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Brain Sciences
Special Issues
Stroke and Acute Stroke Care: Looking Ahead
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Stroke and Acute Stroke Care: Looking Ahead

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurorehabilitation".

Deadline for manuscript submissions: closed (30 May 2024) | Viewed by 8789

Special Issue Editor

Dr. Min Su Kim

E-Mail Website
Guest Editor
Department of Physical & Rehabilitation Medicine, College of Medicine, Soonchunhyang University, Cheonan 31151, Republic of Korea
Interests: stroke; rehabilitation; neuromodulation; physical therapy; robotics; artificial intelligence; neuroimaging; acute stroke care; exercise
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Stroke is a leading cause of long-term disability in millions worldwide each year. Because stroke leaves patients with significant sequelae such as motor impairment, speech impairment, cognitive impairment, and swallowing disorders and places a heavy burden on the patient's family, the development of acute care and rehabilitation techniques is a significant topic for researchers. This Special Issue will cover various aspects related to innovative approaches in stroke acute care and rehabilitation, including:

  • Acute stroke care: exploration of new intervention techniques and protocols for acute stroke care and the potential of neuroprotective agents.
  • Neurotechnology and artificial intelligence-based interventions: exploration of using virtual reality, robotics, sensors, wearables, and artificial intelligence in acute stroke care and rehabilitation.
  • Non-invasive brain stimulation: investigation of transcranial magnetic and electrical stimulation's effectiveness in promoting neural plasticity.
  • Rehabilitation exercise technique: innovative approaches to restore functional disability and improve cardiorespiratory fitness for stroke survivors.

By exploring cutting-edge technologies, techniques, and interventions, we aim to contribute to developing innovative, evidence-based strategies that can optimize stroke care and rehabilitation and improve the lives of stroke survivors.

Dr. Min Su Kim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • stroke
  • rehabilitation
  • neuromodulation
  • physical therapy
  • robotics
  • artificial intelligence
  • neuroimaging
  • acute stroke care
  • exercise

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Published Papers (5 papers)

