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IEEE Journal of Translational Engineering in Health and Medicine

Zhuo Chen, Elmer Salazar, Kyle Marple, Sandeep R Das, Alpesh Amin, Daniel Cheeran, Lakshman S Tamil, Gopal Gupta
Management of heart failure is a major health care challenge. Healthcare providers are expected to use best practices described in clinical practice guidelines, which typically consist of a long series of complex rules. For heart failure management, the relevant guidelines are nearly 80 pages long. Due to their complexity, the guidelines are often difficult to fully comply with, which can result in suboptimal medical practices. In this paper, we describe a heart failure treatment adviser system that automates the entire set of rules in the guidelines for heart failure management...
2018: IEEE Journal of Translational Engineering in Health and Medicine
David Quintero, Emma Reznick, Daniel J Lambert, Siavash Rezazadeh, Leslie Gray, Robert D Gregg
This paper presents a potential solution to the challenge of configuring powered knee-ankle prostheses in a clinical setting. Typically, powered prostheses use impedance-based control schemes that contain several independent controllers which correspond to consecutive periods along the gait cycle. This control strategy has numerous control parameters and switching rules that are generally tuned by researchers or technicians and not by a certified prosthetist. We propose an intuitive clinician control interface (CCI) in which clinicians tune a powered knee-ankle prosthesis based on a virtual constraint control scheme, which tracks desired periodic joint trajectories based on a continuous measurement of the phase (or progression) of gait...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Sam Darvishi, Alireza Gharabaghi, Michael C Ridding, Derek Abbott, Mathias Baumert
There is evidence that 15-30% of the general population cannot effectively operate brain-computer interfaces (BCIs). Thus the BCI performance predictors are critically required to pre-screen participants. Current neurophysiological and psychological tests either require complicated equipment or suffer from subjectivity. Thus, a simple and objective BCI performance predictor is desirable. Neurofeedback (NFB) training involves performing a cognitive task (motor imagery) instructed via sensory stimuli and re-adjusted through ongoing real-time feedback...
2018: IEEE Journal of Translational Engineering in Health and Medicine
George W Carpenter, Holly G Myers, Eric A Sherer, Katie A Evans, D Patrick O'Neal
An optically-based injection control system has been developed for preclinical use for an intravenous drug delivery application. Current clinical drug delivery for oncology typically provides for intravenous administration without an awareness of achieved plasma concentration, yet interpatient variability produces consequences ranging from toxicity to ineffectual treatments. We report a closed-loop injection system integrating a pulse-photoplethysmograph to measure the concentration of an injected agent in the circulating blood system using a previously described technique...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Qi Wang, Annick Timmermans, Wei Chen, Jie Jia, Li Ding, Li Xiong, Jifeng Rong, Panos Markopoulos
The objective is to evaluate to which extent that Zishi a garment equipped with sensors that can support posture monitoring can be used in upper extremity rehabilitation training of stroke patients. Seventeen stroke survivors (mean age: 55 years old, SD =13.5) were recruited in three hospitals in Shanghai. Patients performed 4 tasks (analytical shoulder flexion, functional shoulder flexion placing a cooking pot, analytical flexion in the scapular plane, and functional flexion in the scapular plane placing a bottle of water) with guided feedback on a tablet that was provided through inertial sensors embedded in the Zishi system at the scapula and the thoracic spine region...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Kenny Chen, Paolo Gabriel, Abdulwahab Alasfour, Chenghao Gong, Werner K Doyle, Orrin Devinsky, Daniel Friedman, Patricia Dugan, Lucia Melloni, Thomas Thesen, David Gonda, Shifteh Sattar, Sonya Wang, Vikash Gilja
Reliable posture labels in hospital environments can augment research studies on neural correlates to natural behaviors and clinical applications that monitor patient activity. However, many existing pose estimation frameworks are not calibrated for these unpredictable settings. In this paper, we propose a semi-automated approach for improving upper-body pose estimation in noisy clinical environments, whereby we adapt and build around an existing joint tracking framework to improve its robustness to environmental uncertainties...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Bijan Siassi, Mahmood Ebrahimi, Shahab Noori, Shuyang Sheng, Debjit Ghosh, Istvan Seri
