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Sensors, Vol. 23, Pages 6793: Performance Evaluation for Clinical Stroke Rehabilitation via an Automatic Mobile Gait Trainer
Fu-Cheng Wang This paper investigates the clinical efficacy of an automatic mobile trainer for gait training in stroke patients. Neuro-Developmental Treatment (NDT) is a rehabilitation method for stroke patients that enhances motor learning through repeated practice. Despite the proven effectiveness of therapist-assisted NDT, it is labor-intensive and demands health resources. Therefore, we developed automatic trainers based on NDT principles to perform gait training. This paper modifies the mobile trainer’s intervention patterns to improve the subject’s longitudinal gait symmetry, lateral p...
Source: Sensors - July 29, 2023 Category: Biotechnology Authors: Chih-Jen Shih You-Chi Li Wei Yuan Szu-Fu Chen Ang-Chieh Lin Tzu-Tung Lin Fu-Cheng Wang Tags: Article Source Type: research

Sensors, Vol. 18, Pages 4107: Compressibility of High-Density EEG Signals in Stroke Patients
sco C. Morabito Stroke is a critical event that causes the disruption of neural connections. There is increasing evidence that the brain tries to reorganize itself and to replace the damaged circuits, by establishing compensatory pathways. Intra- and extra-cellular currents are involved in the communication between neurons and the macroscopic effects of such currents can be detected at the scalp through electroencephalographic (EEG) sensors. EEG can be used to study the lesions in the brain indirectly, by studying their effects on the brain electrical activity. The primary goal of the present work was to investigate po...
Source: Sensors - November 23, 2018 Category: Biotechnology Authors: Nadia Mammone Simona De Salvo Cosimo Ieracitano Silvia Marino Emanuele Cartella Alessia Bramanti Roberto Giorgianni Francesco C. Morabito Tags: Article Source Type: research

Sensors, Vol. 21, Pages 4482: NE-Motion: Visual Analysis of Stroke Patients Using Motion Sensor Networks
tavo Nonato A large number of stroke survivors suffer from a significant decrease in upper extremity (UE) function, requiring rehabilitation therapy to boost recovery of UE motion. Assessing the efficacy of treatment strategies is a challenging problem in this context, and is typically accomplished by observing the performance of patients during their execution of daily activities. A more detailed assessment of UE impairment can be undertaken with a clinical bedside test, the UE Fugl–Meyer Assessment, but it fails to examine compensatory movements of functioning body segments that are used to bypass impairment. In th...
Source: Sensors - June 30, 2021 Category: Biotechnology Authors: Rodrigo Colnago Contreras Avinash Parnandi Bruno Gomes Coelho Claudio Silva Heidi Schambra Luis Gustavo Nonato Tags: Article Source Type: research

Sensors, Vol. 22, Pages 4670: Stroke Risk Prediction with Machine Learning Techniques
gka A stroke is caused when blood flow to a part of the brain is stopped abruptly. Without the blood supply, the brain cells gradually die, and disability occurs depending on the area of the brain affected. Early recognition of symptoms can significantly carry valuable information for the prediction of stroke and promoting a healthy life. In this research work, with the aid of machine learning (ML), several models are developed and evaluated to design a robust framework for the long-term risk prediction of stroke occurrence. The main contribution of this study is a stacking method that achieves a high performance that ...
Source: Sensors - June 21, 2022 Category: Biotechnology Authors: Elias Dritsas Maria Trigka Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7872: Development and Testing of a Daily Activity Recognition System for Post-Stroke Rehabilitation
kubic Those who survive the initial incidence of a stroke experience impacts on daily function. As a part of the rehabilitation process, it is essential for clinicians to monitor patients’ health status and recovery progress accurately and consistently; however, little is known about how patients function in their own homes. Therefore, the goal of this study was to develop, train, and test an algorithm within an ambient, in-home depth sensor system that can classify and quantify home activities of individuals post-stroke. We developed the Daily Activity Recognition and Assessment System (DARAS). A daily a...
Source: Sensors - September 14, 2023 Category: Biotechnology Authors: Rachel Proffitt Mengxuan Ma Marjorie Skubic Tags: Article Source Type: research

