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An Integrated Model of Patient and Staff Satisfaction Using Queuing Theory

A. Komashie, A. Mousavi, P.J. Clarkson, T. Young

This paper investigates the connection between patient satisfaction, waiting time, staff satisfaction and service time. It uses a variety of models to enable improvement against experiential and operational health service goals. Patient satisfaction levels are estimated using a model based on waiting (waiting times)…

Authors

See complete bios of the authors in the full version of this article.

A KomashieA Komashie
Dr. Komashie is currently at Wycliffe Hall College, Oxford University and affiliated with the Engineering Design Centre in Cambridge University where he worked at a Postdoctoral Researcher. His research interests are in the application of Queuing Theory, Discrete Event Simulation, Design Process, Complexity and Systems Thinking for improving healthcare delivery.

A MousaviA Mousavi
Dr. Mousavi is a Senior Lecturer and the Head of the Systems Engineering Research Group at Brunel University. His research interests are in Mathematical Modelling and Simulation, Applied Control and Computing.

P J ClarksonP J Clarkson
Dr. Clarkson is the Director of the Engineering Design Centre in the Engineering Department of Cambridge University, UK. His research interests are in the general area of engineering design, particularly the development of design methodologies to address specific design issues, like process management, change management, healthcare design and inclusive design.

T YoungT Young
Dr. Young is Professor of Healthcare Systems at Brunel University, Uxbridge, UK. His research interests are the organization and delivery of care and the role and value of technology. He is also a leader of the Cumberland Initiative; a collaboration between health, industry and academia, committed to building a national Centre in services and systems excellence.



Principal Dynamic Mode Analysis of EEG Data for Assisting the Diagnosis of Alzheimer’s Disease

Y. Kang, J. Escudero, D. Shin, E. Ifeachor, V. Marmarelis

Alzheimer’s disease (AD) is currently the most common neurodegenerative disorder in the western world and in the future its incidence is expected to double every 20 years. Because a definitive diagnosis can only be made by autopsy and AD pathology could start years before the first symptoms, there is a need for objective, non-invasive and affordable means to support clinicians in the detection…

Authors

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Y KangY Kang
Ms. Kang is currently pursuing a PhD degree with the Biomedical Simulations Resource (BMSR), University of Southern California, CA, USA. Her research interests include biomedical signal processing, computational modeling of dynamic physiological systems, with the focus on improved clinical diagnosis.

J EscuderoJ Escudero
Dr. Escudero is a tenure-track faculty member (Chancellor’s Fellow) at the University of Edinburgh, UK. His research interests include biomedical signal processing, multiway decompositions, graph theory and pattern recognition in clinical applications.

D ShinD Shin
Dr. Shin is a senior research associate at the Department of Biomedical Engineering of the University of Southern California. His primary research interests are: statistical signal processing, linear and nonlinear dynamic modeling of biomedical systems, with special focus on multi-input/multi-output and closed-loop modeling with applications to neural information processing and physiological autoregulation.

E IfeachorE Ifeachor
Dr. Ifeachor is co-editor in chief of the journal Source Code for Biology & Medicine. His current research includes subject-specific bio data analysis for patient-specific early diagnosis and predictive healthcare in the areas of dementia, Parkinson’s disease, brain injury in the early stages of life and cancer.

V MarmarelisV Marmarelis
Dr. Marmarelis is a Professor of Biomedical Engineering at USC and co-Director of the Biomedical Simulations Resource, a research center funded by NIH. His research interests are dynamic nonlinear modeling of biomedical systems; neural information processing; modeling of physiological autoregulation; multimodal ultrasound tomography (MUT) for diagnostic imaging; and model-based diagnostic physiomarkers.



