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Phone Accelerometer

Sensor parameters description for [PHONE_ACCELEROMETER]:

Key                              Description
[CONTAINER] Data stream container (database table, CSV file, etc.) where the accelerometer data is stored. This can be a single container or an array of containers

RAPIDS provider

Available time segments and platforms

  • Available for all time segments
  • Available for Android and iOS

File Sequence

- data/raw/{pid}/phone_accelerometer_raw.csv
- data/raw/{pid}/phone_accelerometer_with_datetime.csv
- data/interim/{pid}/phone_accelerometer_features/phone_accelerometer_{language}_{provider_key}.csv
- data/processed/features/{pid}/phone_accelerometer.csv

Parameters description for [PHONE_ACCELEROMETER][PROVIDERS][RAPIDS]:

Key                              Description
[COMPUTE] Set to True to extract PHONE_ACCELEROMETER features from the RAPIDS provider
[FEATURES] Features to be computed, see table below

Features description for [PHONE_ACCELEROMETER][PROVIDERS][RAPIDS]:

Feature Units Description
maxmagnitude m/s2 The maximum magnitude of acceleration (\(\|acceleration\| = \sqrt{x^2 + y^2 + z^2}\)).
minmagnitude m/s2 The minimum magnitude of acceleration.
avgmagnitude m/s2 The average magnitude of acceleration.
medianmagnitude m/s2 The median magnitude of acceleration.
stdmagnitude m/s2 The standard deviation of acceleration.

Assumptions/Observations

  1. Analyzing accelerometer data is a memory intensive task. If RAPIDS crashes is likely because the accelerometer dataset for a participant is to big to fit in memory. We are considering different alternatives to overcome this problem.

PANDA provider

These features are based on the work by Panda et al.

Available time segments and platforms

  • Available for all time segments
  • Available for Android and iOS

File Sequence

- data/raw/{pid}/phone_accelerometer_raw.csv
- data/raw/{pid}/phone_accelerometer_with_datetime.csv
- data/interim/{pid}/phone_accelerometer_features/phone_accelerometer_{language}_{provider_key}.csv
- data/processed/features/{pid}/phone_accelerometer.csv

Parameters description for [PHONE_ACCELEROMETER][PROVIDERS][PANDA]:

Key                              Description
[COMPUTE] Set to True to extract PHONE_ACCELEROMETER features from the PANDA provider
[FEATURES] Features to be computed for exertional and non-exertional activity episodes, see table below

Features description for [PHONE_ACCELEROMETER][PROVIDERS][PANDA]:

Feature Units Description
sumduration minutes Total duration of all exertional or non-exertional activity episodes.
maxduration minutes Longest duration of any exertional or non-exertional activity episode.
minduration minutes Shortest duration of any exertional or non-exertional activity episode.
avgduration minutes Average duration of any exertional or non-exertional activity episode.
medianduration minutes Median duration of any exertional or non-exertional activity episode.
stdduration minutes Standard deviation of the duration of all exertional or non-exertional activity episodes.

Assumptions/Observations

  1. Analyzing accelerometer data is a memory intensive task. If RAPIDS crashes is likely because the accelerometer dataset for a participant is to big to fit in memory. We are considering different alternatives to overcome this problem.
  2. See Panda et al for a definition of exertional and non-exertional activity episodes