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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Vydáno v:	2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE) Ročník 6; s. 1 - 6
Hlavní autoři:	Kamaruzaman, F.F.A, Izhar, Che Ani Adi, Fauzilan, A.S., Setumin, Samsul, Hussain, Z., Abdullah, M.F.
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.12.2021
Témata:	Human Gait Machine learning Machine Learning (ML) Machine learning algorithms Medical treatment Prediction Support vector machines Systematics Technological innovation Training
On-line přístup:	Získat plný text
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Popis
Shrnutí:	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.
DOI:	10.1109/ICRAIE52900.2021.9703983