Bending Angle Sensor Based on Double-layer Capacitance Suitable for Human Jointhttps://www.embs.org/ojemb/wp-content/uploads/sites/20/2023/06/10168208-scaled.jpg18102560IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)//www.embs.org/ojemb/wp-content/uploads/sites/20/2022/06/ieee-ojemb-logo2x.png
Goal: To develop bending angle sensors based on double-layer capacitance for monitoring joint angles during cycling exercises. Methods: We develop a bending angle sensor based on double-layer capacitive and conducted…
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Author(s)3: Jordi Laguarta, Ferran Hueto, Brian Subirana
COVID-19 Artificial Intelligence Diagnosis using only Cough Recordingshttps://www.embs.org/ojemb/wp-content/uploads/sites/20/2020/09/Covid19-artificial.png200200IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)//www.embs.org/ojemb/wp-content/uploads/sites/20/2022/06/ieee-ojemb-logo2x.png
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 through our website (opensigma.mit.edu) between April and May 2020 and created the largest audio COVID-19 cough balanced dataset reported to date with 5,320 subjects.
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Author(s)3: 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
Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?https://www.embs.org/ojemb/wp-content/uploads/sites/20/2020/08/Can-mhealth.png200200IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)//www.embs.org/ojemb/wp-content/uploads/sites/20/2022/06/ieee-ojemb-logo2x.png
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.
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