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Development of a Smart Hallway for Marker-Less Human Foot Tracking and Stride Analysis IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-03-29 Vinod Gutta, Pascal Fallavollita, Natalie Baddour, Edward D. Lemaire
Objective: In this research, a marker-less ‘smart hallway’ is proposed where stride parameters are computed as a person walks through an institutional hallway. Stride analysis is a viable tool for identifying mobility changes, classifying abnormal gait, estimating fall risk, monitoring progression of rehabilitation programs, and indicating progression of nervous system related disorders. Methods: Smart
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Detecting Effect of Levodopa in Parkinson’s Disease Patients Using Sustained Phonemes IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-03-17 Nemuel D. Pah, Mohammod A. Motin, Peter Kempster, Dinesh K. Kumar
Background: Parkinson’s disease (PD) is a multi-symptom neurodegenerative disease generally managed with medications, of which levodopa is the most effective. Determining the dosage of levodopa requires regular meetings where motor function can be observed. Speech impairment is an early symptom in PD and has been proposed for early detection and monitoring of the disease. However, findings from previous
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MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-03-09 Jing Zhang, Deng Liang, Aiping Liu, Min Gao, Xiang Chen, Xu Zhang, Xun Chen
Automatic arrhythmia detection using 12-lead electrocardiogram (ECG) signal plays a critical role in early prevention and diagnosis of cardiovascular diseases. In the previous studies on automatic arrhythmia detection, most methods concatenated 12 leads of ECG into a matrix, and then input the matrix to a variety of feature extractors or deep neural networks for extracting useful information. Under
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IEEE Journal on Translational Engineering in Medicine and Biology publication information IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-03-12
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Stomach 3D Reconstruction Using Virtual Chromoendoscopic Images IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-02-24 Aji Resindra Widya, Yusuke Monno, Masatoshi Okutomi, Sho Suzuki, Takuji Gotoda, Kenji Miki
Gastric endoscopy is a golden standard in the clinical process that enables medical practitioners to diagnose various lesions inside a patient’s stomach. If a lesion is found, a success in identifying the location of the found lesion relative to the global view of the stomach will lead to better decision making for the next clinical treatment. Our previous research showed that the lesion localization
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Rapid Screening of Physiological Changes Associated With COVID-19 Using Soft-Wearables and Structured Activities: A Pilot Study IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-02-11 Luca Lonini, Nicholas Shawen, Olivia Botonis, Michael Fanton, Chadrasekaran Jayaraman, Chaithanya Krishna Mummidisetty, Sung Yul Shin, Claire Rushin, Sophia Jenz, Shuai Xu, John A. Rogers, Arun Jayaraman
Objective: Controlling the spread of the COVID-19 pandemic largely depends on scaling up the testing infrastructure for identifying infected individuals. Consumer-grade wearables may present a solution to detect the presence of infections in the population, but the current paradigm requires collecting physiological data continuously and for long periods of time on each individual, which poses limitations
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Massage Therapy’s Effectiveness on the Decoding EEG Rhythms of Left/Right Motor Imagery and Motion Execution in Patients With Skeletal Muscle Pain IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-02-03 Huihui Li, Kai Fan, Junsong Ma, Bo Wang, Xiaohao Qiao, Yan Yan, Wenjing Du, Lei Wang
Objective: Most of effectiveness assessments of the widely-used Massage therapy were based on subjective routine clinical assessment tools, such as Visual Analogue Scale (VAS) score. However, few studies demonstrated the impact of massage on the Electroencephalograph (EEG) rhythm decoding of Motor imagery (MI) and motion execution (ME) with trunk left/right bending in patients with skeletal muscle
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Intraductal Tissue Sampling Device Designed for the Biliary Tract IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-02-04 Malay S. Patel, Matthew D. Carson, Eric J. Seibel, Lucas R. Meza
Clinical sampling of tissue that is read by a pathologist is currently the gold standard for making a disease diagnosis, but the few minimally invasive techniques available for small duct biopsies have low sensitivity, increasing the likelihood of false negative diagnoses. We propose a novel biopsy device designed to accurately sample tissue in a biliary stricture under fluoroscopy or endoscopic guidance
