Application of a Generalized Regression Neural Network to the Estimation of Average Gait Speed
EOG Alvaredo, GA Castellanos, FEH Montero… - Progress in Artificial …, 2021 - Springer
This work addresses the estimation of the average gait speed through a Generalized
Regression Neural Network. According to this goal, acceleration and angular velocity
signals were gathered from an Inertial Measurement Unit placed in the lumbar region. In
order to lead to a more adequate composition of the training and validation subsets, a novel
approach, based on route optimization, in particular, the nearest neighbor algorithm, was
implemented. Although only five features were extracted from IMU's signals, the results were …
Regression Neural Network. According to this goal, acceleration and angular velocity
signals were gathered from an Inertial Measurement Unit placed in the lumbar region. In
order to lead to a more adequate composition of the training and validation subsets, a novel
approach, based on route optimization, in particular, the nearest neighbor algorithm, was
implemented. Although only five features were extracted from IMU's signals, the results were …
Application of a Generalized Regression Neural Network to the Estimation of Average Gait Speed
FEH Montero, TYA Rodríguez - Progress in Artificial Intelligence …, 2021 - books.google.com
This work addresses the estimation of the average gait speed through a Generalized
Regression Neural Network. According to this goal, acceleration and angular velocity
signals were gathered from an Inertial Measurement Unit placed in the lumbar region. In
order to lead to a more adequate composition of the training and validation subsets, a novel
approach, based on route optimization, in particular, the nearest neighbor algorithm, was
implemented. Although only five features were extracted from IMU's signals, the results were …
Regression Neural Network. According to this goal, acceleration and angular velocity
signals were gathered from an Inertial Measurement Unit placed in the lumbar region. In
order to lead to a more adequate composition of the training and validation subsets, a novel
approach, based on route optimization, in particular, the nearest neighbor algorithm, was
implemented. Although only five features were extracted from IMU's signals, the results were …
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