Transactions on Neural Systems and Rehabilitation Engineering

Featured Articles
VME-DWT: An Efficient Algorithm for Detection and Elimination of Eye Blink From Short Segments of Single EEG Channel
Mohammad Shahbakhti, Matin Beiramvand, Mojtaba Nazari, Anna Broniec-Wójcik, Piotr Augustyniak, Ana Santos Rodrigues, Michal Wierzchon, Vaidotas Marozas
Objective: Recent advances in development of low-cost single-channel electroencephalography (EEG) headbands have opened new possibilities for applications in health monitoring and brain-computer interface (BCI) systems. These recorded EEG signals, however, are often contaminated by eye blink artifacts that can yield... Read more
Posted on 26 MAR 2021
Featured Articles
Deep Learning for Accelerometric Data Assessment and Ataxic Gait Monitoring
Aleš Procházka, Ondřej Dostál, Pavel Cejnar, Hagar Ibrahim Mohamed, Zbyšek Pavelek, Martin Vališ, Oldřich Vyšata
Ataxic gait monitoring and assessment of neurological disorders belong to important multidisciplinary areas that are supported by digital signal processing methods and machine learning tools. This paper presents the possibility of using accelerometric data to optimise deep learning convolutional neural... Read more
Posted on 26 MAR 2021
Articles
Detecting effect of levodopa in Parkinson’s disease patients using sustained phonemes
Nemuel D. Pah, Mohammod A. Motin, Peter Kempster, Dinesh 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... Read more
Posted on 18 MAR 2021
Articles
Design, Simulation, and Development of a BioSensor for Viruses Detection using FPGA
Mohammed Abdallah
Abstract: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... Read more
Posted on 2 FEB 2021
Articles
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
R. Gallachio, 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... Read more
Posted on 3 DEC 2020
Articles
Side-Channel Sensing: Exploiting Side-Channels to Extract Information for Medical Diagnostics and Monitoring
Aaron Spence, Shaun Bangay
Abstract 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... Read more
Posted on 7 OCT 2020
Articles
COVID-19 Artificial Intelligence Diagnosis using only Cough Recordings
Jordi Laguarta, Ferran Hueto, Brian Subirana
Abstract: Goal: We hypothesized that COVID-19 subjects, especially including asymptomatics, could be accurately discriminated only from a forced-cough cell phone recording using Artificial Intelligence. To train our MIT Open Voice model we built a data collection pipeline of COVID-19 cough recordings... Read more
Posted on 30 SEP 2020
Articles
Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?
Catherine P. Adans-Dester, Stacy Bamberg, Francesco Bertacchi, Brian Caulfield, Kara Chappie, Danilo Demarchi, M. Kelley Erb, Juan Estrada, Eric Fabara, Michael Freni, E. Karl Friedl, Roozbeh Ghaffari, Geoffrey Gill, Mark S. Greenberg, Reed W. Hoyt, Emil Jovanov, Christoph Kanzler, Dina Katabi, Meredith Kernan, Colleen Kigin, Sunghoon Ivan Lee, Steffen Leonhardt, Nigel Hamilton Lovell, Jose Mantilla, Thomas H. McCoy, Nell Meosky Luo, Glenn A. Miller, John Moore, Derek O'Keeffe, Jeffrey Palmer, Federico Parisi, Shyamal Patel, Ming Jack Po, Benito L. Pugliese, Thomas Quatieri, Tauhidur Rahman, Nathan Ramasarma, John A. Rogers, Guillermo U. Ruiz-Esparza, Stefano Sapienza, Gregory Schiurring, Lee Schwamm, Hadi Shafiee, Sara Kelly Silacci, Nathaniel M. Sims, Tanya Talkar, William J. Tharion, James A. Toombs, Christopher Uschnig, Gloria Vergara, Paul Wacnik, May D. Wang, James Welch, Lina Williamson, Ross Zafonte, Adrian Zai, Yuan-Ting Zhang, Guillermo J. Tearney, Rushdy Ahmad, David R. Walt, Paolo Bonato
Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise... Read more
Posted on 17 AUG 2020
Featured Articles
Real-time Radiofrequency Ablation Lesion Depth Estimation Using Multi-Frequency Impedance with a Deep Neural Network and Tree-based Ensemble
Emre Besler, Y. Curtis Wang, Alan V. Sahakian
A combination of different machine learning algorithms and a hardware setup that consists of an embedded system and a 3D-printed electrode device is used to monitor the progress of radiofrequency ablation depth on a perfused breast tissue model. The device at the center of the tissue model both applied the alternating current and collected the tissue impedance data at multiple frequencies, which is fed into tree-based ensemble (TE) models and a deep neural network (DNN). Their predictions showed a mean difference against physical measurements of 0.5 mm for the DNN and 0.7 mm for the TEs... Read more
Posted on 30 JUN 2020
Articles, Published Articles
Non-contact Early Warning of Shaking Palsy
Xiaodong Yang, Dou Fan, Aifeng Ren, Nan Zhao, Zhiya Zhang, Daniyal Haider, Muhammad Bilal Khan, Jie Tian
        Abstract Objective: Parkinsonian gait is a defining feature of Shaking Palsy (SP) and it has one of the worse impact on human healthy life than other SP symptoms. The objective of this work is to propose a Parkinsonian gait detection system... Read more
Posted on 18 JUN 2019