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11 pages, 846 KiB  
Article
Sensor-Based Balance Training with Exergaming Feedback in Subjects with Chronic Stroke: A Pilot Randomized Controlled Trial
by Alex Martino Cinnera, Irene Ciancarelli, Serena Marrano, Massimiliano Palagiano, Elisa Federici, Alessio Bisirri, Marco Iosa, Stefano Paolucci, Giacomo Koch and Giovanni Morone
Brain Sci. 2024, 14(9), 917; https://doi.org/10.3390/brainsci14090917 - 13 Sep 2024
Viewed by 1204
Abstract
Background: As one of the leading causes of disability in the world, stroke can determine a reduction of balance performance with a negative impact on daily activity and social life. In this study, we aimed to evaluate the effects of sensor-based balance training [...] Read more.
Background: As one of the leading causes of disability in the world, stroke can determine a reduction of balance performance with a negative impact on daily activity and social life. In this study, we aimed to evaluate the effects of sensor-based balance training with exergaming feedback on balance skills in chronic stroke patients. Methods: 21 individuals (11F, 57.14 ± 13.82 years) with a single event of ischemic stroke were randomly assigned to the sensor-based balance training group (SB-group) or the usual care balance training group (UC-group). Both groups received 10 add-on sessions with exergaming feedback (SB-group) or conventional training (UC-group). Clinical and instrumental evaluation was performed before (t0), after (t1), and after one month (t2) from intervention. Participation level was assessed using the Pittsburgh Rehabilitation Participation Scale at the end of each session. Results: The SB-group showed an improvement in postural stability (p = 0.02) when compared to the UC-group. In the evaluation of motivational level, the score was statistically higher in the SB-group with respect to the UC-group (p < 0.01). Conclusion: Except for the improvement in postural stability, no difference was recorded in clinical score, suggesting a comparable gain in both groups. However, patients undergoing sensor-based training exhibited a higher participation score, ultimately indicating the use of this training to improve the adherence to rehabilitation settings, especially in patients with lower compliance. Full article
(This article belongs to the Special Issue Stroke and Acute Stroke Care: Looking Ahead)
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13 pages, 790 KiB  
Article
Automated Pupillometry Is Able to Discriminate Patients with Acute Stroke from Healthy Subjects: An Observational, Cross-Sectional Study
by Irene Scala, Massimo Miccoli, Pia Clara Pafundi, Pier Andrea Rizzo, Francesca Vitali, Simone Bellavia, Jacopo Di Giovanni, Francesca Colò, Giacomo Della Marca, Valeria Guglielmi, Valerio Brunetti, Aldobrando Broccolini, Riccardo Di Iorio, Mauro Monforte, Paolo Calabresi and Giovanni Frisullo
Brain Sci. 2024, 14(6), 616; https://doi.org/10.3390/brainsci14060616 - 20 Jun 2024
Viewed by 1498
Abstract
Background: Automated pupillometry (AP) is a handheld, non-invasive tool that is able to assess pupillary light reflex dynamics and is useful for the detection of intracranial hypertension. Limited evidence is available on acute ischemic stroke (AIS) patients. The primary objective was to evaluate [...] Read more.
Background: Automated pupillometry (AP) is a handheld, non-invasive tool that is able to assess pupillary light reflex dynamics and is useful for the detection of intracranial hypertension. Limited evidence is available on acute ischemic stroke (AIS) patients. The primary objective was to evaluate the ability of AP to discriminate AIS patients from healthy subjects (HS). Secondly, we aimed to compute a predictive score for AIS diagnosis based on clinical, demographic, and AP variables. Methods: We included 200 consecutive patients admitted to a comprehensive stroke center who underwent AP assessment through NPi-200 (NeurOptics®) within 72 h of stroke onset and 200 HS. The mean values of AP parameters and the absolute differences between the AP parameters of the two eyes were considered in the analyses. Predictors of stroke diagnosis were identified through univariate and multivariate logistic regressions; we then computed a nomogram based on each variable’s β coefficient. Finally, we developed a web app capable of displaying the probability of stroke diagnosis based on the predictive algorithm. Results: A high percentage of pupil constriction (CH, p < 0.001), a low constriction velocity (CV, p = 0.002), and high differences between these two parameters (p = 0.036 and p = 0.004, respectively) were independent predictors of AIS. The highest contribution in the predictive score was provided by CH, the Neurological Pupil Index, CV, and CV absolute difference, disclosing the important role of AP in the discrimination of stroke patients. Conclusions: The results of our study suggest that AP parameters, and in particular, those concerning pupillary constriction, may be useful for the early diagnosis of AIS. Full article
(This article belongs to the Special Issue Stroke and Acute Stroke Care: Looking Ahead)
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14 pages, 3610 KiB  
Article
The Development of an Artificial Intelligence Video Analysis-Based Web Application to Diagnose Oropharyngeal Dysphagia: A Pilot Study
by Chang-Won Jeong, Chung-Sub Lee, Dong-Wook Lim, Si-Hyeong Noh, Hee-Kyung Moon, Chul Park and Min-Su Kim
Brain Sci. 2024, 14(6), 546; https://doi.org/10.3390/brainsci14060546 - 27 May 2024
Cited by 4 | Viewed by 1818
Abstract
The gold standard test for diagnosing dysphagia is the videofluoroscopic swallowing study (VFSS). However, the accuracy of this test varies depending on the specialist’s skill level. We proposed a VFSS-based artificial intelligence (AI) web application to diagnose dysphagia. Video from the VFSS consists [...] Read more.
