Update docs & links in config.yaml
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config.yaml
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config.yaml
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@ -474,6 +474,7 @@ EMPATICA_DATA_STREAMS:
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# Sensors ------
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# Sensors ------
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# See https://www.rapids.science/latest/features/empatica-accelerometer/
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EMPATICA_ACCELEROMETER:
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EMPATICA_ACCELEROMETER:
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TABLE: ACC
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TABLE: ACC
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PROVIDERS:
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PROVIDERS:
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@ -483,6 +484,7 @@ EMPATICA_ACCELEROMETER:
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SRC_FOLDER: "dbdp" # inside src/features/empatica_accelerometer
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SRC_FOLDER: "dbdp" # inside src/features/empatica_accelerometer
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SRC_LANGUAGE: "python"
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SRC_LANGUAGE: "python"
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# See https://www.rapids.science/latest/features/empatica-heartrate/
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EMPATICA_HEARTRATE:
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EMPATICA_HEARTRATE:
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TABLE: HR
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TABLE: HR
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PROVIDERS:
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PROVIDERS:
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@ -492,6 +494,7 @@ EMPATICA_HEARTRATE:
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SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
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SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
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SRC_LANGUAGE: "python"
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SRC_LANGUAGE: "python"
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# See https://www.rapids.science/latest/features/empatica-temperature/
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EMPATICA_TEMPERATURE:
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EMPATICA_TEMPERATURE:
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TABLE: TEMP
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TABLE: TEMP
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PROVIDERS:
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PROVIDERS:
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@ -501,6 +504,7 @@ EMPATICA_TEMPERATURE:
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SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
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SRC_FOLDER: "dbdp" # inside src/features/empatica_heartrate
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SRC_LANGUAGE: "python"
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SRC_LANGUAGE: "python"
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# See https://www.rapids.science/latest/features/empatica-electrodermal-activity/
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EMPATICA_ELECTRODERMAL_ACTIVITY:
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EMPATICA_ELECTRODERMAL_ACTIVITY:
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TABLE: EDA
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TABLE: EDA
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PROVIDERS:
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PROVIDERS:
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@ -510,6 +514,7 @@ EMPATICA_ELECTRODERMAL_ACTIVITY:
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SRC_FOLDER: "dbdp" # inside src/features/empatica_electrodermal_activity
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SRC_FOLDER: "dbdp" # inside src/features/empatica_electrodermal_activity
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SRC_LANGUAGE: "python"
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SRC_LANGUAGE: "python"
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# See https://www.rapids.science/latest/features/empatica-blood-volume-pulse/
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EMPATICA_BLOOD_VOLUME_PULSE:
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EMPATICA_BLOOD_VOLUME_PULSE:
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TABLE: BVP
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TABLE: BVP
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PROVIDERS:
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PROVIDERS:
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@ -519,6 +524,7 @@ EMPATICA_BLOOD_VOLUME_PULSE:
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SRC_FOLDER: "dbdp" # inside src/features/empatica_blood_volume_pulse
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SRC_FOLDER: "dbdp" # inside src/features/empatica_blood_volume_pulse
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SRC_LANGUAGE: "python"
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SRC_LANGUAGE: "python"
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# See https://www.rapids.science/latest/features/empatica-inter-beat-interval/
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EMPATICA_INTER_BEAT_INTERVAL:
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EMPATICA_INTER_BEAT_INTERVAL:
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TABLE: IBI
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TABLE: IBI
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PROVIDERS:
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PROVIDERS:
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@ -528,6 +534,7 @@ EMPATICA_INTER_BEAT_INTERVAL:
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SRC_FOLDER: "dbdp" # inside src/features/inter_beat_interval
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SRC_FOLDER: "dbdp" # inside src/features/inter_beat_interval
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SRC_LANGUAGE: "python"
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SRC_LANGUAGE: "python"
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# See https://www.rapids.science/latest/features/empatica-tags/
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EMPATICA_TAGS:
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EMPATICA_TAGS:
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TABLE: TAGS
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TABLE: TAGS
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PROVIDERS: # None implemented yet
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PROVIDERS: # None implemented yet
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@ -537,21 +544,28 @@ EMPATICA_TAGS:
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# PLOTS #
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# PLOTS #
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########################################################################################################################
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########################################################################################################################
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# Data quality
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# Data quality ------