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mHealth Technology Translation in a Limited Resources Community—Process, Challenges, and Lessons Learned From a Limited Resources Community of Chiang Mai Province, Thailand IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-01-27 Waraporn Boonchieng, Jintana Chaiwan, Bijaya Shrestha, Manash Shrestha, Adam J.O. Dede, Ekkarat Boonchieng
This report aims to provide practical advice about the implementation of a public health monitoring system using both geographic information system technology and mobile health, a term used for healthcare delivery via mobile devices. application amongst household residents and community stakeholders in the limited resource community. A public health monitoring system was implemented in a semi-rural
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Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-02-01 M. Abdallah
Objective: Impedance based biosensing provides a unique, highly sensitive electrical approach to biomolecule detection, cell growth, and other biological events. To date, an impedance change due to the cell growth has been considered as a solution to detect some changes in a cell’s behavior. The impedance change detection is normally measured via an impedance analyzer which is expensive and also cumbersome
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Autonomous Robot for Removing Superficial Traumatic Blood IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-02-02 Baiquan Su, Shi Yu, Xintong Li, Yi Gong, Han Li, Zifeng Ren, Yijing Xia, He Wang, Yucheng Zhang, Wei Yao, Junchen Wang, Jie Tang
Objective : To remove blood from an incision and find the incision spot is a key task during surgery, or else over discharge of blood will endanger a patient’s life. However, the repetitive manual blood removal involves plenty of workload contributing fatigue of surgeons. Thus, it is valuable to design a robotic system which can automatically remove blood on the incision surface. Methods : In this
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Hand-Held Zoom Micro-Imaging System Based on Microfluidic Chip for Point-of-Care Testing (POCT) of Vaginal Inflammation IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-01-26 Ning Yang, Jingxin Peng, Liang Wu, Xue Han, Naila Shaheen, Xiaobo Zou
Background: Vaginitis is a common and very private disease, and the current diagnosis is a frequent go to the hospital for testing. Objective: In order to improve the convenience and speed of detection, in this paper, we have developed a hand-held zoom micro-imaging system based on a microfluidic chip for point-of-care testing (POCT) of vaginal inflammation. Methods: This system consists of a microfluidic
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Pathologic Blood Samples Tolerate Exposure to Vibration and High Turbulence in Simulated Drone Flights, but Plasma Samples Should be Centrifuged After Flight IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-01-20 Karl Arne Johannessen, Nina Kristin Steen Wear, Karin Toska, Morten Hansbø, Jens Petter Berg, Erik Fosse
Objective. Most of the previous studies of drone transport of blood samples examined normal blood samples transported under tranquil air conditions. We studied the effects of 1- and 2-hour drone flights using random vibration and turbulence simulation (10-30 g-force) on blood samples from 16 healthy volunteers and 74 patients with varying diseased. Methods: Thirty-two of the most common analytes were
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A Deep Convolutional Neural Network Method to Detect Seizures and Characteristic Frequencies Using Epileptic Electroencephalogram (EEG) Data IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2021-01-11 Md. Rashed-Al-Mahfuz, Mohammad Ali Moni, Shahadat Uddin, Salem A. Alyami, Matthew A. Summers, Valsamma Eapen
Background: Diagnosing epileptic seizures using electroencephalogram (EEG) in combination with deep learning computational methods has received much attention in recent years. However, to date, deep learning techniques in seizure detection have not been effectively harnessed due to sub-optimal classifier design and improper representation of the time-domain signal. Methods: In this study, we focused
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Registration Techniques for Clinical Applications of Three-Dimensional Augmented Reality Devices IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-12-17 Christopher M. Andrews, Alexander B. Henry, Ignacio M. Soriano, Michael K. Southworth, Jonathan R. Silva
Many clinical procedures would benefit from direct and intuitive real-time visualization of anatomy, surgical plans, or other information crucial to the procedure. Three-dimensional augmented reality (3D-AR) is an emerging technology that has the potential to assist physicians with spatial reasoning during clinical interventions. The most intriguing applications of 3D-AR involve visualizations of anatomy
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Errata to “Quantifying Tremor in Essential Tremor Using Inertial Sensors Validation of an Algorithm” IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-12-22 Patrick Mcgurrin, James Mcnames, Tianxia Wu, Mark Hallett, Dietrich Haubenberger
