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...
| Published in: | 2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering, ICRAIE 2021 |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
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Institute of Electrical and Electronics Engineers Inc.
2022
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136505986&doi=10.1109%2fICRAIE52900.2021.9703983&partnerID=40&md5=0c48a5e24d3bafaefa89f055a98ee12d |
| Summary: | 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. |
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| DOI: | 10.1109/ICRAIE52900.2021.9703983 |