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# See https://www.rapids.science/latest/visualizations/data-quality-visualizations/#1-histograms-of-phone-data-yield
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HISTOGRAM_PHONE_DATA_YIELD:
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HISTOGRAM_PHONE_DATA_YIELD:
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PLOT: False
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PLOT: False
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# See https://www.rapids.science/latest/visualizations/data-quality-visualizations/#2-heatmaps-of-overall-data-yield
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HEATMAP_PHONE_DATA_YIELD_PER_PARTICIPANT_PER_TIME_SEGMENT:
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HEATMAP_PHONE_DATA_YIELD_PER_PARTICIPANT_PER_TIME_SEGMENT:
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PLOT: False
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PLOT: False
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# See https://www.rapids.science/latest/visualizations/data-quality-visualizations/#3-heatmap-of-recorded-phone-sensors
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HEATMAP_SENSORS_PER_MINUTE_PER_TIME_SEGMENT:
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HEATMAP_SENSORS_PER_MINUTE_PER_TIME_SEGMENT:
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PLOT: False
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PLOT: False
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# See https://www.rapids.science/latest/visualizations/data-quality-visualizations/#4-heatmap-of-sensor-row-count
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HEATMAP_SENSOR_ROW_COUNT_PER_TIME_SEGMENT:
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HEATMAP_SENSOR_ROW_COUNT_PER_TIME_SEGMENT:
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PLOT: False
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PLOT: False
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SENSORS: [PHONE_ACCELEROMETER, PHONE_ACTIVITY_RECOGNITION, PHONE_APPLICATIONS_FOREGROUND, PHONE_BATTERY, PHONE_BLUETOOTH, PHONE_CALLS, PHONE_CONVERSATION, PHONE_LIGHT, PHONE_LOCATIONS, PHONE_MESSAGES, PHONE_SCREEN, PHONE_WIFI_CONNECTED, PHONE_WIFI_VISIBLE]
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SENSORS: [PHONE_ACCELEROMETER, PHONE_ACTIVITY_RECOGNITION, PHONE_APPLICATIONS_FOREGROUND, PHONE_BATTERY, PHONE_BLUETOOTH, PHONE_CALLS, PHONE_CONVERSATION, PHONE_LIGHT, PHONE_LOCATIONS, PHONE_MESSAGES, PHONE_SCREEN, PHONE_WIFI_CONNECTED, PHONE_WIFI_VISIBLE]
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# Features
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# Features ------
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# See https://www.rapids.science/latest/visualizations/feature-visualizations/#1-heatmap-correlation-matrix
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HEATMAP_FEATURE_CORRELATION_MATRIX:
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HEATMAP_FEATURE_CORRELATION_MATRIX:
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PLOT: False
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PLOT: False
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MIN_ROWS_RATIO: 0.5
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MIN_ROWS_RATIO: 0.5
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@ -16,20 +16,24 @@ You can add new features to any existing sensors (see list below) by adding a ne
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As a tutorial, we will add a new provider for `PHONE_ACCELEROMETER` called `VEGA` that extracts `feature1`, `feature2`, `feature3` in Python and that it requires a parameter from the user called `MY_PARAMETER`.
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As a tutorial, we will add a new provider for `PHONE_ACCELEROMETER` called `VEGA` that extracts `feature1`, `feature2`, `feature3` in Python and that it requires a parameter from the user called `MY_PARAMETER`.
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??? info "Existing Sensors"
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??? info "Existing Sensors"
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An existing sensor is any of the phone or Fitbit sensors with a configuration entry in `config.yaml`:
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An existing sensor of any device with a configuration entry in `config.yaml`:
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Smartphone (AWARE)
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Smartphone (AWARE)
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- Phone Accelerometer
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- Phone Accelerometer
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- Phone Activity Recognition
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- Phone Activity Recognition
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- Phone Applications Crashes
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- Phone Applications Foreground
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- Phone Applications Foreground
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- Phone Applications Notifications
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- Phone Battery
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- Phone Battery
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- Phone Bluetooth
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- Phone Bluetooth
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- Phone Calls
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- Phone Calls
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- Phone Conversation
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- Phone Conversation
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- Phone Data Yield
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- Phone Data Yield
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- Phone Keyboard
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- Phone Light
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- Phone Light
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- Phone Locations
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- Phone Locations
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- Phone Log
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- Phone Messages
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- Phone Messages
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- Phone Screen
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- Phone Screen
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- Phone WiFI Connected
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- Phone WiFI Connected
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@ -28,8 +28,8 @@ Sensor parameters description for `[PHONE_DATA_YIELD]`:
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PHONE_LOCATIONS
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PHONE_LOCATIONS
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PHONE_LOG
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PHONE_LOG
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PHONE_SCREEN
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PHONE_SCREEN
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PHONE_WIFI_VISIBLE
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PHONE_WIFI_CONNECTED
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PHONE_WIFI_CONNECTED
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PHONE_WIFI_VISIBLE
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```
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```
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## RAPIDS provider
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## RAPIDS provider
