Zobrazeno 1 - 5
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pro vyhledávání: '"Seth R. Donahue"'
Autor:
Seth R. Donahue, Michael E. Hahn
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-19 (2023)
Abstract Wearable sensors and machine learning algorithms are becoming a viable alternative for biomechanical analysis outside of the laboratory. The purpose of this work was to estimate gait events from inertial measurement units (IMUs) and utilize
Externí odkaz:
https://doaj.org/article/b67cc8aa9b014d9ba38f4ee816c5000c
Autor:
Seth R. Donahue, Michael E. Hahn
Publikováno v:
Frontiers in Sports and Active Living, Vol 5 (2023)
In laboratory experiments, biomechanical data collections with wearable technologies and machine learning have been promising. Despite the development of lightweight portable sensors and algorithms for the identification of gait events and estimation
Externí odkaz:
https://doaj.org/article/cbd042430966416ab61820365a632f18
Autor:
Seth R. Donahue, Michael E. Hahn
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 30, Pp 108-114 (2022)
The purpose of this study was to compare a heuristic feature identification algorithm with output from the Beta Process Auto Regressive Hidden Markov Model (BP-AR-HMM) utilizing minimally sampled (≤ 100 Hz) human locomotion data for identification
Externí odkaz:
https://doaj.org/article/93e2fad397c44cd5937a21f500f7f6be
Autor:
Seth R. Donahue, Michael E. Hahn
Publikováno v:
Sensors, Vol 22, Iss 9, p 3452 (2022)
The development of lightweight portable sensors and algorithms for the identification of gait events at steady-state running speeds can be translated into the real-world environment. However, the output of these algorithms needs to be validated. The
Externí odkaz:
https://doaj.org/article/d4fc9b1c3b7640f29fbdd2499ce23135
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. 25:1583-1590
Goal : The purpose of this study was to provide an initial examination of the utility of the Beta Process - Auto Regressive - Hidden Markov Model (BP-AR-HMM) for the prior identification of gait events. A secondary objective was to determine whether