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Part of MONSTER: https://arxiv.org/abs/2502.15122.

WISDM
Category HAR
Num. Examples 17,166
Num. Channels 3
Length 100
Sampling Freq. 20 Hz
Num. Classes 6
License Other
Citations [1]

WISDM describes six daily activities—Walking, Jogging, Stairs, Sitting, Standing, and Lying Down—collected in a controlled laboratory environment. Data were recorded from 36 participants using a smartphone's built-in tri-axial accelerometer, with the device placed in the user's front pants pocket. The accelerometer captures acceleration along the x, y, and z axes, providing a comprehensive view of the user's movements. The data is sampled at a rate of 20 Hz, resulting in a total of 1,098,207 samples across 3 dimensions [1]. The processed dataset contains 17,166 multivariate time series with a length of 100 (representing 5 seconds of data at 20 Hz). WISDM is split based on subjects.

[1] Jeffrey W Lockhart, Tony Pulickal, and Gary M Weiss. (2012). Applications of mobile activity recognition. In Conference on Ubiquitous Computing, pages 1054–1058.

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