There is a great need for training in pediatric echocardiography. In addition to physicians being trained in pediatric cardiology and echocardiography technologists, neonatologist, pediatric intensivists, and other health care professionals may be interested in such training. Since, there is limited opportunity of training on live patients, echocardiographic simulators may be of help. No simulator with complete range of echocardiographic modalities is available for neonates and infants. The aim of this project was to develop a mannequin-based echocardiographic simulator capable of simulating full range of pediatric 2D, color flow Doppler, spectral Doppler, and M-mode echocardiograms...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Joseph R Scalea, Stephen Restaino, Matthew Scassero, Gil Blankenship, Stephen T Bartlett, Norman Wereley
Organ transportation has yet to be substantially innovated. If organs could be moved by drone, instead of ill-timed commercial aircraft or expensive charter flights, lifesaving organs could be transplanted more quickly. A modified, six-rotor UAS was used to model situations relevant to organ transportation. To monitor the organ, we developed novel technologies that provided the real-time organ status using a wireless biosensor combined with an organ global positioning system. Fourteen drone organ missions were performed...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Xiaodong Yang, Dou Fan, Aifeng Ren, Nan Zhao, Zhiya Zhang, Fangming Hu, Weigang Wang, Masood Ur Rehman, Jie Tian
A non-intrusive sleep apnea detection system using a C-Band channel sensing technique is proposed to monitor sleep apnea syndrome in real time. The system utilizes perturbations of RF signals to differentiate between patient's breathing under normal and sleep apnea conditions. The peak distance calculation is used to obtain the respiratory rates. A comparison of the datasets generated by the proposed method and a wearable sensor is made using a concordance correlation coefficient to establish its accuracy. The results show that the proposed sensing technique exhibits high accuracy and robustness, with more than 80% concordance with the wearable breathing sensor...
2018: IEEE Journal of Translational Engineering in Health and Medicine
An-Ti Chiang, Qi Chen, Yao Wang, Mei R Fu
Using Kinect sensors to monitor and provide feedback to patients performing intervention or rehabilitation exercises is an upcoming trend in healthcare. However, the joint positions measured by the Kinect sensor are often unreliable, especially for joints that are occluded by other parts of the body. Also, users' motion sequences differ significantly even when doing the same exercise and are not temporally aligned, making the evaluation of the correctness of their movement challenging. This paper aims to develop a Kinect-based intervention system, which can guide the users to perform the exercises more effectively...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Pubudu N Pathirana, M Sajeewani Karunarathne, Gareth L Williams, Phan T Nam, Hugh Durrant-Whyte
Wearable inertial measurement units (IMU) measuring acceleration, earth magnetic field, and gyroscopic measurements can be considered for capturing human skeletal postures in real time. Number of movement disorders require accurate and robust estimation of the human joint pose. Though these movements are inherently slow, the accuracy of estimation is vital as many subtle moment patterns, such as tremor are useful to capture under many assessments scenarios. Also, as the end user is a patient with movement disabilities, the practical wearability aspects impose stringent requirements such as the use of minimal number of sensors as well as positioning them in conformable areas of the human body; particularly for longer term monitoring...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Mohsen Nabian, Yu Yin, Jolie Wormwood, Karen S Quigley, Lisa F Barrett, Sarah Ostadabbas
Electrocardiogram, electrodermal activity, electromyogram, continuous blood pressure, and impedance cardiography are among the most commonly used peripheral physiological signals (biosignals) in psychological studies and healthcare applications, including health tracking, sleep quality assessment, disease early-detection/diagnosis, and understanding human emotional and affective phenomena. This paper presents the development of a biosignal-specific processing toolbox (Bio-SP tool) for preprocessing and feature extraction of these physiological signals according to the state-of-the-art studies reported in the scientific literature and feedback received from the field experts...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Antonia E Curtin, Kevin V Burns, Alan J Bank, Theoden I Netoff
We developed an automated approach for QRS complex detection and QRS duration (QRSd) measurement that can effectively analyze multichannel electrocardiograms (MECGs) acquired during abnormal conduction and pacing in heart failure and cardiac resynchronization therapy (CRT) patients to enable the use of MECGs to characterize cardiac activation in such patients. The algorithms use MECGs acquired with a custom 53-electrode investigational body surface mapping system and were validated using previously collected data from 58 CRT patients...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Atam P Dhawan
