Frequency content analysis of gait &amp;#x2014; Vertical ground reaction force

Karout, Hiba; Diab, Mohamad O.; Moslem, Bassam; Alkhatib, Rami; Corbier, Christophe; Badaoui, Mohamed El

doi:10.1109/icabme.2015.7323249

Cited by 1 publication

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Gait pattern signal is commonly performed via inertial measurement units (IMUs), tactile sensors, vertical ground reaction force [2], surface electromyography, electroencephalograms, and so on [3]. The majority of popular gait datasets employ computer vision technology to improve efficiency, such as the Carnegie Mellon University Motion of Body dataset [4], the Human Identification at a Distance-University of Maryland dataset, the Chinese Academy of Sciences Institute of Automation Gait database [5], and the Osaka University Institute of Science and Industry Research Gait database [6].…”

Section: Introductionmentioning

confidence: 99%

Personal‐specific gait recognition based on latent orthogonal feature space

Zhou

Shan

Fang

et al. 2021

Cognitive Comp and Systems

View full text Add to dashboard Cite

Exoskeleton has been applied in the field of medical rehabilitation and assistance. However, there are still some problems in the interaction between human and exoskeleton, such as time delay, the existence of certain constraints on the human body, and the movement in time is hard to follow. A human motion pattern recognition model based on the long short-term memory (LSTM) is proposed, which can recognise the state of the human body. Meanwhile, the orthogonalisation method is integrated to make personalspecific disentangling, and it can effectively improve the generalisation ability of different groups of people, so as to improve the effective follower ability of the exoskeleton. Compared with some other traditional methods, this model has better performance and stronger generalisation ability, which has certain significance in the field of exoskeleton algorithm. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract