Systematic Literature Review: Recognition of Human Gait Cycle Using Machine Learning Approach

This paper aims to summarise the studies on the human gait cycle analysis that applied an Artificial Intelligent Algorithm (AI) based on inertial sensor data, verifying whether it can support the clinical evaluation. This study focuses on the research on the main databases, particularly from the yea...

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书目详细资料
发表在:2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering, ICRAIE 2021
主要作者: 2-s2.0-85136505986
格式: Conference paper
语言:English
出版: Institute of Electrical and Electronics Engineers Inc. 2022
在线阅读:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136505986&doi=10.1109%2fICRAIE52900.2021.9703983&partnerID=40&md5=0c48a5e24d3bafaefa89f055a98ee12d
实物特征
总结:This paper aims to summarise the studies on the human gait cycle analysis that applied an Artificial Intelligent Algorithm (AI) based on inertial sensor data, verifying whether it can support the clinical evaluation. This study focuses on the research on the main databases, particularly from the year 2015 to 2021. Fifteen studies were identified that have met the inclusion criteria. This paper also discussed the Machine Learning (ML) approach applied to classify and predict the gait cycle. The ML algorithm proposed are SVM, MC and ANN. Features such as swing and stance are the most selected features for healthy subjects, extracted from ground reaction force (GRF) during gait. © 2021 IEEE.
ISSN:
DOI:10.1109/ICRAIE52900.2021.9703983