In the above article [1] , the following disclosures should have appeared. Dietrich Haubenberger is now employed by Neurocrine Biosciences, Inc., San Diego, CA 92130, USA. James McNames is an employee of APDM, Portland, OR 97201, USA, a company that may have a commercial interest in the results of this research and technology. This potential conflict of interest has been reviewed and managed by OHSU
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Quantifying Pathological Synergies in the Upper Extremity of Stroke Subjects With the Use of Inertial Measurement Units: A Pilot Study IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-12-07 Miguel M. C. Bhagubai, Gerjan Wolterink, Anne Schwarz, Jeremia P. O. Held, Bert-Jan F. Van Beijnum, Peter H. Veltink
Background: Stroke is one of the main causes of disability in the world, causing loss of motor function on mainly one side of the body. A proper assessment of motor function is required to help to direct and evaluate therapy. Assessment is currently performed by therapists using observer-based standardized clinical assessment protocols. Sensor-based technologies can be used to objectively quantify
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Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients Using Primary Care Electronic Health Records IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-11-24 Gavin Tsang, Shang-Ming Zhou, Xianghua Xie
A growing elderly population suffering from incurable, chronic conditions such as dementia present a continual strain on medical services due to mental impairment paired with high comorbidity resulting in increased hospitalization risk. The identification of at risk individuals allows for preventative measures to alleviate said strain. Electronic health records provide opportunity for big data analysis
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Assessment of Carotid Arterial Stiffness in Community Settings With ARTSENS® IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-12-03 Jayaraj Joseph, P. M. Nabeel, Sudha Ramachandra Rao, Ramachandran Venkatachalam, Malay Ilesh Shah, Prabhdeep Kaur
Objective: We investigate the field feasibility of carotid stiffness measurement using ARTSENS® Touch and report the first community-level data from India. Method: In an analytical cross-sectional survey among 1074 adults, we measured specific stiffness index ( $\beta $ ), pressure-strain elastic modulus ( $\text{E}_{\text {p}}$ ), arterial compliance (AC), and one-point pulse wave velocity (PWV $_{\beta
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Assessment of Residual Radioactivity by a Comprehensive Wireless, Wearable Device in Thyroid Cancer Patients Undergoing Radionuclide Therapy and Comparison With the Results of a Home Device: A Feasibility Study IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-12-02 R. Gallicchio, D. Scapicchio, A. Nardelli, T. Pellegrino, M. Prisco, P. Mainenti, C. Sirignano, P. Pedicini, G. Storto
Objective : To investigate the feasibility of using a wireless wearable device (WD) in differentiated thyroid cancer (DTC) patients undergoing radionuclide therapy with I-131 (RAI) and protected hospitalization, this study compared the measurements of residual radioactivity obtained with those registered by a permanent environmental home device (HD). Methods : Twenty consecutive patients undergoing
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Novel Technique for Noninvasive Detection of Localized Dynamic Brain Signals by Using Transcranial Static Magnetic Fields IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-11-18 Osamu Hiwaki
The techniques for noninvasive measurement of brain function such as electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS) have been used in diagnosing brain conditions. However, the conventional techniques have critical limitations of spatial or temporal resolution. Here, we developed a novel technique
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Design of a Device for Lower Limb Prophylaxis and Exercise IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-11-09 K. Vinay, Krishna Nagaraj, H. R. Arvinda, V. Vikas, Madhav Rao
The problem of immobility of legs leading to a potentially life threatening condition including deep venous thrombosis (DVT) is well known. The reduced mobility of leg affects a large number of patients in a wide range of clinical scenarios spanning from swelling of the legs to pulmonary embolism. In normal human beings, an elegant system of venous return, both active and passive is responsible for
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A Feasibility Study of Non-Invasive Continuous Estimation of Brachial Pressure Derived From Arterial and Venous Lines During Dialysis IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-11-04 Jill Stewart, Paul Stewart, Thomas Walker, Daniela Viramontes Horner, Bethany Lucas, Kelly White, Andy Muggleton, Mel Morris, Nicholas M. Selby, Maarten W. Taal
