke patients
AbstractTranscranial direct current stimulation (tDCS) is an emerging brain intervention technique that has gained growing attention in recent years in the rehabilitation area. In this paper, we investigated the efficacy of tDCS in the rehabilitation process of stroke patients, utilizing corticomuscular coupling (CMC) and brain functional network analysis. Specifically, we examined changes in CMC relationships between the treatment and control groups before and after rehabilitation by transfer entropy (TE), and constructed brain functional networks by TE. We further calculated features of the functional networks, including...
Source: Medical and Biological Engineering and Computing - September 5, 2023 Category: Biomedical Engineering Source Type: research

Automatic Alberta Stroke Program Early Computed Tomographic Scoring in patients with acute ischemic stroke using diffusion-weighted imaging
This study aims to propose a deep learning based automatic evaluation strategy for DWI-ASPECTS to serve as a reference for clinicians in urgent decision making for endovascular thrombectomy. Ten ASPECTS regions are extracted from the DWI series to train the independent classification network for each region, the accurate training labels of which are confirmed by neuroradiologists. Two classical convolutional neural networks (VGG-16 and ResNet-50) are validated. Subsequently, the innovative CBAM-VGG is designed to improve the accurate scoring of four small-volume DWI-ASPECTS regions, including caudate nucleus, lenticular nu...
Source: Medical and Biological Engineering and Computing - July 13, 2023 Category: Biomedical Engineering Source Type: research

Gait asymmetry in stroke patients with unilateral spatial neglect
AbstractThe recovery of independent gait represents one of the main functional goals of the rehabilitative interventions after stroke but it can be hindered by the presence of unilateral spatial neglect (USN). The aim of the paper is to study if the presence of USN in stroke patients affects lower limb gait parameters between the two body sides, differently from what could be expected by the motor impairment alone, and to explore whether USN is associated to specific gait asymmetry. Thirty-five stroke patients (right or left lesion and ischemic or hemorrhagic etiology) who regained independent gait were assessed for global...
Source: Medical and Biological Engineering and Computing - December 29, 2022 Category: Biomedical Engineering Source Type: research

Hemodynamic effects of intravenous bolus injection of iopromide 370 twice in abdominal contrast-enhanced CT and coronary CTA dual-site sequential examinations
In conclusion, intravenous bolus injection of iopromide 370 twice in dual-site sequential examinations induced dose-cumulative and time-dependent hemodynamic effects, which all fluctuated within the normal ranges.Graphical abstract
Source: Medical and Biological Engineering and Computing - November 7, 2022 Category: Biomedical Engineering Source Type: research

Using convolutional neural network to analyze brain MRI images for predicting functional outcomes of stroke
AbstractNowadays, the physicians usually predict functional outcomes of stroke based on clinical experiences and big data, so we wish to develop a model to accurately identify imaging features for predicting functional outcomes of stroke patients. Using magnetic resonance imaging of ischemic and hemorrhagic stroke patients, we developed and trained a VGG-16 convolutional neural network (CNN) to predict functional outcomes after 28-day hospitalization. A total of 44 individuals (24 men and 20 women) were recruited from Taoyuan General Hospital and China Medical University Hsinchu Hospital to enroll in the study. Based on â€...
Source: Medical and Biological Engineering and Computing - August 2, 2022 Category: Biomedical Engineering Source Type: research

Ludic Table: a comparative study between playful rehabilitation and kinesiotherapy in restricting upper limb movements in individuals with stroke
AbstractStroke is a neurological syndrome resulting from the sudden interruption of blood flow. Among the symptoms/consequences of the stroke are muscle weakness in the lower and/or upper limbs, decreased sensitivity, altered fine motor skills, proprioception, and reflections. The treatment for the motor consequences is orthopedic management, in which the physiotherapist assists the individual in repetitive range of motion exercises, which can be demotivating during the treatment. The Ludic Table (LT), on the other hand, incorporates playfulness into therapy, making it a motivating tool. This research describes the compara...
Source: Medical and Biological Engineering and Computing - March 4, 2022 Category: Biomedical Engineering Source Type: research

Real-time visual analytics for in-home medical rehabilitation of stroke patient —systematic review
This study has emphasized the analysis of the most important research works in these domains. The studies included in this review are published between January 2008 and December 2020 that met eligibility criteria. From 243 papers retrieved from research including the Google Scholar database and manual research, 69 papers were finally included. This paper presents a classification of the reviewed research based on key features required by the visual analytics for real-time monitoring of patients. The findings suggested that real-time monitoring visual analytics for biodata captured during the rehabilitation sessions was not...
Source: Medical and Biological Engineering and Computing - February 1, 2022 Category: Biomedical Engineering Source Type: research