The gold standard test for diagnosing dysphagia is the videofluoroscopic swallowing study (VFSS). However, the accuracy of this test varies depending on the specialist’s skill level. We proposed a VFSS-based artificial intelligence (AI) web application to diagnose dysphagia. Video from the VFSS consists of multiframe data that contain approximately 300 images. To label the data, the server separated them into frames during the upload and stored them as a video for analysis. Then, the separated data were loaded into a labeling tool to perform the labeling. The labeled file was downloaded, and an AI model was developed by training with You Only Look Once (YOLOv7). Using a utility called SplitFolders, the entire dataset was divided according to a ratio of training (70%), test (10%), and validation (20%). When a VFSS video file was uploaded to an application equipped with the developed AI model, it was automatically classified and labeled as oral, pharyngeal, or esophageal. The dysphagia of a person was categorized as either penetration or aspiration, and the final analyzed result was displayed to the viewer. The following labeling datasets were created for the AI learning: oral (n = 2355), pharyngeal (n = 2338), esophageal (n = 1480), penetration (n = 1856), and aspiration (n = 1320); the learning results of the YOLO model, which analyzed dysphagia using the dataset, were predicted with accuracies of 0.90, 0.82, 0.79, 0.92, and 0.96, respectively. This is expected to help clinicians more efficiently suggest the proper dietary options for patients with oropharyngeal dysphagia. Full article
(This article belongs to the Special Issue Stroke and Acute Stroke Care: Looking Ahead)
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13 pages, 2222 KiB  
Article
Overactivity of the Less Affected Side as a Possible Pattern of Asymmetry in Sitting in Patients Suffering from First-Time Ischemic Stroke—An Observational Study
by Agata Zdrowowicz-Doroz, Jakub Stolarski, Karolina Krzysztoń, Izabela Domitrz and Jan Kochanowski
Brain Sci. 2023, 13(12), 1716; https://doi.org/10.3390/brainsci13121716 - 14 Dec 2023
Viewed by 1630
Abstract
It has been observed that in some people in the acute phase of ischemic stroke (IS) there is a tendency to shift the body weight towards the side more affected by the disease and a tendency to spontaneous movements of the upper and/or [...] Read more.
It has been observed that in some people in the acute phase of ischemic stroke (IS) there is a tendency to shift the body weight towards the side more affected by the disease and a tendency to spontaneous movements of the upper and/or lower limbs (not covered by the neurological syndrome). The purposes of this study were: to define the kind of behavior observed, and to select symptoms which can predict its occurrence. Participants (n = 222) hospitalized due to first-time IS were assigned to three groups. A: 78 patients with no lateralization of the neurological syndrome (lateralization of the neurological syndrome—LoNS); B: 109 patients with LoNS; O+ group: 35 patients, who at the beginning of hospitalization presented, apart from LoNS, characteristic motor symptoms performed by the less affected side. Patients underwent therapy depending on the neurological symptoms. If the patient showed potential symptoms of a new phenomenon, overactivity of the less affected side (OLAS), a trial therapy (focused on this behavior) was used to confirm it. The predictive symptoms, selected among these from the index day, for the occurrence of OLAS in sitting were distinguished: asymmetry in supine posture and simple, repetitive movements of the nonparetic upper extremity. Full article
(This article belongs to the Special Issue Stroke and Acute Stroke Care: Looking Ahead)
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17 pages, 1922 KiB  
Systematic Review
The Effect of Extremely Low-Frequency Magnetic Field on Stroke Patients: A Systematic Review
by Renata Marchewka, Tomasz Trzmiel and Katarzyna Hojan
Brain Sci. 2024, 14(5), 430; https://doi.org/10.3390/brainsci14050430 - 26 Apr 2024
Cited by 1 | Viewed by 1936
Abstract
Background: The aim of this study was to review the current state of scientific evidence on the effect of extremely low-frequency magnetic fields stimulation (ELF-MFs) on stroke patients. Methods: A systematic review of PubMed, ScienceDirect, PeDro and Embase databases was conducted. Only articles [...] Read more.
Background: The aim of this study was to review the current state of scientific evidence on the effect of extremely low-frequency magnetic fields stimulation (ELF-MFs) on stroke patients. Methods: A systematic review of PubMed, ScienceDirect, PeDro and Embase databases was conducted. Only articles published in English, involving adult participants and focusing on individuals who had experienced a stroke, specifically examining the impact of ELF-MFs on post-stroke patients and had well-defined criteria for inclusion and exclusion of participants, were included. The methodological quality of the included studies was assessed using the Quality Assessment Tool for Quantitative Studies (QATQS). Results: A total of 71 studies were identified through database and reference lists’ search, from which 9 were included in the final synthesis. All included studies showed a beneficial effect of ELF-MFs on stroke patients, however seven of the included studies were carried by the same research group. Improvements were observed in domains such as oxidative stress, inflammation, ischemic lesion size, functional status, depressive symptoms and cognitive abilities. Conclusions: The available literature suggests a beneficial effect of ELF-MFs on post-stroke patients; however, the current data are too limited to broadly recommend the use of this method. Further research with improved methodological quality is necessary. Full article
(This article belongs to the Special Issue Stroke and Acute Stroke Care: Looking Ahead)
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