Vaulting Detection with the Multi-Model Unscented Kalman Filter

Document Type

Conference Proceeding

Publication Date

1-1-2024

Abstract

A method for automatically detecting vaulting gait is presented. Two gait models are parameterized based on data from humans, representing a normal gait and a vaulting gait. Structural observability analysis is performed taking into account measurements from a wearable sensor package. A multi-model Unscented Kalman Filter is applied to sensor data from live trials to automatically detect the gait mode.

Identifier

85208224367 (Scopus)

ISBN

[9798350358513]

Publication Title

IEEE International Conference on Automation Science and Engineering

External Full Text Location

https://doi.org/10.1109/CASE59546.2024.10711410

e-ISSN

21618089

ISSN

21618070

First Page

3306

Last Page

3311

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