Sensors, Vol. 21, Pages 914: Paddle Stroke Analysis for Kayakers Using Wearable Technologies
In this study, we propose a systematic approach for evaluating the training performance of kayakers based on the multiple sensors fusion technology. Kayakers’ motion information is collected by miniature inertial sensor nodes attached on the body. The extend Kalman filter (EKF) method is used for data fusion and updating human posture. After sensor calibration, the kayakers’ actions are reconstructed by rigid-body model. The quantitative kinematic analysis is carried out based on joint angles. Machine learning algorithms are used for differentiating the stroke cycle into different phases, includ...
Source: Sensors - January 29, 2021 Category: Biotechnology Authors: Long Liu Hui-Hui Wang Sen Qiu Yun-Cui Zhang Zheng-Dong Hao Tags: Article Source Type: research

Sensors, Vol. 21, Pages 5130: Estimation of Stroke Volume Variance from Arterial Blood Pressure: Using a 1-D Convolutional Neural Network
Conclusions: We developed a new CNN deep-learning model to estimate SVV. Our CNN model seems to be a viable alternative when the necessary medical device is not available, thereby allowing a wider range of application and resulting in optimal patient management.
Source: Sensors - July 29, 2021 Category: Biotechnology Authors: Hye-Mee Kwon Woo-Young Seo Jae-Man Kim Woo-Hyun Shim Sung-Hoon Kim Gyu-Sam Hwang Tags: Article Source Type: research

Sensors, Vol. 22, Pages 5066: Detection of a Stroke Volume Decrease by Machine-Learning Algorithms Based on Thoracic Bioimpedance in Experimental Hypovolaemia
Aarne Feldheiser Compensated shock and hypovolaemia are frequent conditions that remain clinically undetected and can quickly cause deterioration of perioperative and critically ill patients. Automated, accurate and non-invasive detection methods are needed to avoid such critical situations. In this experimental study, we aimed to create a prediction model for stroke volume index (SVI) decrease based on electrical cardiometry (EC) measurements. Transthoracic echo served as reference for SVI assessment (SVI-TTE). In 30 healthy male volunteers, central hypovolaemia was simulated using a lower body negative pressure (LBN...
Source: Sensors - July 6, 2022 Category: Biotechnology Authors: Matthias Stetzuhn Timo Tigges Alexandru Gabriel Pielmus Claudia Spies Charlotte Middel Michael Klum Sebastian Zaunseder Reinhold Orglmeister Aarne Feldheiser Tags: Article Source Type: research

Sensors, Vol. 16, Pages 134: A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington’s Disease Patients
Machine learning methods have been widely used for gait assessment through the estimation of spatio-temporal parameters. As a further step, the objective of this work is to propose and validate a general probabilistic modeling approach for the classification of different pathological gaits. Specifically, the presented methodology was tested on gait data recorded on two pathological populations (Huntington’s disease and post-stroke subjects) and healthy elderly controls using data from inertial measurement units placed at shank and waist. By extracting features from group-specific Hidden Markov Models (HMMs) and signal in...
Source: Sensors - January 21, 2016 Category: Biotechnology Authors: Andrea ManniniDiana TrojanielloAndrea CereattiAngelo Sabatini Tags: Article Source Type: research

Sensors, Vol. 22, Pages 5347: Surface-Free Multi-Stroke Trajectory Reconstruction and Word Recognition Using an IMU-Enhanced Digital Pen
n M. Eskofier Efficient handwriting trajectory reconstruction (TR) requires specific writing surfaces for detecting movements of digital pens. Although several motion-based solutions have been developed to remove the necessity of writing surfaces, most of them are based on classical sensor fusion methods limited, by sensor error accumulation over time, to tracing only single strokes. In this work, we present an approach to map the movements of an IMU-enhanced digital pen to relative displacement data. Training data is collected by means of a tablet. We propose several pre-processing and data-preparation methods to sync...
Source: Sensors - July 18, 2022 Category: Biotechnology Authors: Mohamad Wehbi Daniel Luge Tim Hamann Jens Barth Peter Kaempf Dario Zanca Bjoern M. Eskofier Tags: Article Source Type: research

