Optimizing the input feature sets and machine learning algorithms for reliable and accurate estimation of continuous, cuffless blood pressure

Autor: Rajesh S. Kasbekar, Songbai Ji, Edward A. Clancy, Anita Goel

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)

Abstract The advent of mobile devices, wearables and digital healthcare has unleashed a demand for accurate, reliable, and non-interventional ways to measure continuous blood pressure (BP). Many consumer products claim to measure BP with a cuffless d

Externí odkaz: https://doaj.org/article/e157019448f344ce9e67cf01386cf86b

Random Channel Masks for Regularization of Least Squares-Based Finger EMG-Force Modeling to Improve Cross-Day Performance

Autor: Xinyu Jiang, Xiangyu Liu, Jiahao Fan, Chenyun Dai, Edward A. Clancy, Wei Chen

Publikováno v: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 30, Pp 2157-2167 (2022)

Estimating the finger forces from surface electromyography (sEMG) is essential for diverse applications (e.g., human-machine interfacing). The performance of pre-trained sEMG-force models degenerates significantly when applied on a second day, due to

Externí odkaz: https://doaj.org/article/3d9a8a145cbb477db0f729bfd7150d43

IEEE Access Special Section Editorial: Advanced Information Sensing and Learning Technologies for Data-Centric Smart Health Applications

Autor: Qingxue Zhang, Vincenzo Piuri, Edward A. Clancy, Dian Zhou, Thomas Penzel, Wenchuang Walter Hu

Publikováno v: IEEE Access, Vol 9, Pp 30404-30407 (2021)

Smart health is bringing vast and promising possibilities on the road to comprehensive health management. Smart health applications are strongly data-centric and, thus, empowered by two key factors: information sensing and information learning. In a

Externí odkaz: https://doaj.org/article/995124c2649440308b2263cfce95b179

Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol

Autor: He Wang, Jianan Li, Benjamin E. McDonald, Todd R. Farrell, Xinming Huang, Edward A. Clancy

Publikováno v: Sensors, Vol 23, Iss 5, p 2465 (2023)

Wireless wearable sensor systems for biomedical signal acquisition have developed rapidly in recent years. Multiple sensors are often deployed for monitoring common bioelectric signals, such as EEG (electroencephalogram), ECG (electrocardiogram), and

Externí odkaz: https://doaj.org/article/eae0d8d58d5c4804b4ac7a6995776dc0

Consensus for experimental design in electromyography (CEDE) project

Autor: Eduardo Martinez-Valdes, Roger M. Enoka, Aleš Holobar, Kevin McGill, Dario Farina, Manuela Besomi, François Hug, Deborah Falla, Richard G. Carson, Edward A. Clancy, Catherine Disselhorst-Klug, Jaap H. van Dieën, Kylie Tucker, Simon Gandevia, Madeleine Lowery, Karen Søgaard, Thor Besier, Roberto Merletti, Matthew C. Kiernan, John C. Rothwell, Eric Perreault, Paul W. Hodges

Publikováno v: Journal of Electromyography and Kinesiology, 68:102726, 1-14. Elsevier Limited
Martinez-Valdes, E, Enoka, R M, Holobar, A, McGill, K, Farina, D, Besomi, M, Hug, F, Falla, D, Carson, R G, Clancy, E A, Disselhorst-Klug, C, van Dieën, J H, Tucker, K, Gandevia, S, Lowery, M, Søgaard, K, Besier, T, Merletti, R, Kiernan, M C, Rothwell, J C, Perreault, E & Hodges, P W 2023, ' Consensus for experimental design in electromyography (CEDE) project : Single motor unit matrix ', Journal of Electromyography and Kinesiology, vol. 68, 102726, pp. 1-14 . https://doi.org/10.1016/j.jelekin.2022.102726

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials gene

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c038d8498fe9d07389fd16015fa1de0f
https://doi.org/10.1016/j.jelekin.2022.102726