Objective: Intradialytic haemodynamic instability is a significant clinical problem, leading to end-organ ischaemia and contributing to morbidity and mortality in haemodialysis patients. Non-invasive continuous blood pressure monitoring is not currently part of routine practice but may aid detection and prevention of significant falls in blood pressure during dialysis. Brachial blood pressure is currently
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Quantifying Tremor in Essential Tremor Using Inertial Sensors—Validation of an Algorithm IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-10-21 Patrick Mcgurrin, James Mcnames, Tianxia Wu, Mark Hallett, Dietrich Haubenberger
Background Assessment of essential tremor is often done by a trained clinician who observes the limbs during different postures and actions and subsequently rates the tremor. While this method has been shown to be reliable, the inter- and intra-rater reliability and need for training can make the use of this method for symptom progression difficult. Many limitations of clinical rating scales can potentially
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A Decision Support System for Diabetes Chronic Care Models Based on General Practitioner Engagement and EHR Data Sharing IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-10-14 Emanuele Frontoni, Luca Romeo, Michele Bernardini, Sara Moccia, Lucia Migliorelli, Marina Paolanti, Alessandro Ferri, Paolo Misericordia, Adriano Mancini, Primo Zingaretti
Objective Decision support systems (DSS) have been developed and promoted for their potential to improve quality of health care. However, there is a lack of common clinical strategy and a poor management of clinical resources and erroneous implementation of preventive medicine. Methods To overcome this problem, this work proposed an integrated system that relies on the creation and sharing of a database
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Quantification of Resting-State Ballistocardiogram Difference Between Clinical and Non-Clinical Populations for Ambient Monitoring of Heart Failure IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-10-08 Isaac Sungjae Chang, Susanna Mak, Narges Armanfard, Jennifer Boger, Sherry L. Grace, Amaya Arcelus, Caroline Chessex, Alex Mihailidis
A ballistocardiogram (BCG) is a versatile bio-signal that enables ambient remote monitoring of heart failure (HF) patients in a home setting, achieved through embedded sensors in the surrounding environment. Numerous methods of analysis are available for extracting physiological information using the BCG; however, most have been developed based on non-clinical subjects. While the difference between
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Side-Channel Sensing: Exploiting Side-Channels to Extract Information for Medical Diagnostics and Monitoring IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-10-06 Aaron Spence, Shaun Bangay
Information within systems can be extracted through side-channels; unintended communication channels that leak information. The concept of side-channel sensing is explored, in which sensor data is analysed in non-trivial ways to recover subtle, hidden or unexpected information. Practical examples of side-channel sensing are well known in domains such as cybersecurity (CYB), but are not formally recognised
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Early Detection of Acute Chest Syndrome Through Electronic Recording and Analysis of Auscultatory Percussion IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-09-30 Bekah Allen, Robert Molokie, Thomas J. Royston
Acute chest syndrome (ACS) is the leading cause of death among people with sickle cell disease. ACS is clinically defined and diagnosed by the presence of a new pulmonary infiltrate on chest imaging with accompanying fever and respiratory symptoms like hypoxia, tachypnea, and shortness of breath. However, the characteristic chest x-ray (CXR) findings necessary for a clinical diagnosis of ACS can be
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Locomo-Net: A Low -Complex Deep Learning Framework for sEMG-Based Hand Movement Recognition for Prosthetic Control IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-09-15 Arvind Gautam, Madhuri Panwar, Archana Wankhede, Sridhar P. Arjunan, Ganesh R. Naik, Amit Acharyya, Dinesh K. Kumar
Background: The enhancement in the performance of the myoelectric pattern recognition techniques based on deep learning algorithm possess computationally expensive and exhibit extensive memory behavior. Therefore, in this paper we report a deep learning framework named ‘Low-Complex Movement recognition-Net’ (LoCoMo-Net) built with convolution neural network (CNN) for recognition of wrist and finger
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Evaluation of the Vibe Actigraph in Patients With Chronic Obstructive Pulmonary Disease: A Pilot Study. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-08-20 Nafeez Syed,Jeremy D Road,Christopher J Ryerson,Jordan A Guenette
Study objective: To validate the Vibe actigraph in assessing sleep-wake patterns compared to polysomnography (PSG) in patients with COPD. Methods: Nine stable COPD patients wore actigraphs while undergoing PSG. The correlation between total sleep time (TST), total sleep period (TSP), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency was determined for corresponding measurements