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@ -74,26 +74,26 @@ Participant files link together multiple devices (smartphones and wearables) to
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|-------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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|-------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| `[DEVICE_IDS]` | An array of the strings that uniquely identify each smartphone, you can have more than one for when participants changed phones in the middle of the study, in this case, data from all their devices will be joined and relabeled with the last 1 on this list. |
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| `[DEVICE_IDS]` | An array of the strings that uniquely identify each smartphone, you can have more than one for when participants changed phones in the middle of the study, in this case, data from all their devices will be joined and relabeled with the last 1 on this list. |
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| `[PLATFORMS]` | An array that specifies the OS of each smartphone in `[DEVICE_IDS]` , use a combination of `android` or `ios` (we support participants that changed platforms in the middle of your study!). You can set `[PLATFORMS]: [infer]` and RAPIDS will infer them automatically (each phone data stream infer this differently, e.g. `aware_mysql` uses the `aware_device` table). |
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| `[PLATFORMS]` | An array that specifies the OS of each smartphone in `[DEVICE_IDS]` , use a combination of `android` or `ios` (we support participants that changed platforms in the middle of your study!). You can set `[PLATFORMS]: [infer]` and RAPIDS will infer them automatically (each phone data stream infer this differently, e.g. `aware_mysql` uses the `aware_device` table). |
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| `[LABEL]` | A string that is used in reports and visualizations. |
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| `[LABEL]` | A string that is used in reports and visualizations. |
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| `[START_DATE]` | A string with format `YYY-MM-DD` . Only data collected *after* this date will be included in the analysis |
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| `[START_DATE]` | A string with format `YYYY-MM-DD` or `YYYY-MM-DD HH:MM:SS`. Only data collected *after* this date time will be included in the analysis. By default, `YYYY-MM-DD` is interpreted as `YYYY-MM-DD 00:00:00`. |
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| `[END_DATE]` | A string with format `YYY-MM-DD` . Only data collected *before* this date will be included in the analysis |
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| `[END_DATE]` | A string with format `YYYY-MM-DD` or `YYYY-MM-DD HH:MM:SS`. Only data collected *before* this date time will be included in the analysis. By default, `YYYY-MM-DD` is interpreted as `YYYY-MM-DD 00:00:00`. |
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=== "[FITBIT]"
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=== "[FITBIT]"
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| Key | Description |
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| Key | Description |
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|------------------|-----------------------------------------------------------------------------------------------------------|
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|------------------|-----------------------------------------------------------------------------------------------------------|
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| `[DEVICE_IDS]` | An array of the strings that uniquely identify each Fitbit, you can have more than one in case the participant changed devices in the middle of the study, in this case, data from all devices will be joined and relabeled with the last `device_id` on this list. |
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| `[DEVICE_IDS]` | An array of the strings that uniquely identify each Fitbit, you can have more than one in case the participant changed devices in the middle of the study, in this case, data from all devices will be joined and relabeled with the last `device_id` on this list. |
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| `[LABEL]` | A string that is used in reports and visualizations. |
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| `[LABEL]` | A string that is used in reports and visualizations. |
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| `[START_DATE]` | A string with format `YYY-MM-DD` . Only data collected *after* this date will be included in the analysis |
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| `[START_DATE]` | A string with format `YYYY-MM-DD` or `YYYY-MM-DD HH:MM:SS`. Only data collected *after* this date time will be included in the analysis. By default, `YYYY-MM-DD` is interpreted as `YYYY-MM-DD 00:00:00`. |
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| `[END_DATE]` | A string with format `YYY-MM-DD` . Only data collected *before* this date will be included in the analysis |
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| `[END_DATE]` | A string with format `YYYY-MM-DD` or `YYYY-MM-DD HH:MM:SS`. Only data collected *before* this date time will be included in the analysis. By default, `YYYY-MM-DD` is interpreted as `YYYY-MM-DD 00:00:00`. |
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=== "[EMPATICA]"
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=== "[EMPATICA]"
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| Key | Description |
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| Key | Description |
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|------------------|-----------------------------------------------------------------------------------------------------------|
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|------------------|-----------------------------------------------------------------------------------------------------------|
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| `[LABEL]` | A string that is used in reports and visualizations. |
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| `[LABEL]` | A string that is used in reports and visualizations. |
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| `[START_DATE]` | A string with format `YYY-MM-DD` . Only data collected *after* this date will be included in the analysis |
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| `[START_DATE]` | A string with format `YYYY-MM-DD` or `YYYY-MM-DD HH:MM:SS`. Only data collected *after* this date time will be included in the analysis. By default, `YYYY-MM-DD` is interpreted as `YYYY-MM-DD 00:00:00`. |
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| `[END_DATE]` | A string with format `YYY-MM-DD` . Only data collected *before* this date will be included in the analysis
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| `[END_DATE]` | A string with format `YYYY-MM-DD` or `YYYY-MM-DD HH:MM:SS`. Only data collected *before* this date time will be included in the analysis. By default, `YYYY-MM-DD` is interpreted as `YYYY-MM-DD 00:00:00`. |
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### Automatic creation of participant files
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### Automatic creation of participant files
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You can use a CSV file with a row per participant to automatically create participant files.
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You can use a CSV file with a row per participant to automatically create participant files.
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