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Source: Sensors

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Total 332 results found since Jan 2013.

Sensors, Vol. 22, Pages 6708: Investigating Stroke Effects on Respiratory Parameters Using a Wearable Device: A Pilot Study on Hemiplegic Patients
This study investigates the performance of a custom wearable device for respiratory monitoring in post-stroke patients. We tested the device on six hemiplegic patients under different respiratory regimes. The estimated respiratory parameters (i.e., respiratory frequency and the timing of the respiratory phase) demonstrated good agreement with the ones provided by a gold standard device. The promising results of this pilot study encourage the exploitation of wearables on these patients that may strongly impact the treatment of chronic diseases, such as hemiplegia.
Source: Sensors - September 5, 2022 Category: Biotechnology Authors: Joshua Di Di Tocco Daniela Lo Presti Martina Zaltieri Marco Bravi Michelangelo Morrone Silvia Sterzi Emiliano Schena Carlo Massaroni Tags: Article Source Type: research

Sensors, Vol. 22, Pages 6596: Research and Development of Ankle & ndash;Foot Orthoses: A Review
This article reviews the development process of ankle–foot orthoses and proposes that the integration of new ankle–foot orthoses with rehabilitation technologies such as monitoring or myoelectric stimulation will play an important role in reducing the walking energy consumption of patients in the study of human-in-the-loop models and promoting neuro/muscular rehabilitation.
Source: Sensors - September 1, 2022 Category: Biotechnology Authors: Congcong Zhou Zhao Yang Kaitai Li Xuesong Ye Tags: Systematic Review Source Type: research

Sensors, Vol. 22, Pages 6323: Deep Learning-Based Subtask Segmentation of Timed Up-and-Go Test Using RGB-D Cameras
Ha Ryu The timed up-and-go (TUG) test is an efficient way to evaluate an individual’s basic functional mobility, such as standing up, walking, turning around, and sitting back. The total completion time of the TUG test is a metric indicating an individual’s overall mobility. Moreover, the fine-grained consumption time of the individual subtasks in the TUG test may provide important clinical information, such as elapsed time and speed of each TUG subtask, which may not only assist professionals in clinical interventions but also distinguish the functional recovery of patients. To perform mor...
Source: Sensors - August 23, 2022 Category: Biotechnology Authors: Yoon Jeong Choi Yoo Sung Bae Baek Dong Cha Je Ha Ryu Tags: Article Source Type: research

Sensors, Vol. 22, Pages 6190: Sleep Monitoring during Acute Stroke Rehabilitation: Toward Automated Measurement Using Multimodal Wireless Sensors
In this study, we explored the feasibility of (1) collecting overnight biophysical data from patients with subacute stroke using a simple sensor system and (2) constructing machine-learned algorithms to detect sleep stages. Ten individuals with stroke in an inpatient rehabilitation hospital wore two wireless sensors during a single night of sleep. Polysomnography served as ground truth to classify different sleep stages. A population model, trained on data from multiple patients and tested on data from a separate patient, performed poorly for this limited sample. Personal models trained on data from one patient and tested ...
Source: Sensors - August 18, 2022 Category: Biotechnology Authors: Pin-Wei Chen Megan K. O ’Brien Adam P. Horin Lori L. McGee Koch Jong Yoon Lee Shuai Xu Phyllis C. Zee Vineet M. Arora Arun Jayaraman Tags: Article Source Type: research

Sensors, Vol. 22, Pages 6113: Recognition of Uni-Stroke Characters with Hand Movements in 3D Space Using Convolutional Neural Networks
il Shin Hand gestures are a common means of communication in daily life, and many attempts have been made to recognize them automatically. Developing systems and algorithms to recognize hand gestures is expected to enhance the experience of human–computer interfaces, especially when there are difficulties in communicating vocally. A popular system for recognizing hand gestures is the air-writing method, where people write letters in the air by hand. The arm movements are tracked with a smartwatch/band with embedded acceleration and gyro sensors; a computer system then recognizes the written letters. One o...
Source: Sensors - August 16, 2022 Category: Biotechnology Authors: Won-Du Chang Akitaka Matsuoka Kyeong-Taek Kim Jungpil Shin Tags: Article Source Type: research

Sensors, Vol. 22, Pages 5589: Ti2C-TiO2 MXene Nanocomposite-Based High-Efficiency Non-Enzymatic Glucose Sensing Platform for Diabetes Monitoring
a Yadav Vinod Verma Diabetes is a major health challenge, and it is linked to a number of serious health issues, including cardiovascular disease (heart attack and stroke), diabetic nephropathy (kidney damage or failure), and birth defects. The detection of glucose has a direct and significant clinical importance in the management of diabetes. Herein, we demonstrate the application of in-situ synthesized Ti2C-TiO2 MXene nanocomposite for high throughput non-enzymatic electrochemical sensing of glucose. The nanocomposite was synthesized by controlled oxidation of Ti2C-MXene nanosheets using H2O2 at room temperature. T...
Source: Sensors - July 26, 2022 Category: Biotechnology Authors: Vinod Kumar Sudheesh K. Shukla Meenakshi Choudhary Jalaj Gupta Priyanka Chaudhary Saurabh Srivastava Mukesh Kumar Manoj Kumar Devojit Kumar Sarma Bal Chandra Yadav Vinod Verma Tags: Article Source Type: research