Point-of-Care Technologies (POCT) in Healthcare have emerged as a potential pathway in global and resource-limited environments towards improving access to healthcare with emphasis on preventive, personalized and precision medicine. The potential uses for POC technologies by patients or clinicians are many-from home-based monitoring to semi-managed and clinical inpatient healthcare. However, it is yet to be proven precisely what technologies are necessary or how they should be used to make an impact in improving access to quality healthcare...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Fayez Alruwaili, Kim Cluff, Jacob Griffith, Hussam Farhoud
This paper focuses on the development of a passive, lightweight skin patch sensor that can measure fluid volume changes in the heart in a non-invasive, point-of-care setting. The wearable sensor is an electromagnetic, self-resonant sensor configured into a specific pattern to formulate its three passive elements (resistance, capacitance, and inductance). In an animal model, a bladder was inserted into the left ventricle (LV) of a bovine heart, and fluid was injected using a syringe to simulate stoke volume (SV)...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Andrew Lowe, Timothy H Oh, Ralph Stewart
Atrial fibrillation (Afib) contributes significantly to overall cardiovascular risk. Widespread screening for Afib in primary care is sometimes performed by palpation, but suffers from low accuracy and is dependent on clinician experience. Algorithms implemented on oscillometric blood pressure devices can detect Afib with high sensitivity and specificity, but information on factors affecting accuracy is scant. Concurrent diagnostic electrocardiogram (ECG) and oscillometry were measured in participants in ECG clinics at two sites...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Rohan Joshi, Bart L Bierling, Xi Long, Janna Weijers, Loe Feijs, Carola Van Pul, Peter Andriessen
Continuously monitoring body movement in preterm infants can have important clinical applications since changes in movement-patterns can be a significant marker for clinical deteriorations including the onset of sepsis, seizures, and apneas. This paper proposes a system and method to monitor body movement of preterm infants in a clinical environment using ballistography. The ballistographic signal (BSG) is acquired using a thin and a film-like sensor that is placed underneath an infant. Manual annotations based on video-recordings served as a reference standard for identifying movement...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Christos P Loizou, Dimitrios Matamis, Giorgos Minas, Theodoros Kyprianou, Christakis D Loizou, Eleni Soilemezi, Entela Kotco, Constantinos S Pattichis
Measurements of ultrasound diaphragmatic motion, amplitude, force, and velocity of contraction may provide important and essential information about diaphragmatic fatigue, weakness, or paralysis. In this paper, we propose and evaluate a semi-automated analysis system for measuring the diaphragmatic motion and estimating the maximum relaxation rate (MRR_SAUS) from ultrasound M-mode images of the diaphragmatic muscle. The system was evaluated on 27 M-mode ultrasound images of the diaphragmatic muscle [20 with no resistance (NRES) and 7 with resistance (RES)]...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Jingting Yao, S Tridandapani, W F Auffermann, C A Wick, P T Bhatti
To more accurately trigger data acquisition and reduce radiation exposure of coronary computed tomography angiography (CCTA), a multimodal framework utilizing both electrocardiography (ECG) and seismocardiography (SCG) for CCTA prospective gating is presented. Relying upon a three-layer artificial neural network that adaptively fuses individual ECG- and SCG-based quiescence predictions on a beat-by-beat basis, this framework yields a personalized quiescence prediction for each cardiac cycle. This framework was tested on seven healthy subjects (age: 22-48; m/f: 4/3) and eleven cardiac patients (age: 31-78; m/f: 6/5)...
2018: IEEE Journal of Translational Engineering in Health and Medicine
Zhe Wang, Yu Zheng, David C Zhu, Andrea C Bozoki, Tongtong Li
This paper proposes a robust method for the Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal control subject classification under size limited fMRI data samples by exploiting the brain network connectivity pattern analysis. First, we select the regions of interest (ROIs) within the default mode network and calculate the correlation coefficients between all possible ROI pairs to form a feature vector for each subject. Second, we propose a regularized linear discriminant analysis (LDA) approach to reduce the noise effect due to the limited sample size...
2018: IEEE Journal of Translational Engineering in Health and Medicine
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