Sensors & Passive Data

For a high-level overview of data collection capabilities, see Collect Rich Data.

mindLAMP continuously collects background sensor data from participants' devices without any action required. This includes GPS location, accelerometer, screen state, device motion, health metrics, and more. All sensor data follows a consistent JSON event format, making it straightforward to query, export, and analyze.

mindLAMP supports 9 device sensors (GPS, accelerometer, device motion, device state, steps, nearby devices, telephony, analytics, activity recognition) and 10 health platform sensors that read from Apple HealthKit or Google Health Connect (sleep, heart rate, HRV, respiratory rate, blood pressure, blood glucose, oxygen saturation, body temperature, workouts, nutrition). On enrolled iOS research devices, SensorKit provides additional data streams.

See the Sensor Reference for per-sensor documentation, or Sensor Configuration for setup and sampling rates.

In This Section

Sensor Usage

Data collection workflow, quality monitoring, and troubleshooting.

Sensor Configuration

Sampling types, rates, permissions, wearable setup, and health platform integration.

Sensor Data Format

SensorEvent format, data retrieval methods, Cortex analysis, and deprecated sensors.

Sensor Reference

Per-sensor documentation — data fields, platform support, sampling behavior, Cortex features, and configuration.

Further Reading

Configure sensors through the dashboard's Sensors tab. For programmatic access, see the API and SDKs. For per-sensor schemas, see the Sensor Reference. For the Cortex analysis pipeline (raw → primary → secondary features), see the Cortex documentation.