Wearable Accelerometer Desktop Client

This application uses QFluentWidgets framework https://qfluentwidgets.com

This repository contains the source code for wearable accelerometer Desktop Client.

Prerequisites

• Python 3.7 or <= 3.12

Installation

1. Clone the repository and navigate to the project directory.

https://github.com/biospi/wearableAccelerometerClient.git
cd wearableAccelerometerClient

2. Create a virtual environment

python -m venv .venv
.\.venv\Scripts\activate    # Windows
source .venv/bin/activate   # macOS/Linux

3. Install the required dependencies.

You can install the required dependencies by running:

pip install -r requirements.txt

Running the Application

To launch the GUI, run the following command:

python src/gallery/gui.py

This will open the main window of the application. If your system has DPI scaling enabled, the application will automatically adjust accordingly.

Building the Executable (Windows)

You can package this into a single .exe file so that collaborators don’t need Python installed.

pyinstaller --onefile --noconsole .\src\gallery\gui.py

Quick Start

This section should get you started collecting accelerometer data from the wearable accelerometer. Wou will need:

• Wearable accelerometer
• Micro SD card (FAT32 formatted)

• Magnet
• USB-C cable
• Bluetooth capable laptop
• The "Wearable Accelerometer Desktop Client" software from this repository. For Windows PC binaries are available here

1. Prepare the micro SD

If not already formatted, format the micro sd (FAT32)

Optional:

Note

If you choose to create a config.txt file at the root of the micro-SD card, you can override the device’s default sensor and logging behavior. Below is a description of each available parameter.

Config.txt example:

xyz_sens=1.2
xyz_sampling=25
xyz_buffer_size=2560
flip_count=99999
count_only=1
no_log=0

Parameter	Description
xyz_sens	Sets the XYZ sensor sensitivity (e.g., accelerometer gain). Higher values make the system more responsive to smaller movements.
xyz_sampling	Sampling rate in Hz. Determines how many sensor samples are captured per second. Higher values increase accuracy but also power usage and file size.
xyz_buffer_size	Size of the internal buffer (in samples). Larger buffers reduce the risk of overflow but require more RAM.
flip_count	Maximum number of "flip" events the device will detect before enabling Bluetooth discovery
count_only	When set to 1, the device saves activity counts. When 0, full data (x,y,z, activity_count) logging is enabled.
no_log	When set to 1, disables logging to the SWD port. When 0, logging is enabled as normal.

2. Charging

Plug a USB-C cable in the accelerometer port with a standard (5V 1-3A) power source, like a laptop or a smartphone charging brick. The LED indicator will light up solid red indicating that the device is charging.

3. Turn on and start recording data

To turn on the device briefly swipe a magnet over the top. When the device turns on, the light indicator will briefly flash white.

The accelerometer is now automatically saving data to the micro-sd card, it will automatically go to sleep when no motion is detected and wake up when motion is detected.

You are now ready to place the accelerometer on a subject, to access the data simply remove the micro-sd card and read it on your computer.

Note

To manually turn off the device swipe the opposite side of the magnet over the top of the device.

4. Bluetooth connection

Connecting to the device via the "Wearable Accelerometer Desktop Client" allows to:

• Set the accelerometer internal clock (automatic on first connection)
• Configure the accelerometer sensitivity and sampling rate
• Stream and visualise the accelerometer data in real time

To enable Bluetooth discovery hold a magnet 5 seconds above the top of the device and remove it. The light indicator will blink blue to confirm that the device is now discoverable

Make sure that Bluetooth is enabled on your laptop and open Connecting to the device via the "Wearable Accelerometer Desktop Client"

1. click the "Scan button"

2. Select the "Accelerometer" in the list

3. On the left menu select the gear icon to access the setting menu

4. On the left menu select the "arrow down" icon to access the data streaming menu

5. Data

Once powered on, the device automatically begins recording motion data to an MS Excel–compatible CSV file. Each row represents one sample collected at a fixed sampling rate. A typical data snippet looks like:

Column	Name	Description
A	Timestamp	A 12-digit timestamp in the format YYMMDDhhmmss: • YY – year • MM – month • DD – day • hh – hour (24-hour format) • mm – minutes • ss – seconds Example: 250126043757 → 2025-01-26 04:37:57
B	X-axis	Raw acceleration value along the X axis (units depend on device configuration, commonly g or m/s²).
C	Y-axis	Raw acceleration value along the Y axis.
D	Z-axis	Raw acceleration value along the Z axis.
E	Activity Count	A derived value representing the estimated activity level at that timestamp.

A sample cat dataset is available here

Note

Depending on the device configuration, not all columns may be present. For example, if count_only mode is enabled, only the Activity Count column will be recorded in the CSV file.

License

This project is licensed under the GPLv3 License. See the LICENSE file for details.