CAPTURE-24: A large dataset of wrist-worn activity tracker data collected in the wild for human activity recognition
Existing activity tracker datasets for human activity recognition are typically obtained by having participants perform predefined activities in an enclosed environment under supervision. This results in small datasets with a limited number of activities and heterogeneity, lacking the mixed and nuan...
Main Authors: | Chan, S, Hang, Y, Tong, C, Acquah, A, Schonfeldt, A, Gershuny, J, Doherty, A |
---|---|
Format: | Journal article |
Language: | English |
Published: |
Nature Research
2024
|
Similar Items
-
Capture-24: Activity tracker dataset for human activity recognition
by: Chan Chang, S, et al.
Published: (2021) -
Capture-24: Activity tracker dataset for human activity recognition
by: Chan Chang, S, et al.
Published: (2021) -
Capture-24: Activity tracker dataset for human activity recognition - Temperature & light sensor data
by: Chan Chang, S, et al.
Published: (2023) -
User Acceptance of Wrist-Worn Activity Trackers Among Community-Dwelling Older Adults: Mixed Method Study
by: Puri, Arjun, et al.
Published: (2017-11-01) -
OxWalk: Wrist and hip-based activity tracker dataset for free-living step detection and gait recognition
by: Small, S R, et al.
Published: (2022)