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Total Iron Measurement in Human Serum With a Novel Smartphone-Based Assay. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-06-26 Michael Serhan,David Jackemeyer,Mindy Long,Mark Sprowls,Ismael Diez Perez,Wolfgang Maret,Fang Chen,Nongjian Tao,Erica Forzani
Background : Abnormally low or high blood iron levels are common health conditions worldwide and can seriously affect an individual’s overall well-being. A low-cost point-of-care technology that measures blood iron markers with a goal of both preventing and treating iron-related disorders represents a significant advancement in medical care delivery systems. Methods: A novel assay equipped with an
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Wearable Device-Independent Next Day Activity and Next Night Sleep Prediction for Rehabilitation Populations. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-08-05 Allison Fellger,Gina Sprint,Douglas Weeks,Elena Crooks,Diane J Cook
Wearable sensor-based devices are increasingly applied in free-living and clinical settings to collect fine-grained, objective data about activity and sleep behavior. The manufacturers of these devices provide proprietary software that labels the sensor data at specified time intervals with activity and sleep information. If the device wearer has a health condition affecting their movement, such as
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A Singular Spectrum Analysis-Based Data-Driven Technique for the Removal of Cardiogenic Oscillations in Esophageal Pressure Signals. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-07-30 Sourav Kumar Mukhopadhyay,Michael Zara,Irene Telias,Lu Chen,Remi Coudroy,Takeshi Yoshida,Laurent Brochard,Sridhar Krishnan
Objective: Assessing the respiratory and lung mechanics of the patients in intensive care units is of utmost need in order to guide the management of ventilation support. The esophageal pressure ( $\boldsymbol {P}_{ \boldsymbol {eso}}$ ) signal is a minimally invasive measure, which portrays the mechanics of the lung and the pattern of breathing. Because of the close proximity of the lung to the beating
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Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-07-23 Federico Wadehn, Thomas Heldt
Objective: Novel applications of transcranial Doppler (TCD) ultrasonography, such as the assessment of cerebral vessel narrowing/occlusion or the non-invasive estimation of intracranial pressure (ICP), require high-quality maximal flow velocity waveforms. However, due to the low signal-to-noise ratio of TCD spectrograms, measuring the maximal flow velocity is challenging. In this work, we propose a
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Performance Evaluation of Mixed Reality Display for Guidance During Transcatheter Cardiac Mapping and Ablation. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-07-03 Michael K Southworth,Jennifer N Avari Silva,Walter M Blume,George F Van Hare,Aarti S Dalal,Jonathan R Silva
Cardiac electrophysiology procedures present the physician with a wealth of 3D information, typically presented on fixed 2D monitors. New developments in wearable mixed reality displays offer the potential to simplify and enhance 3D visualization while providing hands-free, dynamic control of devices within the procedure room. Objective: This work aims to evaluate the performance and quality of a mixed
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Implications of Physiology-Sensitive Gait Exercise on the Lower Limb Electromyographic Activity of Hemiplegic Post-Stroke Patients: A Feasibility Study in Low Resource Settings. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-07-01 Dhaval Solanki,Siddhant Kumar,B Shubha,Uttama Lahiri
Background: Stroke is one of the leading causes of disability with ~80% of post-stroke survivors suffering from gait-related deficits. Conventional gait rehabilitation settings are labor-intensive and need rigorous involvement of clinicians (who use their expertise to decide the dosage of exercise intensity based on patient’s capability). This demands a technology-assisted individualized exercise platform
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A Modular Adjustable Transhumeral Prosthetic Socket for Evaluating Myoelectric Control. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-07-01 Ben W Hallworth,James A Austin,Heather E Williams,Mayank Rehani,Ahmed W Shehata,Jacqueline S Hebert
Novel myoelectric control strategies may yield more robust, capable prostheses which improve quality of life for those affected by upper-limb loss; however, the development and translation of such strategies from an experimental setting towards daily use by persons with limb loss is a slow and costly process. Since prosthesis functionality is highly dependent on the physical interface between the user’s
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Rapid, Low-Cost Dielectrophoretic Diagnosis of Bladder Cancer in a Clinical Setting. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-06-24 Rashedul Hoque,Hugh Mostafid,Michael Pycraft Hughes
