Tutorial 1: Getting Started with BI-Vital

1. Become Familiar with BI-Vital

Before recording your own dataset, you will first get to know the BI-Vital system.
In this part, you will install the app, explore the sensor hardware, connect via Bluetooth,
and interact with the live data stream. This ensures you understand the basic functionality
of both the device and the app before performing your own measurement.

1.1 Install the BI-Vital App

Download and install the BI-Vital App on your smartphone:

Open the app and explore the main menu to get an initial overview of the available tools (e.g., DataPlotter, Settings, Info).

1.2 Power on and Explore the BI-Vital Sensor

Turn on your BI-Vital sensor and follow the
First Steps guide (Steps 1–3).

Get familiar with:

the hardware buttons
the LED indicators

1.3 Connect via Bluetooth in the DataPlotter

Open the DataPlotter tool inside the BI-Vital App.

Establish a Bluetooth connection using the 4-digit MAC address printed on the front of the sensor.

1.4 Explore Available Sensor Data

Inside the DataPlotter:

Explore the available sensor channels
Adjust measurement settings (e.g., window size, sampling rate)
Start and stop live measurements
Interact physically with the sensor and observe the changes in real time

Try different configurations to understand how BI-Vital responds under various conditions.

2. Record Your Own BI-Vital Dataset (3–5 minutes walking)

In this part, you will collect your first BI-Vital dataset.
You will record 3–5 minutes of movement (walking and simple activities) using the BI-Vital sensor and chest belt.
This dataset will later be used for signal exploration and basic Python analysis.

The process consists of three steps:

2.1 Preparation of the Experiment

Before recording, configure the BI-Vital using the Web Toolbox

Use the following configuration:

Acceleration (X, Y, Z) at 100 Hz
Battery level every 10 seconds
Temperature every 1000 ms
Heart Rate: no update interval required
- Only measurable when the chest belt is placed on bare skin
- You may decide whether you want to include heart rate in your experiment

After configuring:

Click “Upload” to save the configuration to the BI-Vital
Scroll to the Storage List at the bottom
If previous recordings exist, format the storage
Disconnect the BI-Vital from USB

Your sensor is now ready for recording.

2.2 Record and Label the Experiment

Open the BI-Vital App on your smartphone
Start the LinkHub module
Select your BI-Vital from the device list
- (It must be powered on and visible via Bluetooth)
In the next screen, start the measurement remotely
The BI-Vital will vibrate, confirming that recording has started
Walk around for 3–5 minutes with the chest belt and sensor attached.

During the experiment, perform several activities and label them live in the app.
Here is an example procedure:

Start Walking
Stop Walking
Start Stair Walking
Stop Stair Walking
Start Squats
Stop Squats
Stop the recording in the LinkHub app
The BI-Vital will vibrate again as confirmation

2.3 Analyse / Evaluate the Experiment

After finishing your recording, follow these steps to download your data and prepare it for analysis:

Download your measurement file
Connect the BI-Vital to your computer and use the Web Toolbox to download the recorded data file to your PC.
Afterwards, format the BI-Vital memory (also in the Web Toolbox) so the device is empty for future recordings.
Finally, shut down the BI-Vital using the user button.
Download your label file from the LinkHub App
Open the LinkHub App: On the welcome screen, navigate to the Labels folder.
Download the label file to your smartphone’s general download storage.
Then transfer this file (e.g., via USB, AirDrop, or cloud sync) from your smartphone to your PC.
Analyse your data using Python
Follow the BI-Vital Python tutorial available here:
How-To Use Python Lib for Datasets

In the basic_example notebook, adjust the plotting code so that all sensor values you configured earlier (e.g., acceleration, temperature, battery, heart rate if recorded) are visualized.
This ensures that your recorded dataset is fully represented and allows you to inspect the behavior of each signal inside the Jupyter notebook.

You now have both your measurement data and the optional label file ready for further analysis in Python.

3. Record Your Own BI-Vital Dataset Using the Serial Terminal (3–5 minutes walking)

In this part, you will repeat the previous experiment, but this time you will configure and control the BI-Vital exclusively via the serial terminal, without using the mobile app.
You will again record 3–5 minutes of movement with multiple activities.
This dataset will later be analysed in Python in the same way as in Exercise 2.

The process consists of three steps:

3.1 Preparation of the Experiment

Before recording, configure the BI-Vital using a serial terminal.
You may use the Web Serial Terminal or any terminal program on your PC:

Connect the BI-Vital via USB and open the serial terminal.
A welcome screen should appear.
Enter the configuration menu by typing:
```
measure -config
```
Configure the following sensors:
- ECG Raw → no update rate required
- ECG Quality Index → no update rate required
- Euler Angles (roll, pitch, yaw) → 10 Hz
- Temperature, Humidity, Pressure → 1 Hz
Test your configuration by typing (quit with pressing “q” on your keyboard):
```
measure -live
```
Format the internal storage:
```
fs -format -backup
```
Disconnect the BI-Vital from USB.
Your device is now ready for recording.

3.2 Record the Experiment (without App)

For this exercise, you will not use the BI-Vital App.
Start and stop the recording directly on the BI-Vital hardware using the User-Button.
For details on hardware-based measurement control, see:
First Steps with BI-Vital - Sections 4.2 and 4.3
Perform a 3–5 minute measurement while walking and doing several activities (e.g., stairs, squats, slow/fast walking).

No labels are created in this exercise.

3.3 Analyse / Evaluate the Experiment

This time you do not download the data using the Web Toolbox.
Instead, use the BI-Vital Python tools directly:
- Create a new project and series using bvtool
- Then use bvtool data to import the recording directly from the BI-Vital hardware (for that the BI-Vital Hardware should be connected via USB to your PC)
After importing, analyse your data in Python exactly as in Exercise 2:

Follow the BI-Vital Python tutorial:
How-To Use Python Lib for Datasets

In the basic_example notebook, adjust the plotting code so that all sensor values you configured earlier
(ECG raw, ECG quality, Euler angles, environmental data) are visualized.
This ensures that your recorded dataset is fully represented and allows you to inspect the behavior of each signal inside the Jupyter notebook.

You now have a second dataset recorded using an alternative workflow and can compare both approaches in your analysis.