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subject_id
int64
1.6k
1.65k
activity_code
stringclasses
18 values
timestamp
int64
268B
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Smartphone and Smartwatch Activity and Biometrics 15m6

A 15.6-million-sample, multi-device time-series corpus that unites 3-axis accelerometer and gyroscope streams from 51 volunteers. Each participant carried a smartphone and smartwatch while performing 18 everyday activities for three minutes apiece, generating synchronized recordings sampled at 20 Hz.

Every record is formatted as:

  • subject_id – integer 1600–1650 uniquely identifying the volunteer
  • activity_code – single ASCII letter A–S (the letter N is deliberately skipped) denoting the performed activity:
    • "A" - Walking
    • "B" - Jogging
    • "C" - Stairs
    • "D" - Sitting
    • "E" - Standing
    • "F" - Typing
    • "G" - Brushing Teet
    • "H" - Eating Soup
    • "I" - Eating Chips
    • "J" - Eating Pasta
    • "K" - Driking from Cup
    • "L" - Eating Sandwich
    • "M" - Kicking (Soccer Ball)
    • "O" - Playing Catch w/ Tennis Ball
    • "P" - Dribbling (Basketball)
    • "Q" - Writing
    • "R" - Clapping
    • "S" - Folding Clothes
  • timestamp – Unix epoch in seconds
  • x, y, z – instantaneous sensor readings for the corresponding device and modality

The dataset is split into four directories—phone-accelerometer, phone-gyroscope, watch-accelerometer, watch-gyroscope—each holding 51 per-subject files. Alongside raw traces, pre-computed 10-second sliding-window features are provided, enabling both activity-recognition and behavioral-biometric research.

Acknowledgements: The dataset is hosted at the UCI MLR—Smartphone and Smartwatch Activity and Biometrics

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