This study implements a 4-fold cross-validation and inferencing procedure.

<p>The dataset comprises (A) treadmill walking and (B) overground locomotion data, both divided into 4 folds. Each fold contains a training dataset from 24 subjects, a validation dataset from 8 subjects, and a testing dataset from 8 subjects for the treadmill walking data. Furthermore, the tes...

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Bibliographic Details
Main Author:	Dollaporn Anopas (20036556) (author)
Other Authors:	Yodchanan Wongsawat (7209779) (author), Jetsada Arnin (20036559) (author)
Published:	2024
Subjects:	Developmental Biology Space Science Biological Sciences not elsewhere classified xlink "> individuals continuous gait phase lower limb impairment method employs windows 51 ms across time phase using average time error neural network model currently cannot detect treadmill walking data overground walking data unsupervised learning method unsupervised learning treadmill walking overground walking trained model neural networks comparatively lower walking conditions overground locomotion 42 ms 20 ms time trajectories time applications traditional methods thereby eliminating robotic systems obtain due laboratory setting different speeds
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This study implements a 4-fold cross-validation and inferencing procedure.

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