Representative model confidence output for a no-exoskeleton testing trial.

Representative model confidence output for a no-exoskeleton testing trial.

<p>LSTM detection curves peak at roughly the same time as the manual event confidence curves. LSTM HS detection curves show fluctuations before the peaks while the TO detection curves show fluctuations after the peaks.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Xiaowen Chen (192197) (author)
مؤلفون آخرون: Anne E. Martin (10838318) (author)
منشور في: 2025
الموضوعات:
Science Policy
Space Science
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
use roughly 8
use neural networks
two lstm models
recent methods tend
previous lstm algorithms
machine learning algorithms
ground reaction force
custom ankle exoskeletons
algorithm successfully detected
manually identified events
events within 16ms
subjects &# 8217
heel marker height
detection methods tend
assistive walking device
testing data ratio
low training requirements
new model required
detecting gait events
final model output
new long short
term memory model
assisted walking using
new model
gait events
term memory
long short
subjects walking
model makes
weighted output
heel strike
detection rate
walking behaviors
unassisted walking
kinematic data
79 training
utilize thresholding
significantly altered
paper introduces
high robustness
excellent tool
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