Bladder cancer is the 9th most common cancer worldwide. Diagnosing bladder cancer typically involves highly invasive cystoscopy, with followup monitored using uteroscopy. Molecular methods have been developed as an adjunct to this, but tend to be expensive or require expert operator input. Here we present a study of the use of dielectrophoresis (DEP) of voided cells from eight cancer-presenting patients
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Development of a Patch-Type Flexible Oxygen Partial Pressure Sensor. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-06-29 Yuta Katayama,Yuta Fujioka,Kosuke Tsukada
Oxygen concentration in living organisms is one of the important vital indicators in emergency care and bedside medical settings. However, the oximetry method has limitations: the measurement site is limited to the tissue containing blood and the absolute value of oxygen concentration cannot be measured. To overcome these limitations, in this work, we develop a new oxygen sensor that can directly measure
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Teleoperation of Collaborative Robot for Remote Dementia Care in Home Environments. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-06-15 Honghao Lv,Geng Yang,Huiying Zhou,Xiaoyan Huang,Huayong Yang,Zhibo Pang
As a senile chronic, progressive and currently incurable disease, dementia has an enormous impact on society and life quality of the elderly. The development of teleoperation technology has changed the traditional way of care delivery and brought a variety of novel applications for dementia care. In this paper, a telerobotic system is presented which gives the caregivers the capability of assisting
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Unified Open Hardware Platform for Digital X-Ray Devices; its Conceptual Model and First Implementation. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-06-04 F Aytac Durmaz,Altay Brusan,Cengizhan Ozturk
Background: Digital radiography devices are still the gold standard for diagnosis or therapy guidance in medicine. Despite the similarities between all direct digital x-ray systems, researchers and new companies face significant challenges during the development phase of innovative x-ray devices; each component is manufactured independently, guidance towards device integration from manufacturers is
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Ultrasound-Based Attenuation Imaging for the Non-Invasive Quantification of Liver Fat - A Pilot Study on Feasibility and Inter-Observer Variability. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-06-10 Daniel Jesper,Daniel Klett,Barbara Schellhaas,Lukas Pfeifer,Moritz Leppkes,Maximilian Waldner,Markus F Neurath,Deike Strobel
Attenuation imaging is a novel, ultrasound-based technique to objectively detect and quantify liver steatosis. In this study, we evaluated the performance and inter-observer variability of attenuation imaging and compared it to a known quantification method of liver fat, the hepatorenal index (HRI). Two observers measured attenuation coefficients (AC) in an attenuation phantom, 20 healthy volunteers
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Accurate Fiducial Point Detection Using Haar Wavelet for Beat-by-Beat Blood Pressure Estimation. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-06-05 Muskan Singla,Syed Azeemuddin,Prasad Sistla
Pulse Arrival Time (PAT) derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) for cuff-less Blood Pressure (BP) measurement has been a contemporary and widely accepted technique. However, the features extracted for it are conventionally from an isolated pulse of ECG and PPG signals. As a result, the estimated BP is intermittent. Objective: This paper presents feature extraction from each
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Convex Representations Using Deep Archetypal Analysis for Predicting Glaucoma. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-05-28 Anshul Thakur,Michael Goldbaum,Siamak Yousefi
Goal: The purpose of this study was to identify clinically relevant patterns of glaucomatous vision loss through convex representation to predict glaucoma several years prior to disease onset. Methods: We developed a deep archetypal analysis to identify patterns of glaucomatous vision loss, and then projected visual fields over the identified patterns. Projections provided a representation that was
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DFENet: Deep Feature Enhancement Network for Accurate Calculation of Instantaneous Wave-Free Ratio. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-06-03 Jiping Li,Liang Song,Heye Zhang
Accurate iFR calculation can provide important clinical information for intracoronary functional assessment without administration of adenosine, which needs to locate object points in the pressure waveforms: peak, the dichrotic notch and the pressure nadir at the end of diastole. We propose a DFENet that is capable of locating object points to calculate iFR accurately. We first design a SFRA into DFENet