Development of Point of Care Testing Device for Neurovascular Coupling from Simultaneous Recording of EEG and NIRS During Anodal Transcranial Direct Current Stimulation

U. Jindal, M. Sood, A. Dutta, S.R. Chowdhury

This paper presents a point-of-care testing device for bedside measurement of cerebral blood flow and cerebrovascular reserve. The device detects neurovascular coupling (NVC) from simultaneous recording of electroencephalogram and near infra red spectroscopy during anodal transcranial direct current stimulation (tDCS). Studies in healthy subjects and stroke survivors…

Authors

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U JindalU Jindal
Mr. Jindal is pursuing a M.S. degree in Electronics and Communication Engineering from the International Institute of Information Technology, Hyderabad, India. His research interests involve the development of embedded systems for biomedical applications.

M SoodM Sood
Ms. Sood is pursuing a M.S. degree in Electronics and Communication Engineering from the International Institute of Information Technology, Hyderabad, India. Her research interests involve the development of solutions to healthcare needs and embedded system design.

A DuttaA Dutta
Dr. Dutta is is currently the Principal Investigator of the Institut national de recherche en informatique et en automatique – INRIA’s NeuroPhys4NeuroRehab project in the DEMAR research group of the Montpellier Laboratory of Informatics, Robotics, and Microelectronics.

SR ChowdhurySR Chowdhury
Dr. Chowdhury is currently an Assistant Professor at the Centre for VLSI and Embedded Systems Technology, IIIT, Hyderabad, India. His research interests span around the development of Biomedical Embedded Systems, VLSI architectures and ASIC design of intelligent signal processing circuits.

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Published Articles

Automated Lung Segmentation and Image Quality Assessment for Clinical 3-D/4-D-Computed Tomography

J. Wei, G. Li

4-D-computed tomography (4DCT) provides not only a new dimension of patient-specific information for radiation therapy planning and treatment, but also a challenging scale of data volume to process and analyze. Manual analysis using existing 3-D tools is unable to keep up with vastly increased 4-D data volume, automated processing and analysis are thus needed to process 4DCT data effectively and efficiently…

Authors

See complete bios of the authors in the full version of this article.

J WeiJ Wei
Mr. Wei is currently an Associate Professor with the Department of Computer Science, City College of New York, New York, NY, USA. His research interests include multimodal computing, signal/image/video processing, computer vision, machine learning, and medical imaging.

G LiG Li
Mr. Li is currently an Assistant Attending Physicist with the Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. His research interests include multimodal image-guided radiotherapy and radiosurgery, motion management with 4-D imaging, and 4-D treatment planning.

Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning

D. Chakraborty, U. Maulik

Microarrays have now gone from obscurity to being almost ubiquitous in biological research. At the same time, the statistical methodology for microarray analysis has progressed from simple visual assessments of results to novel algorithms for analyzing changes in expression profiles. In a micro-RNA (miRNA) or gene-expression profiling experiment…

Authors

See complete bios of the authors in the full version of this article.

D ChakrabortyD Chakraborty
Mr. Chakraborty has a master’s degree in computer science and engineering from Bengal Engineering College, Howrah, India. He is currently an Associate Professor with the Department of Electronics and Communication Engineering at Murshidabad College of Engineering and Technology. His research interests include supervised and semisupervised learning, pattern classification, remote sensing, and bioinformatics.

U MaulikU Maulik
Dr. Maulik has been a professor with the Department of Computer Science and Engineering, Jadavpur University, Kolkata, India, since 2004. He has co-authored seven books and over 250 research publications. His research interests include computational intelligence, bioinformatics, combinatorial optimization, pattern recognition, and data mining.

Design, Fabrication and Experimental Validation of Novel Flexible Silicon-based Dry Sensors for Electroencephalography Signal Measurements

Y.H. Yu, S. W. Lu, L. D. Liao, C. T. Lin

Many electroencephalography (EEG) sensors, including conventional wet and dry sensors, use materials that can cause skin irritation and discomfort. To overcome this drawback, this study reports on the design and human testing of a SGS-certified, silicon-based dry-contact EEG sensor. In addition to being non-irritating, the acicular sensors are lightweight, flexible, and capable of easily fitting to the scalp…