Handling of derived imbalanced dataset using XGBoost for identification of pulmonary embolism —a non-cardiac cause of cardiac arrest
AbstractRelationship between pulmonary embolism and heart failure is presented in this paper. The proposed research is divided into two phases. The first phase includes the establishment of a novel database with the help of a Cleveland ’s database for cardiology in order to establish a link between pulmonary embolism and heart failure. The connectivity is based on the relationship between the stroke volume and the pulse pressure (Pp <  25% (ap_hi)). The second phase includes the applicability of machine learning on the novel database. Novel database formed in this work is imbalanced, resulting in the overfitting p...
Source: Medical and Biological Engineering and Computing - January 13, 2022 Category: Biomedical Engineering Source Type: research

Evaluation of carotid intima media thickness measurement from ultrasound images
AbstractA third of deaths in the world are due to cardiovascular diseases [1]. Atherosclerosis is the major cause of myocardial infarction, which occurs by deposition of plaque in the coronary artery. The chance of stroke rises with the thickening of carotid artery due to the plaque. Hence, accurate measurement of the intima-media thickness is necessary for predicting the chance of stroke. The stopping criterion and active resampling are incorporated in greedy snake segmentation technique. This modified algorithm segmented and extracted the intima-media complex in the ultrasound images. The snake control points obtained fr...
Source: Medical and Biological Engineering and Computing - January 6, 2022 Category: Biomedical Engineering Source Type: research

Identifying risk factors of intracerebral hemorrhage stability using explainable attention model
AbstractSegmentation of intracerebral hemorrhage (ICH) helps improve the quality of diagnosis, draft the desired treatment methods, and clinically observe the variations with healthy patients. The clinical utilization of various ICH progression scoring systems has limitations due to the systems ’ modest predictive value. This paper proposes a single pipeline of a multi-task model for end-to-end hemorrhage segmentation and risk estimation. We introduce a 3D spatial attention unit and integrate it into the state-of-the-art segmentation architecture, UNet, to enhance the accuracy by bootstr apping the global spatial represe...
Source: Medical and Biological Engineering and Computing - December 2, 2021 Category: Biomedical Engineering Source Type: research

Predictive and diagnosis models of stroke from hemodynamic signal monitoring
AbstractThis work presents a novel and promising approach to the clinical management of acute stroke. Using machine learning techniques, our research has succeeded in developing accurate diagnosis and prediction real-time models from hemodynamic data. These models are able to diagnose stroke subtype with 30 min of monitoring, to predict the exitus during the first 3 h of monitoring, and to predict the stroke recurrence in just 15 min of monitoring. Patients with difficult access to a CT scan and all patients that arrive at the stroke unit of a specialized hospital will benefit from these positive results. The results obtai...
Source: Medical and Biological Engineering and Computing - May 14, 2021 Category: Biomedical Engineering Source Type: research

Effect of triangular electrode schemes on Broca ’s cortical stimulation: conventional and HD-tDCS study
AbstractTranscranial direct current stimulation (tDCS) is a therapeutic and complementary treatment in several cognitive diseases, psychiatric disorders, and disabilities that occur due to an accident or stroke. In the current research, we aimed to boost some parts of the stimulation structure and proposed a new electrode scheme in the mentioned approach. After segmenting magnetic resonance imaging (MRI) scans and using a tissue correction routine algorithm, we attempted to create an appropriate head model and electrode placement according to electric stimulation, whereby we completed tDCS processing. The considered electr...
Source: Medical and Biological Engineering and Computing - March 30, 2021 Category: Biomedical Engineering Source Type: research

Hybrid artificial fish particle swarm optimizer and kernel extreme learning machine for type-II diabetes predictive model
AbstractThe World Health Organization(WHO) estimated that in 2016, 1.6 million deaths caused were due to diabetes. Precise and on-time diagnosis of type-II diabetes is crucial to reduce the risk of various diseases such as heart disease, stroke, kidney disease, diabetic retinopathy, diabetic neuropathy, and macrovascular problems. The non-invasive methods like machine learning are reliable and efficient in classifying the people subjected to type-II diabetics risk and healthy people into two different categories. This present study aims to develop a stacking-based integrated kernel extreme learning machine (KELM) model for...
Source: Medical and Biological Engineering and Computing - March 18, 2021 Category: Biomedical Engineering Source Type: research

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