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BioMeT and Algorithm Challenges: A Proposed Digital Standardized Evaluation Framework. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-05-28 Alan Godfrey,Jennifer C Goldsack,Pamela Tenaerts,Andrea Coravos,Clara Aranda,Azid Hussain,Marcos E Barreto,Fraser Young,Rodrigo Vitorio
Technology is advancing at an extraordinary rate. Continuous flows of novel data are being generated with the potential to revolutionize how we better identify, treat, manage, and prevent disease across therapeutic areas. However, lack of security of confidence in digital health technologies is hampering adoption, particularly for biometric monitoring technologies (BioMeTs) where frontline healthcare
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A Review on Serious Games for Dementia Care in Ageing Societies. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-05-28 Huansheng Ning,Rongyang Li,Xiaozhen Ye,Yudong Zhang,Lu Liu
Dementia is a severe disease threatening ageing societies, which not only causes great harm to patients both physically and psychologically but also places a heavy burden on patients’ families. Medications have been used for the treatment of dementia but with little success. However, serious games, as a new form of dementia therapy, stand out from various therapeutic methods and pave the way for dementia
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Measuring Gait Variables Using Computer Vision to Assess Mobility and Fall Risk in Older Adults With Dementia. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-05-28 Kimberley-Dale Ng,Sina Mehdizadeh,Andrea Iaboni,Avril Mansfield,Alastair Flint,Babak Taati
Fall risk is high for older adults with dementia. Gait impairment contributes to increased fall risk, and gait changes are common in people with dementia, although the reliable assessment of gait is challenging in this population. This study aimed to develop an automated approach to performing gait assessments based on gait data that is collected frequently and unobtrusively, and analysed using computer
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Determination of Clinical Parameters Sensitive to Functional Voice Disorders Applying Boosted Decision Stumps. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-05-22 Patrick Schlegel,Andreas M Kist,Marion Semmler,Michael Dollinger,Melda Kunduk,Stephan Durr,Anne Schutzenberger
Background: Various voice assessment tools, such as questionnaires and aerodynamic voice characteristics, can be used to assess vocal function of individuals. However, not much is known about the best combinations of these parameters in identification of functional dysphonia in clinical settings. Methods: This study investigated six scores from clinically commonly used questionnaires and seven acoustic
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A 12-Lead ECG-Based System With Physiological Parameters and Machine Learning to Identify Right Ventricular Hypertrophy in Young Adults. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-05-21 Gen-Min Lin,Henry Horng-Shing Lu
Objective: The presence of right ventricular hypertrophy (RVH) accounts for approximately 5-10% in young adults. The sensitivity estimated by commonly used 12-lead electrocardiographic (ECG) criteria for identifying the presence of RVH is under 20% in the general population. The aim of this study is to develop a 12-lead ECG system with the related information of age, body height and body weight via
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Intubation Containment System for Improved Protection From Aerosolized Particles During Airway Management. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-05-11 Russell K Gore,Christopher Saldana,David W Wright,Adam M Klein
Objectives: Worldwide efforts to protect front line providers performing endotracheal intubation during the COVID-19 pandemic have led to innovative devices. Authors evaluated the aerosol containment effectiveness of a novel intubation aerosol containment system (IACS) compared with a recently promoted intubation box and no protective barrier. Methods: In a simulation center at the authors’ university
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Integrated Development Environment for EEG-Driven Cognitive-Neuropsychological Research. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-05-06 Shoham Jacobsen,Oded Meiron,David Yoel Salomon,Nir Kraizler,Hagai Factor,Efraim Jaul,Elishai Ezra Tsur
Background: EEG-driven research is paramount in cognitive-neuropsychological studies, as it provides a non-invasive window to the underlying neural mechanisms of cognition and behavior. A myriad collection of software and hardware frameworks has been developed to alleviate some of the technical barriers involved in EEG-driven research. Methods: we propose an integrated development environment which
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Vibrotactile -Feedback Device for Postural Balance Among Malocclusion Patients. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-04-27 Bhornsawan Thanathornwong,Wattana Jalayondeja
