Real-time gait anomaly detection using 1D-CNN and LSTM
author
Rostovski, Jakob
Ahmadilivani, Mohammad Hasan
Krivošei, Andrei
Kuusik, Alar
Alam, Muhammad Mahtab
statement of authorship
Jakob Rostovski, Mohammad Hasan Ahmadilivani, Andrei Krivošei, Alar Kuusik, Muhammad Mahtab Alam
source
Digital Health and Wireless Solutions : First Nordic Conference, NCDHWS 2024, Oulu, Finland, May 7–8, 2024 : Proceedings, Part II
location of publication
Cham
publisher
Springer
year of publication
2024
pages
p. 260-278
series
Communications in computer and information science ; 2084
conference name, date
NCDHWS 2024 : The First Nordic Conference on Digital Health and Wireless Solutions (NCDHWS), May 7–8, 2024
conference location
Oulu, Finland
url
https://doi.org/10.1007/978-3-031-59091-7_17
subject term
kõnnak
käimisraskused
sügavõpe
reaalajasüsteemid
andurid
algoritmid
Scopus
https://www.scopus.com/sourceid/17700155007
https://www.scopus.com/record/display.uri?eid=2-s2.0-85193513969&origin=resultslist&sort=plf-f&src=s&sot=b&sdt=b&s=ALL%28%22Real-Time+Gait+Anomaly+Detection+Using+1D-CNN+and+LSTM%22%29&sessionSearchId=a1950993a8713b95c4defac4e2fbf8c1&relpos=0
WOS
https://www.webofscience.com/wos/woscc/full-record/WOS:001265181000017
category (general)
Mathematics
Matemaatika
Computer science
Arvutiteadus
category (sub)
Mathematics. General mathematics
Matemaatika. Üldmatemaatika
Computer science. General computer science
Arvutiteadus. Üldine arvutiteadus
keyword
human gait
anomaly detection
gait analysis
machine learning (ML)
real-time
1D-CNN
LSTM
wearable sensors
ISSN
1865-0929
ISBN
978-3-031-59090-0
notes
Bibliogr.: 37 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
Thomas Johann Seebecki elektroonikainstituut
arvutisüsteemide instituut
language
inglise