CORE
šŗš¦Ā
Ā make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Self-Supervised Learning of Wrist-Worn Daily Living Accelerometer Data Improves the Automated Detection of Gait in Older Adults
Authors
Becker C
Brand YE
+14Ā more
Buchman AS
Cereatti A
Del Din S
Hausdorff JM
Kluge F
Maetzler W
Muller A
Palmerini L
Paraschiv-Ionescu A
Perlman O
Rochester L
Sharrack B
Vereijken B
Yarnall AJ
Publication date
Publisher
Nature Publishing Group
Abstract
Abstract is not available.
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Newcastle University E-Prints
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:eprints.ncl.ac.uk:300741
Last time updated on 16/09/2024