Latest research trends in gait analysis using wearable sensors and machine learning: A systematic review
author
Saboor, Abdul
Kask, Triin
Kuusik, Alar
Alam, Muhammad Mahtab
Le Moullec, Yannick
statement of authorship
Abdul Saboor, Triin Kask, Alar Kuusik, Muhammad Mahtab Alam, Yannick Le Moullec, Imran Khan Niazi, Ahmed Zoha, Rizwan Ahmad
source
IEEE Access
publisher
IEEE
journal volume number month
vol. 8
year of publication
2020
pages
art. 3022818, p. 167830−167864
url
https://doi.org/10.1109/ACCESS.2020.3022818
subject term
tehisõpe
kõnnak
käimistestid
andurid
biosensorid
meditsiinitehnoloogia
keyword
gait analysis
machine learning
wearable sensors
survey
medical applications
ISSN
2169-3536
notes
Bibliogr.: 202 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/21100374601
https://www.scopus.com/record/display.uri?eid=2-s2.0-85100409488&origin=inward&txGid=698683f16632643e3182cc2e31a35d1e
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=IEEE%20ACCESS&year=2022
https://www.webofscience.com/wos/woscc/full-record/WOS:000572977500001
category (general)
Engineering
Computer science
Materials science
Tehnika
Arvutiteadus
Materjaliteadus
category (sub)
Engineering. General engineering
Computer science. General computer science
Materials science. General materials science
Tehnika. Üldine inseneriteadus
Arvutiteadus. Üldine arvutiteadus
Materjaliteadus. Üldine materjaliteadus
quartile
Q1
TalTech department
Thomas Johann Seebecki elektroonikainstituut
language
inglise
Reserch Group
Cognitronic lab-on-a-chip research group
Research laboratory for cognitronics
Communication systems research group