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Total 601 results found since Jan 2013.

Sensors, Vol. 22, Pages 9859: Explainable Artificial Intelligence Model for Stroke Prediction Using EEG Signal
This study aims to utilize ML models to classify the ischemic stroke group and the healthy control group for acute stroke prediction in active states. Moreover, XAI tools (Eli5 and LIME) were utilized to explain the behavior of the model and determine the significant features that contribute to stroke prediction models. In this work, we studied 48 patients admitted to a hospital with acute ischemic stroke and 75 healthy adults who had no history of identified other neurological illnesses. EEG was obtained within three months following the onset of ischemic stroke symptoms using frontal, central, temporal, and occipital cor...
Source: Sensors - December 15, 2022 Category: Biotechnology Authors: Mohammed Saidul Islam Iqram Hussain Md Mezbaur Rahman Se Jin Park Md Azam Hossain Tags: Article Source Type: research

Sensors, Vol. 21, Pages 1864: Detection and Classification of Stroke Gaits by Deep Neural Networks Employing Inertial Measurement Units
Tien-Yun Kuo 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 crucial for clinical experts to make decisions about the medication and rehabilitation strategies for the stroke patients. However, the evaluation is often subjective, and different clinicians might have different diagnoses of stroke gait patterns. In addition, some patients may present with mixed neurological gaits. Therefore, we apply artificial intelligen...
Source: Sensors - March 7, 2021 Category: Biotechnology Authors: Fu-Cheng Wang Szu-Fu Chen Chin-Hsien Lin Chih-Jen Shih Ang-Chieh Lin Wei Yuan You-Chi Li Tien-Yun Kuo Tags: Article Source Type: research

Sensors, Vol. 21, Pages 7685: Analysis of Gait Characteristics Using Hip-Knee Cyclograms in Patients with Hemiplegic Stroke
In conclusion, the hip-knee cyclograms, which show inter-joint coordination and visualized gait cycle in stroke patients, are clinically significant.
Source: Sensors - November 19, 2021 Category: Biotechnology Authors: Ho Seok Lee Hokyoung Ryu Shi-Uk Lee Jae-sung Cho Sungmin You Jae Hyeon Park Seong-Ho Jang Tags: Article Source Type: research

Sensors, Vol. 21, Pages 7784: Detection of Unilateral Arm Paresis after Stroke by Wearable Accelerometers and Machine Learning
alle Åström Recent advances in stroke treatment have provided effective tools to successfully treat ischemic stroke, but still a majority of patients are not treated due to late arrival to hospital. With modern stroke treatment, earlier arrival would greatly improve the overall treatment results. This prospective study was performed to asses the capability of bilateral accelerometers worn in bracelets 24/7 to detect unilateral arm paralysis, a hallmark symptom of stroke, early enough to receive treatment. Classical machine learning algorithms as well as state-of-the-art deep neural networks were evaluated on detectio...
Source: Sensors - November 23, 2021 Category: Biotechnology Authors: Johan Wasselius Eric Lyckeg ård Finn Emma Persson Petter Ericson Christina Brog årdh Arne G. Lindgren Teresa Ullberg Kalle Åström Tags: Article Source Type: research

Sensors, Vol. 18, Pages 3420: Using the Pulse Contour Method to Measure the Changes in Stroke Volume during a Passive Leg Raising Test
The objective of this study was to assess the stability and accuracy of this method by making use of the passive leg raising test. We studied 24 healthy subjects (40 ± 9.3 years), and used the Medis® CS 1000, an impedance cardiography, as the comparing reference. The pulse contour method measured the waveform of the brachial artery by using a cuff. The compliance and resistance of the peripheral artery was detected from the cuff characteristics and the blood pressure waveform. Then, according to the method proposed by Romano et al., the stroke volume could be measured. This method was implemented...
Source: Sensors - October 12, 2018 Category: Biotechnology Authors: Chun-Hung Su Shing-Hong Liu Tan-Hsu Tan Chien-Hsien Lo Tags: Article Source Type: research

