Understanding your data
Calera Device Output Explained
Overview
Calera research devices deliver high-resolution data on core body temperature and physiological responses in a structured CSV file. Outputs include core body temperature, skin temperature, accelerometer data, heart rate when paired, and precise timestamps for detailed analysis.
Key Features
-
High-Resolution Sampling: 1Hz or 1-minute sampling.
-
Multi-Stream Data Output: Simultaneous collection of core temperature, skin temperature, heat flux, accelerometer, heart rate, and battery status in a single integrated dataset.
-
Comprehensive Metadata: Subject information, device specifications, firmware version, and calibration parameters are automatically included in every export file.
Overview
- Subject Information: Participant metadata integration
- Output Columns: overview of the collected data
- Understanding Acceloremeter Data: 3-axis accelerometer captures movement patterns and body orientation changes
- Understanding the Calculations: a brief overview of how calculations are made
Subject Information
On the top part of the CSV file, you can retrieve the following information:- BLE address
- Device ID
- Measurement ID
- Core temp
- Subject information: age, weight, height, gender (0 = male, 1 = female)
- Position of the device
- Permission level = C is for researchers
- Firmware information (version & channel)
Output Columns
| timestamp [us] | Timestamp in UNIX time in us (microseconds elapsed since January 1th 1970) |
| time [UTS - OFS =+ 0100] | Timestamp of the data point in the format "DD:MM:YYYY hh:mm:ss" |
| hf_a0 | Raw heat flux sensor signal in ADC counts (unitless). |
| temp_a0 [mC] | Uncorrected skin temperature signal in millidegree Celsius. |
| status | Debugging Information |
| hr | Beats per minute (bpm) of the heart |
| ax, ay, az | X, Y, and Z component of acceleration in counts. Divided by 64 to get acceleration in G. |
| battery_voltage [mV] | Coin cell voltage in millivolts. Can be used to estimate battery health. |
| cbt [mC] | Core body temperature estimation output in millidegrees. |
Understanding Acceloremeter Data
Accelerometers measure acceleration, not position, using X, Y, and Z axes based on the device’s orientation.
The device records movement data every second, making it easy to see when someone is active or still.
To figure out which axis is which, place the device on a flat surface. The axis pointing up or down will show about ±1g (you can find this by dividing the raw number by 64). Try rotating the device to see how the values change, this helps you understand how each axis responds to movement.
Understanding the Calculations
To obtain heat flux and skin temperature, some short calculations need to be done.
How to obtain calibrated heat flux and offset-corrected skin temperature:
| Heat flux: |
Multiply the raw heat flux sensor signal by 1.953125 uV to get the raw sensor voltage. To obtain a heat flux value in W/m2, you additionally need to divide the sensor signal by its corresponding sensitivity. The sensitivity of each sensor is given in row 13 of the header section (S0 and S1) in the unit of nV/ (W/m2) Heat flux sensor A voltage [in uV] = hf_a0 [in counts] * 1.953125 uV Heat flux A [in W/m2] = hf_a0 [in counts[ * 1.953125 / (S0/1000) |
| Skin temperature |
Remove sensor offset (Tni_off in row 13 of the header ) and divide by 1000. Skin Temperature [in °C] = (temp_a0 [in mC] - Tni_off)/ 1000 Note: In older files, the Tni_off value might be missing. In that case use T0_off and following formula, which will lead to the same result: Skin Temperature [in °C] = (temp_a0 [in mC] - T0off - 213)/ 1000 |
The table below shows the status column, which provides a quality score from 0 to 4, with 4 indicating the highest data quality.
| Status | Status in hexadecimal | Quality |
| 18 | 0x12 | 2 |
| 33 | 0x21 | 1 |
| 34 | 0x22 | 3 |
| 35 | 0x23 | 3 |
| 36 |
0x24 |
4 |