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Behavioral Features Introduction
A behavioral feature is a metric computed from raw sensor data quantifying the behavior of a participant. For example, the time spent at home computed based on location data. These are also known as digital biomarkers.
RAPIDS' config.yaml
has a section for each supported device/sensor (e.g., PHONE_ACCELEROMETER
, FITBIT_STEPS
, EMPATICA_HEARTRATE
). These sections follow a similar structure, and they can have one or more feature PROVIDERS
, that compute one or more behavioral features. You will modify the parameters of these PROVIDERS
to obtain features from different mobile sensors. We'll use PHONE_ACCELEROMETER
as an example to explain this further.
!!! hint
- We recommend reading this page if you are using RAPIDS for the first time
- All computed sensor features are stored under /data/processed/features
on files per sensor, per participant and per study (all participants).
- Every time you change any sensor parameters, provider parameters or provider features, all the necessary files will be updated as soon as you execute RAPIDS.
- In short, to extract features offered by a provider, you need to set its [COMPUTE]
flag to TRUE
, configure any of its parameters, and execute RAPIDS.
Explaining the config.yaml sensor sections with an example
Each sensor section follows the same structure. Click on the numbered markers to know more.
PHONE_ACCELEROMETER: # (1)
CONTAINER: accelerometer # (2)
PROVIDERS: # (3)
RAPIDS:
COMPUTE: False # (4)
FEATURES: ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
SRC_SCRIPT: src/features/phone_accelerometer/rapids/main.py
PANDA:
COMPUTE: False
VALID_SENSED_MINUTES: False
FEATURES: # (5)
exertional_activity_episode: ["sumduration", "maxduration", "minduration", "avgduration", "medianduration", "stdduration"]
nonexertional_activity_episode: ["sumduration", "maxduration", "minduration", "avgduration", "medianduration", "stdduration"]
# (6)
SRC_SCRIPT: src/features/phone_accelerometer/panda/main.py
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These are the descriptions of each marker for accessibility:
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