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Performance evaluation of a machine learning-based methodology using dynamical features to detect nonwear intervals in actigraphy data in a free-living setting

Sleep Health(2025)10.1016/j.sleh.2024.10.003Source: DataRank Database

Performance evaluation of a machine learning-based methodology using dynamical features to detect nonwear intervals in actigraphy data in a free-living setting is a research paper published in Sleep Health (2025). On theSindex it has a DataRank of 0. It has been cited 2 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access2 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Pending

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (6)

Linying Ji ORCID,Yuqi Shen ORCID,Soundar Kumara ORCID,Orfeu M. Buxton ORCID,Sy‐Miin Chow ORCID