WIreless Sensor Data Mining Lab
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WISDM Activity Prediction Dataset

Updated: Dec. 2, 2012
The data in this file corresponds with the data used in the following paper:

Jennifer R. Kwapisz, Gary M. Weiss and Samuel A. Moore (2010).
Activity Recognition using Cell Phone Accelerometers,
Proceedings of the Fourth International Workshop on Knowledge
Discovery from Sensor Data (at KDD-10), Washington DC. [PDF]

When using this dataset, we request that you cite this paper. You may also want to cite our other relevant articles, which can be found here.

When sharing or redistributing this dataset, we request that the readme.txt file is always included.
  • Files:
    • readme.txt
    • WISDM_ar_v1.1_raw_about.txt
    • WISDM_ar_v1.1_trans_about.txt
    • WISDM_ar_v1.1_raw.txt
    • WISDM_ar_v1.1_transformed.arff

Changelog

  • (v1.1)
    • about files updated with summary information
    • file naming convention updated to include version numbers
    • readme.txt updated to include relevant papers
    • WISDM_ar_v1.1_trans_about.txt updated with citation to paper describing the attributes.

  • (v1.0)
    • user names masked with ID numbers 1-36
    • dataset initialized

Statistics

  • Raw Time Series Data
    • Number of examples: 1,098,207
    • Number of attributes: 6
    • Missing attribute values: None
    • Class Distribution
      • Walking: 424,400 (38.6%)
      • Jogging: 342,177 (31.2%)
      • Upstairs: 122,869 (11.2%)
      • Downstairs: 100,427 (9.1%)
      • Sitting: 59,939 (5.5%)
      • Standing: 48,395 (4.4%)

  • Transformed Examples
    • Number of transformed examples: 5,424
    • Number of transformed attributes: 46
    • Missing attribute values: None
    • Class Distribution
      • Walking: 2,082 (38.4%)
      • Jogging: 1,626 (30.0%)
      • Upstairs: 633 (11.7%)
      • Downstairs: 529 (9.8%)
      • Sitting: 307 (5.7%)
      • Standing: 247 (4.6%)

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