Comments: Estimation of body segmental orientation for prosthetic gait using a nonlinear autoregressive neural network with exogenous inputs

Estimation of body segmental orientation for prosthetic gait using a nonlinear autoregressive neural network with exogenous inputs

Assessment of the prosthetic gait is an important clinical approach to evaluate the quality and functionality of the prescribed lower limb prosthesis as well as to monitor rehabilitation progresses following limb amputation. Limited access to quantitative assessment tools generally affects the repea...

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Bibliographic Details
Main Authors:	Tham L.K., Al Kouzbary M., Al Kouzbary H., Liu J., Abu Osman N.A.
Other Authors:	36560464100
Format:	Article
Published:	Springer Science and Business Media Deutschland GmbH 2024
Subjects:	Artificial neural network Inertial sensors NARX network Orientation estimation Prosthetic gait Validation Amputation, Surgical Foot Gait Humans Lower Extremity Neural Networks, Computer Acceleration Artificial limbs Inertial navigation systems Wearable sensors Autoregressive neural networks Complementary filters Exogenous input Inertial sensor Lower limb prosthesis Segmental orientation acceleration adult amputee Article artificial neural network biological model controlled study correlational study gait gravity human human experiment leg amputation locomotion magnetism male measurement accuracy middle aged nonlinear autoregressive neural network nonlinear system normal human reproducibility robotics validation study walk test amputation foot lower limb Neural networks
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Estimation of body segmental orientation for prosthetic gait using a nonlinear autoregressive neural network with exogenous inputs

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