Editorial Comments

On recent paper of Yi-Shin Yu et al., It is quite obvious that the author as well as the reviewer(s) are confusing “silicon” as “silicone”, throughout the entire session of this paper. As is known well, “silicon” (Si26) is an atomic substance at mid of the periodic table and brother of carbon and germanium, basic material of semiconductor which supports entire human informatics world now, while “silicone” is an alias of (poly)alchylsiloxian, typically known such as “silicone-oil” and/or “silicone-rubber”, where (poly)olefin family materials are reconstructed by substituting carbon (C12) with silicon (Si26). Si as single crystal is a light but hard, diamond-like material which can make even a knife, silicone could be staffed as a soft (in some case very soft like animal soft tissue). Yu in his paper obviously speaks and uses a special, conductivity gifted silicone rubber as soft, deformable skin-electrode to obtain certain (but somewhat well known) affordable result. The issue, or rather a problem, is not the essential content of his paper but his (or the all-of-authors’) confusion in terminology, however, more problematic is that the reviewer(s) of this paper for acceptance for JTEHM publication ALSO repeated this confusion, or couldn’t point-out that confusion at all. Here I would like to recommend to the editor and author to once withdraw this paper and resubmit it using correct terminology throughout the paper including the title. It is not an issue of typological errata later to be corrected just with one line “errata” comment but an issue essentially stress the dignity of JTEHM. Here I would ask editor a brave but important decision.

The “silicone and silicone” issues are explained here:

Yasuhito Takeuchi, PhD, Visiting Professor, Department of Renal and Urologic Surgery, Asahikawa Medical University. y.takeuchi@ieee.org

Authors

See complete bios of the authors in the full version of this article.

YH YuYH Yu
Mr. Yu is pursuing a Ph.D. degree from the Institute of Electrical Control Engineering and Brain Research Center, National Chiao Tung University, Hsinchu, Taiwan. His research interests include brain research, biomedical signal processing, brain–computer interfaces and biomedical circuits and systems.

SW LuSW Lu
Mr. Lu is currently an Assistant Researcher with the Brain Research Center, National Chiao-Tung University, Hsinchu, where he is involved in electro-neurophysiology and biomedical signal processing.

LD LiaoLD Liao
Dr. Liao is a Senior Research Scientist and head of the Neurovascular Imaging Laboratory in Singapore Institute for Neurotechnology (SINAPSE) at National University of Singapore. His research interests include neuroimaging, cerebral neuroscience, cognitive neuroscience, in vivo optical microscopy, advanced sensing techniques and design of optical system.

CT LinCT Lin
Dr. Lin is the Provost, Chair Professor of Electrical and Computer Engineering, Professor of the Institute of Imaging and Biomedical Photonics, and Director of Brain Research Center at NCTU. Currently, he is the Editor-in-Chief of the IEEE Transactions on Fuzzy Systems.

Monitoring and Analysis of Respiratory Patterns Using Microwave Doppler Radar

Y. S. Lee, P. N. Pathirana, C. L. Steinfort, T. Caelli

Non-contact detection characteristic of Doppler radar provides an unobtrusive means of respiration detection and monitoring. This avoids additional preparations such as physical sensor attachment or special clothing which can be useful for certain healthcare applications. Furthermore, robustness of Doppler radar against environmental factors such as light, ambient temperature, interference from other signals…

Authors

See complete bios of the authors in the full version of this article.

YS LeeYS Lee
Mr. Lee is currently pursuing his Ph.D. degree at Deakin University, Australia. His research interests include biomedical applications & signals processing, sensors networks and radar signal processing.

P PathiranaP Pathirana
Dr. Pathirana is currently an Associate Professor with the School of Engineering, Deakin University, Geelong, Australia. His current research interests include mobile/wireless networks, rehabilitation robotics, and radar array signal processing.

C Steinfort
Mr. Steinfort is a Respiratory and Sleep Physician with Barwon Health, Geelong, Australia. He is the director of the Geelong respiratory function and sleep medicine laboratory, and has been a member of numerous societies including British, American, Australian and New Zealand Thoracic Societies.