Sensors, Vol. 22, Pages 5349: Reconstructing Synergy-Based Hand Grasp Kinematics from Electroencephalographic Signals
In this study, ten healthy right-handed participants were asked to perform six types of hand grasps representative of the activities of daily living while their neural activities were recorded using electroencephalography (EEG). From half of the participants, hand kinematic synergies were derived, and a neural decoder was developed, based on the correlation between hand synergies and corresponding cortical activity, using multivariate linear regression. Using the synergies and the neural decoder derived from the first half of the participants and only cortical activities from the remaining half of the participants, their h...
Source: Sensors - July 18, 2022 Category: Biotechnology Authors: Dingyi Pei Parthan Olikkal T ülay Adali Ramana Vinjamuri 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. 22, Pages 5293: Localization of Dielectric Anomalies with Multi-Monostatic S11 Using 2D MUSIC Algorithm with Spatial Smoothing
This article demonstrates that the complex value of S11 of an antenna, acquired in a multi-monostatic configuration, can be used for localization of a dielectric anomaly hidden inside a dielectric background medium when the antenna is placed close (~5 mm) to the geometry. It uses an Inverse Synthetic Aperture Radar (ISAR) imaging framework where data is acquired at multiple frequencies and look-angles. Initially, near-field scattering data are used for simulation to validate this methodology since the basic derivation of the Multiple Signal Classification (MUSIC) algorithm is based on the plain wave assumption. Later on, f...
Source: Sensors - July 15, 2022 Category: Biotechnology Authors: Ahmad Bilal Choon Sik Cho Tags: Article Source Type: research

Sensors, Vol. 22, Pages 5200: Towards Multiplexed and Multimodal Biosensor Platforms in Real-Time Monitoring of Metabolic Disorders
Hung Cao Metabolic syndrome (MS) is a cluster of conditions that increases the probability of heart disease, stroke, and diabetes, and is very common worldwide. While the exact cause of MS has yet to be understood, there is evidence indicating the relationship between MS and the dysregulation of the immune system. The resultant biomarkers that are expressed in the process are gaining relevance in the early detection of related MS. However, sensing only a single analyte has its limitations because one analyte can be involved with various conditions. Thus, for MS, which generally results from the co-existence of multipl...
Source: Sensors - July 12, 2022 Category: Biotechnology Authors: Sung Sik Chu Hung Anh Nguyen Jimmy Zhang Shawana Tabassum Hung Cao Tags: Review 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. 22, Pages 4910: Kinect-Based Assessment of Lower Limbs during Gait in Post-Stroke Hemiplegic Patients: A Narrative Review
Veronica Cimolin The aim of this review was to present an overview of the state of the art in the use of the Microsoft Kinect camera to assess gait in post-stroke individuals through an analysis of the available literature. In recent years, several studies have explored the potentiality, accuracy, and effectiveness of this 3D optical sensor as an easy-to-use and non-invasive clinical measurement tool for the assessment of gait parameters in several pathologies. Focusing on stroke individuals, some of the available studies aimed to directly assess and characterize their gait patterns. In contrast, other studies focused...
Source: Sensors - June 29, 2022 Category: Biotechnology Authors: Serena Cerfoglio Claudia Ferraris Luca Vismara Gianluca Amprimo Lorenzo Priano Giuseppe Pettiti Manuela Galli Alessandro Mauro Veronica Cimolin Tags: Review Source Type: research

Sensors, Vol. 22, Pages 4814: Gait Synergy Analysis and Modeling on Amputees and Stroke Patients for Lower Limb Assistive Devices
In conclusion, stroke patients and amputees perform different compensatory mechanisms to adapt to new interlimb and intralimb synergies different from healthy people. LSTM has better synergy modeling and shows a promise for generating trajectories in line with the wearer’s motion for lower limb assistive devices.
Source: Sensors - June 25, 2022 Category: Biotechnology Authors: Feng-Yan Liang Fei Gao Junyi Cao Sheung-Wai Law Wei-Hsin Liao Tags: Article Source Type: research

Sensors, Vol. 22, Pages 4789: A Machine Learning Model for Predicting Sit-to-Stand Trajectories of People with and without Stroke: Towards Adaptive Robotic Assistance
This study presents the recording and analysis of a comprehensive database of full body biomechanics and force data captured during sit-to-stand-to-sit movements in subjects who have and have not experienced stroke. These data were then used in conjunction with simple machine learning algorithms to predict vertical motion trajectories that could be further employed for the control of an assistive robot. A total of 30 people (including 6 with stroke) each performed 20 sit-to-stand-to-sit actions at two different seat heights, from which average trajectories were created. Weighted k-nearest neighbours and linear regression m...
Source: Sensors - June 24, 2022 Category: Biotechnology Authors: Thomas Bennett Praveen Kumar Virginia Ruiz Garate Tags: Article Source Type: research

Sensors, Vol. 22, Pages 4760: A Novel Non-Invasive Thermometer for Continuous Core Body Temperature: Comparison with Tympanic Temperature in an Acute Stroke Clinical Setting
This study aimed to investigate the use of a novel wireless non-invasive heat flux-based thermometer in acute stroke patients admitted to a stroke unit and compare the measurements with the currently used infrared (IR) tympanic temperature readings. The study encompassed 30 acute ischemic stroke patients who underwent continuous measurement (Tcore) with the novel wearable non-invasive CORE device. Paired measurements of Tcore and tympanic temperature (Ttym) by using a standard IR-device were performed 3–5 times/day, yielding a total of 305 measurements. The predicted core temperatures (Tcore) were significant...
Source: Sensors - June 23, 2022 Category: Biotechnology Authors: Milo š Ajčević Alex Buoite Stella Giovanni Furlanis Paola Caruso Marcello Naccarato Agostino Accardo Paolo Manganotti Tags: Article Source Type: research