Sensors, Vol. 20, Pages 4995: The Probability of Ischaemic Stroke Prediction with a Multi-Neural-Network Model
Cong As is known, cerebral stroke has become one of the main diseases endangering people’s health; ischaemic strokes accounts for approximately 85% of cerebral strokes. According to research, early prediction and prevention can effectively reduce the incidence rate of the disease. However, it is difficult to predict the ischaemic stroke because the data related to the disease are multi-modal. To achieve high accuracy of prediction and combine the stroke risk predictors obtained by previous researchers, a method for predicting the probability of stroke occurrence based on a multi-model fusion convolutiona...
Source: Sensors - September 2, 2020 Category: Biotechnology Authors: Yan Liu Bo Yin Yanping Cong Tags: Article Source Type: research

Sensors, Vol. 21, Pages 5334: Prediction of Myoelectric Biomarkers in Post-Stroke Gait
This study aimed to evaluate the potential myoelectric biomarkers for the classification of stroke-impaired muscular activity of the stroke patient group and the muscular activity of the control healthy adult group. We also proposed an EMG-based gait monitoring system consisting of a portable EMG device, cloud-based data processing, data analytics, and a health advisor service. This system was investigated with 48 stroke patients (mean age 70.6 years, 65% male) admitted into the emergency unit of a hospital and 75 healthy elderly volunteers (mean age 76.3 years, 32% male). EMG was recorded during walking using the portable...
Source: Sensors - August 7, 2021 Category: Biotechnology Authors: Iqram Hussain Se-Jin Park Tags: Article Source Type: research

Sensors, Vol. 23, Pages 5513: Automatic Post-Stroke Severity Assessment Using Novel Unsupervised Consensus Learning for Wearable and Camera-Based Sensor Datasets
mmadi Stroke survivors often suffer from movement impairments that significantly affect their daily activities. The advancements in sensor technology and IoT have provided opportunities to automate the assessment and rehabilitation process for stroke survivors. This paper aims to provide a smart post-stroke severity assessment using AI-driven models. With the absence of labelled data and expert assessment, there is a research gap in providing virtual assessment, especially for unlabeled data. Inspired by the advances in consensus learning, in this paper, we propose a consensus clustering algorithm, PSA-NMF, that combin...
Source: Sensors - June 12, 2023 Category: Biotechnology Authors: Najmeh Razfar Rasha Kashef Farah Mohammadi Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7946: Explainable Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Machine Learning Techniques in a Population of 1780 Patients
In this study, we aimed to develop a machine learning (ML) model to predict the risk of PSAMO. We retrospectively studied 1780 patients with stroke who were divided into PSAMO vs. no PSAMO groups based on results of validated depression and anxiety questionnaires. The features collected included demographic and sociological data, quality of life scores, stroke-related information, medical and medication history, and comorbidities. Recursive feature elimination was used to select features to input in parallel to eight ML algorithms to train and test the model. Bayesian optimization was used for hyperparameter tuning. Shaple...
Source: Sensors - September 17, 2023 Category: Biotechnology Authors: Chien Wei Oei Eddie Yin Kwee Ng Matthew Hok Shan Ng Ru-San Tan Yam Meng Chan Lai Gwen Chan Udyavara Rajendra Acharya Tags: Communication Source Type: research

Sensors, Vol. 21, Pages 324: Arm-Stroke Descriptor Variability during 200-m Front Crawl Swimming
gio Gatta The present study aimed to explore the variability of the arm-stroke temporal descriptors between and within laps during middle-distance swimming event using IMMUs. Eight male swimmers performed a 200-m maximum front-crawl in which the inter-lap and intra-lap variability of velocity, stroke rate, stroke-phases duration and arm-coordination index were measured through five units of IMMU. An algorithm computes the 3D coordinates of the wrist by means the IMMU orientation and the kinematic chain of upper arm biomechanical model, and it recognizes the start events of the four arm-stroke phases. Velocity and strok...
Source: Sensors - January 6, 2021 Category: Biotechnology Authors: Matteo Cortesi Rocco Di Michele Silvia Fantozzi Sandro Bartolomei Giorgio Gatta Tags: Article Source Type: research