T CaelliT Caelli
Dr. Caelli is a Senior Principal Researcher at National ICT Australias (NICTA) and part of the
Control and Signal Processing Research Group. His expertise lies in human and machine signal processing, Computer Vision and Pattern Recognition. He is also a Fellow of the International Association for Pattern Recognition (FIAPR) and a Fellow of the Institute for Electronic and Electrical Engineers (FIEEE).

Automatic Detection and Classification of Unsafe Events during Power Wheelchair Use

J. Pineau, A. Moghaddam, H. K. Yuen, P. Archambault, F. Routhier, F. Michaud, P. Boissy

Using a powered wheelchair (PW) is a complex task requiring advanced perceptual and motor control skills. PW incidents and accidents are not uncommon and their consequences can be serious. The objective of our research is to develop technological tools that can be used to characterize a wheelchair user’s driving behavior under various settings…

Authors

See complete bios of the authors in the full version of this article.

J PineauJ Pineau
Dr. Pineau is an Associate Professor at the School of Computer Science at McGill University and member of the Centre for Intelligent Machines (CIM). Her research focuses on developing models and algorithms for learning and decision-making in partially observable stochastic domains, and applying these results to complex problems in robotics and health-care.

A MoghaddamA Moghaddam
Ms. Moghaddam received a B.Sc. In Computer Engineering from University of Tehran, Iran. In 2013, she completed her M.Sc. in Computer Science at McGill University, Canada. Since then, she has been with Facebook Inc., United States, where she is currently a software engineer in Pages Growth and Monetization.

HK YuenHK Yuen
Mr. Yuen received a Bachelor’s degree in Actuarial Analysis from the Chinese University of Hong Kong in 2008. He is currently a Master’s candidate in the Reasoning and Learning Lab from the Computer Science department at McGill University.

P ArchambaultP Archambault
Dr. Archambault is an Associate Professor at the School of Physical and Occupational Therapy, McGill University, Canada. His research interests include power wheelchair mobility, assistive technology, virtual reality and rehabilitation. He is a member of RESNA and SfN.

F RouthierF Routhier
Mr. Routhier is a researcher at the Centre for Interdisciplinary Research in Rehabilitation and Social Intergration (CIRRIS) at Quebec City Rehabilitation Institute and an Associate Professor at Université Laval (Department of Rehabilitation), Québec, Canada. His research interests include wheeled mobility, wheelchair skills, social participation, activity measurement, and assistive devices impacts.

F MichaudF Michaud
Dr. Michaud is a faculty member in the Department of Electrical Engineering and Computer Engineering of the Université de Sherbrooke, and founded IntRoLab, a research laboratory working on designing intelligent autonomous systems that can assist humans in living environments. His research interests are in architectural methodologies for intelligent decision-making and design of interactive autonomous mobile robots.

P BoissyP Boissy
Dr. Boissy has appointments as associate professor at the orthopaedic service, department of surgery and as Senior research scholar FRQS, Research Centre on Aging & Interdisciplinary Institute of Technological Innovation at Université de Sherbrooke. His research is focused on activity monitoring using wearable sensors and their use in clinical and telehealth applications.

The Effect of Light Conditions on Photoplethysmographic Image Acquisition Using a Commercial Camera

H. Liu, Y. Wang, L. Wang

Cameras embedded in consumer devices have previously been used as physiological information sensors. The waveform of the PPGi signals may be significantly affected by the light spectra and intensity. The purpose of this paper is to evaluate the performance of PPGi waveform acquisition in the red, green, and blue channels using a commercial camera in different light conditions…

Authors

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Scope Statement

We focus on innovative solutions to healthcare needs from biomedical engineering, clinical engineering, and medical communities that bridge the engineering and clinical worlds. JTEHM's unique scope is original work at the intersection of engineering and clinical translation.

The journal’s focus is interdisciplinary collaborations among researchers, healthcare providers, and industry. We publish results and best practices from these translational efforts and serve as a community hub for researchers, clinicians, and developers who are addressing challenges in technology development, commercialization, and deployment for better global healthcare. Our ultimate goal is to improve the practice of engineering in translational medicine and to serve as a focal point for the nascent community. Our interactive content includes video, lively commentary, blogs, and other features to engage our clinical and engineering communities.