Sensors, Vol. 19, Pages 2573: Cerebral Small Vessel Disease Biomarkers Detection on MRI-Sensor-Based Image and Deep Learning
-Chun Hsieh Magnetic resonance imaging (MRI) offers the most detailed brain structure image available today; it can identify tiny lesions or cerebral cortical abnormalities. The primary purpose of the procedure is to confirm whether there is structural variation that causes epilepsy, such as hippocampal sclerotherapy, local cerebral cortical dysplasia, and cavernous hemangioma. Cerebrovascular disease, the second most common factor of death in the world, is also the fourth leading cause of death in Taiwan, with cerebrovascular disease having the highest rate of stroke. Among the most common are large vascular atheroscl...
Source: Sensors - June 5, 2019 Category: Biotechnology Authors: Yi-Zeng Hsieh Yu-Cin Luo Chen Pan Mu-Chun Su Chi-Jen Chen Kevin Li-Chun Hsieh Tags: Article Source Type: research

Sensors, Vol. 23, Pages 6110: Application of Deep Learning Algorithm to Monitor Upper Extremity Task Practice
The objective of this study was to develop algorithms to enable the objective identification of task type and quality. Twenty neurotypical participants wore an IMU sensor on the wrist and performed four representative tasks in prescribed fashions that mimicked correct, compensatory, and incomplete movement qualities typically seen in stroke survivors. LSTM classifiers were trained to identify the task being performed and its movement quality. Our models achieved an accuracy of 90.8% for task identification and 84.9%, 81.1%, 58.4%, and 73.2% for movement quality classification for the four tasks for unseen participants. The...
Source: Sensors - July 3, 2023 Category: Biotechnology Authors: Mingqi Li Gabrielle Scronce Christian Finetto Kristen Coupland Matthew Zhong Melanie E. Lambert Adam Baker Feng Luo Na Jin Seo Tags: Article Source Type: research

Sensors, Vol. 21, Pages 3130: A System for Neuromotor Based Rehabilitation on a Passive Robotic Aid
Moroni In the aging world population, the occurrence of neuromotor deficits arising from stroke and other medical conditions is expected to grow, demanding the design of new and more effective approaches to rehabilitation. In this paper, we show how the combination of robotic technologies with progress in exergaming methodologies may lead to the creation of new rehabilitation protocols favoring motor re-learning. To this end, we introduce the Track-Hold system for neuromotor rehabilitation based on a passive robotic arm and integrated software. A special configuration of weights on the robotic arm fully balances the w...
Source: Sensors - April 30, 2021 Category: Biotechnology Authors: Marco Righi Massimo Magrini Cristina Dolciotti Davide Moroni Tags: Article Source Type: research

Sensors, Vol. 22, Pages 2414: Sensing System for Plegic or Paretic Hands Self-Training Motivation
inik Patients after stroke with paretic or plegic hands require frequent exercises to promote neuroplasticity and to improve hand joint mobilization. Available devices for hand exercising are intended for persons with some level of hand control or provide continuous passive motion with limited patient involvement. Patients can benefit from self-exercising where they use the other hand to exercise the plegic or paretic one. However, post-stroke neuropsychological complications, apathy, and cognitive impairments such as forgetfulness make regular self-exercising difficult. This paper describes Przypominajka v2&md...
Source: Sensors - March 21, 2022 Category: Biotechnology Authors: Igor Zubrycki Ewa Pr ączko-Pawlak Ilona Dominik Tags: Article Source Type: research

Sensors, Vol. 20, Pages 2110: Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion
aXin Wang Coaches and athletes are constantly seeking novel training methodologies in an attempt to improve athletic performance. This paper proposes a method of rowing sport capture and analysis based on Inertial Measurement Units (IMUs). A canoeist’s motion was collected by multiple miniature inertial sensor nodes. The gradient descent method was used to fuse data and obtain the canoeist’s attitude information after sensor calibration, and then the motions of canoeist’s actions were reconstructed. Stroke quality was performed based on the estimated joint angles. Machine learn...
Source: Sensors - April 7, 2020 Category: Biotechnology Authors: Long Liu Sen Qiu ZheLong Wang Jie Li JiaXin Wang Tags: Article Source Type: research

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