Multiple studies have suggested that some associations exist between occlusal factors and postural alterations. OBJECTIVES This study aimed to evaluate the effectiveness of a vibrotactile posture trainer device, comprised a wearable device containing an accelerometer sensor to measure the angle of the neck flexion (input) and provided real-time vibrotactile biofeedback (output) for postural balance
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3D Motion Estimation of Left Ventricular Dynamics Using MRI and Track-to-Track Fusion. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-04-24 Kumaradevan Punithakumar,Ismail Ben Ayed,Abraam S Soliman,Aashish Goela,Ali Islam,Shuo Li,Michelle Noga
Objective: This study investigates the estimation of three dimensional (3D) left ventricular (LV) motion using the fusion of different two dimensional (2D) cine magnetic resonance (CMR) sequences acquired during routine imaging sessions. Although standard clinical cine CMR data is inherently 2D, the actual underlying LV dynamics lies in 3D space and cannot be captured entirely using single 2D CMR image
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An Electrocardiographic System With Anthropometrics via Machine Learning to Screen Left Ventricular Hypertrophy among Young Adults. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-04-24 Gen-Min Lin,Kiang Liu
The prevalence of physiological and pathological left ventricular hypertrophy (LVH) among young adults is about 5%. A use of electrocardiographic (ECG) voltage criteria and machine learning for the ECG parameters to identify the presence of LVH is estimated only 20-30% in the general population. The aim of this study is to develop an ECG system with anthropometric data using machine learning to increase
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Real-Time Lung Tumor Tracking Using a CUDA Enabled Nonrigid Registration Algorithm for MRI. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-04-24 Nazanin Tahmasebi,Pierre Boulanger,Jihyun Yun,Gino Fallone,Michelle Noga,Kumaradevan Punithakumar
OBJECTIVE This study intends to develop an accurate, real-time tumor tracking algorithm for the automated radiation therapy for cancer treatment using Graphics Processing Unit (GPU) computing. Although a previous moving mesh based tumor tracking approach has been shown to be successful in delineating the tumor regions from a sequence of magnetic resonance image, the algorithm is computationally intensive
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Multi-Source Transfer Learning via Ensemble Approach for Initial Diagnosis of Alzheimer's Disease. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-04-23 Yun Yang,Xinfa Li,Pei Wang,Yuelong Xia,Qiongwei Ye
Alzheimer's disease (AD) is one of the most common progressive neurodegenerative diseases, and the number of AD patients has increased year after year with the global aging trend. The onset of AD has a long preclinical stage. If doctors can make an initial diagnosis in the mild cognitive impairment (MCI) stage, it is possible to identify and screen those at a high-risk of developing full-blown AD,
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A Composite Fabric-Based Soft Rehabilitation Glove With Soft Joint for Dementia in Parkinson's Disease. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-03-19 Yinglong Chen,Xinyan Tan,Di Yan,Zengmeng Zhang,Yongjun Gong
A kind of wearable exoskeleton soft rehabilitation glove is proposed for the dementia in Parkinson's disease (PD) patients with loss of hand function, limited range of motion, and insufficient finger muscle strength to carry out rehabilitation exercise training in a passive or auxiliary way. A novel soft joint structure based on composite fabric material is introduced for the design of the soft glove
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A Multi-Task Group Bi-LSTM Networks Application on Electrocardiogram Classification. IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2019-11-12 Qiu-Jie Lv,Hsin-Yi Chen,Wei-Bin Zhong,Ying-Ying Wang,Jing-Yan Song,Sai-Di Guo,Lian-Xin Qi,Calvin Yu-Chian Chen
BACKGROUND Cardiovascular diseases (CVD) are the leading cause of death globally. Electrocardiogram (ECG) analysis can provide thoroughly assessment for different CVDs efficiently. We propose a multi-task group bidirectional long short-term memory (MTGBi-LSTM) framework to intelligent recognize multiple CVDs based on multi-lead ECG signals. METHODS This model employs a Group Bi-LSTM (GBi-LSTM) and
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Novel EM Guided Endovascular Instrumentation for In Situ Endograft Fenestration IEEE J. Transl. Eng. Health Med. (IF 2.53) Pub Date : 2020-03-04 S. Condino, R. Piazza, R. M. Viglialoro, D. M. Mocellin, G. Turini, R. N. Berchiolli, F. Micheletti, F. Rossi, R. Pini, V. Ferrari, M. Ferrari
Objective: This work aims at providing novel endovascular instrumentation to overcome current technical limitations of in situ endograft fenestration including challenges in targeting the fenestration site under fluoroscopic control and supplying mechanical support during endograft perforation. Technology: Novel electromagnetically trackable instruments were developed to facilitate the navigation of