Published May 22, 2026 | Version v1
Dataset Open

CASAS ArWISE smartwatch dataset - free living, activity labels: Volume 3

  • 1. ROR icon Washington State University
  • 1. ROR icon Washington State University

Description

The Activity recognition from in-the-WIld SmartwatchEs (ArWISE) dataset is based on sensor data and activity labels collected from smart watches. Sensor data consist of timestamped 10Hz accelerometer and gyroscope readings. Portions of the data are annotated with user-provided labels of their current activity.

Note: Other CASAS smart home and smartwatch datasets are also available, look for more at https://zenodo.org/communities/casas. Additional information about this dataset is available at https://zenodo.org/records/15794726 (doi: 10.5821/zenodo.15794726) and https://zenodo.org/records/15802788 (doi: 10.5821/zenodo.15802788), datasets s5, s6, s7, s8, and s9.

Csv files for each person’s data are organized into zip files by study collection dates. Each file number represents a distinct participant. In cases where the same number is used for files ending in "b" and "w", "b" represents a watch worn while sleeping and "w" is the daytime watch. Volume 3 contains data collected for 51 participants, representing 5 distinct data collections. Each file includes a header with feature names. 

Features

  • stamp: date and time of the sensor reading (string)
  • yaw, pitch, roll, rotation_rate_x, rotation_rate_y, rotation_rate_z, user_acceleration_x, user_acceleration_y, user_acceleration_z: 3d movement (float)
  • user_activity_label: string

Notes

Citation: Please cite the following paper when using this dataset:


Minor, B., Greeley, C., Holder, R., Thomas, B., Holder, L., & Cook, D. (2025). A feature-augmented transformer model to recognize functional activities from in-the-wild smartwatch data. IEEE Journal of Behavioral and Health Informatics. https://doi.org/10.1109/JBHI.2025.3586074

Files

s05.zip

Files (42.3 GB)

Name Size Download all
md5:b765fc00d0e060fd0f383cf88e99c880
22.4 GB Preview Download
md5:2dd952b7cff91f7f9a44b6a0be19b08c
690.8 MB Preview Download
md5:9d855963f6ae9d0be4336ab63e1a359a
3.4 GB Preview Download
md5:466f1c8c60f3aec1687afea4c812a219
9.1 GB Preview Download
md5:13a429e26fd8807cc0793b86ab229f12
6.7 GB Preview Download

Additional details

Funding

National Institute on Aging
R25AG046114
National Institute on Aging
R35AG071451
National Institute on Aging
R01AG065218
U.S. National Science Foundation
1954372

Software