rapids/docs/features/phone-accelerometer.md

Phone Accelerometer

Sensor parameters description for [PHONE_ACCELEROMETER]:

Key	Description
[TABLE]	Database table where the accelerometer data is stored

RAPIDS provider

!!! info "Available day segments and platforms" - Available for all day segments - Available for Android and iOS

!!! info "File Sequence" bash - 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/s^2^	The maximum magnitude of acceleration (\|acceleration\| = \sqrt{x^2 + y^2 + z^2}).
minmagnitude	m/s^2^	The minimum magnitude of acceleration.
avgmagnitude	m/s^2^	The average magnitude of acceleration.
medianmagnitude	m/s^2^	The median magnitude of acceleration.
stdmagnitude	m/s^2^	The standard deviation of acceleration.

!!! note "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.

!!! info "Available day segments and platforms" - Available for all day segments - Available for Android and iOS

!!! info "File Sequence" bash - 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.

!!! note "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