Sensors, Vol. 21, Pages 4269: Deep Learning-Based Stroke Disease Prediction System Using Real-Time Bio Signals
Jae-Hak Yu The emergence of an aging society is inevitable due to the continued increases in life expectancy and decreases in birth rate. These social changes require new smart healthcare services for use in daily life, and covid-19 has also led to a contactless trend necessitating more non-face-to-face health services. Due to the improvements that have been achieved in healthcare technologies, an increasing number of studies have attempted to predict and analyze certain diseases in advance. Research on stroke diseases is actively underway, particularly with the aging population. Stroke, which is fatal to the elderl...
Source: Sensors - June 22, 2021 Category: Biotechnology Authors: Yoon-A Choi Se-Jin Park Jong-Arm Jun Cheol-Sig Pyo Kang-Hee Cho Han-Sung Lee Jae-Hak Yu Tags: Article Source Type: research

Sensors, Vol. 21, Pages 4740: Impacts of Stroke on Muscle Perceptions and Relationships with the Motor and Functional Performance of the Lower Extremities
This study indicated poorer accuracy and consistency in muscle perception for paretic ankles, which correlated with lower limb functions of stroke patients.
Source: Sensors - July 11, 2021 Category: Biotechnology Authors: Wan-Ju Liu Li-Fong Lin Shang-Lin Chiang Liang-Hsuan Lu Chao-Ying Chen Chueh-Ho Lin Tags: Article Source Type: research

Sensors, Vol. 22, Pages 1419: Integrated Timing of Stroking, Breathing, and Kicking in Front-Crawl Swimming: A Novel Stroke-by-Stroke Approach Using Wearable Inertial Sensors
atteo Cortesi Quantitative evaluation of synergic action among the different body segments is fundamental to swimming performance. The aim of the present study was to develop an easy-to-use tool for stroke-by-stroke evaluation of a swimmer’s integrated timing of stroking, kicking, and breathing. Twelve swimmers were evaluated during one trial of 100 m front-crawl swimming at self-selected speed. Five three-axial inertial sensors were mounted on the head, wrists, and ankles. Algorithms for the wrist entry into the water, the lower limb beat during the downward action, and the exit/entry of the face from/in...
Source: Sensors - February 12, 2022 Category: Biotechnology Authors: Silvia Fantozzi Vittorio Coloretti Maria Francesca Piacentini Claudio Quagliarotti Sandro Bartolomei Giorgio Gatta Matteo Cortesi Tags: Article Source Type: research

Sensors, Vol. 22, Pages 1409: Usability of Functional Electrical Stimulation in Upper Limb Rehabilitation in Post-Stroke Patients: A Narrative Review
ubim Santos Stroke leads to significant impairment in upper limb (UL) function. The goal of rehabilitation is the reestablishment of pre-stroke motor stroke skills by stimulating neuroplasticity. Among several rehabilitation approaches, functional electrical stimulation (FES) is highlighted in stroke rehabilitation guidelines as a supplementary therapy alongside the standard care modalities. The aim of this study is to present a comprehensive review regarding the usability of FES in post-stroke UL rehabilitation. Specifically, the factors related to UL rehabilitation that should be considered in FES usability, as well ...
Source: Sensors - February 12, 2022 Category: Biotechnology Authors: Andreia S. P. Sousa Juliana Moreira Cl áudia Silva In ês Mesquita Rui Macedo Augusta Silva Rubim Santos Tags: Review Source Type: research

A magnetoimpedance biosensor microfluidic platform for detection of glial fibrillary acidic protein in blood for acute stroke classification
Biosens Bioelectron. 2022 May 20;211:114410. doi: 10.1016/j.bios.2022.114410. Online ahead of print.ABSTRACTAcute stroke is the third leading cause of mortality and disability worldwide. Administration of appropriate therapy for acute stroke is critically dependent on timely classification into either ischemic or hemorrhagic subtypes, which have divergent treatment pathways. The current classification method is based on neuroimaging, which generally requires the transport of the patient to a hospital-based facility unless a mobile stroke unit is available. Plasma glial fibrillary acidic protein (GFAP) level has been identi...
Source: Biosensors and Bioelectronics - May 26, 2022 Category: Biotechnology Authors: Abkar Sayad Shah Mukim Uddin Scarlett Yao Harold Wilson Jianxiong Chan Henry Zhao Geoffrey Donnan Stephen Davis Efstratios Skafidas Bernard Yan Patrick Kwan Source Type: research