H.-K. Lee scite author profile

The presented study highlights the feasibility and accuracy of novel computational methods based on a morphological filter and a least square acceleration filter to detect step events for evaluating normal and pathological gait parameters using a single accelerometer. This is the first evidence that demonstrates the feasibility and accuracy of the novel accelerometer-based system and methods in both normal and pathological populations.

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Hybrid Deep Neural Network Framework Combining Skeleton and Gait Features for Pathological Gait Recognition

Jun¹,

Lee²,

Lee³

et al. 2023

Preprint

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H.-K. Lee

Classification of temporal bone pneumatization based on sigmoid sinus using computed tomography

Computational methods to detect step events for normal and pathological gait evaluation using accelerometer

Hybrid Deep Neural Network Framework Combining Skeleton and Gait Features for Pathological Gait Recognition

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