System for acquisition of the biosignals from BITalino board.
This topic introduce the project developed, describing each part of the topology and how the data flows. This project has as objective to implement a system for acquisition of the biosignals from the BITalino board via bluetooth, these signals are received and processed, after the processing, the data is stored in the database and can be viewed in a web dashboard.
In this project all ports are defined and changed into other range to avoid conflict and security.
-
18000 -> Web / Dashboard (Grafana)
-
18001 -> Database (PostgreSQL)
-
18002 -> Processing (Python) - Socket between Acquisition application and Processing application
In this section is presented how to use this project. In the first part is introduced how to install all dependencies and prepare the enviroment to be ready to apply the project. In the next step is presented how to use and modify each service/application.
First of all it is necessary install and configure the libraries for the environment are ready to applications.
2.1.1 - Bluetooth:
-
Install the bluetooth library:
sudo apt-get install pi-bluetooth -
Start the configuration:
sudo bluetoothctl -
Scan to find bluetooth address:
scan on -
Connect with the device:
pair xx:xx:xx:xx:xx:xx
2.1.2 - Docker:
!!! Raspberry Pi uses the ARM architecture, so will not be compatible with all containers. Images need to be built from an ARM base !!!
-
Install the docker:
curl -sSL https://get.docker.com | sh -
Add the user:
sudo usermod -aG docker pi -
Enable the docker to start with the system:
sudo systemctl enable docker -
Restart the system:
sudo reboot -h now
2.1.3 - Docker Compose:
-
Install the dependencies:
sudo apt-get install -y libffi-dev libssl-dev -
Install Python 3:
sudo apt-get install -y python3 python3-pip -
Install Docker Compose:
sudo pip3 install docker-compose
After to prepare the enviroment to use the docker compose it is necessary to run the containers to start the application to processing the data, the database and the dashboard. The file that defines the parameters for each service is the 'docker-compose.yml', in this file is defined the network amoung services that will be the 'my-network' with brigde caracteristic. In the next topic is defined the service, for each service is assigned an image that will be based, for the web service will be used the image grafana/grafana:7.0.0, the service database will use the image postgres:9.6 and the processing service will use the image python:3.8.3.
In each service, also is declareted different ports with external visibility. To run the docker compose the path must be changed in the bash with to the folder that are the files of this project, in sequence using cd Docker and docker-compose up -d to run the containers.
Inside the folder 'database' there are two files, the first file is used to inicialize the database 'bitalino' and the table 'patients' with categories 'name', 'ecg', 'eda' and 'time'. The second file is used to check if the database and table was created properly. This database created use the exposed port 18001, user postgres and the password is not defined.
Inside the folder 'web' there are other two folders. The folder 'datasources' there is the file (datasource.yaml) with the configuration of the database (PostgreSQL) that will be used to get the data to monitoring. The folder 'dashboards' there are two files, the first file (dashboard.yaml) is used to configure the dashboard properly and the second file (Patients.json) is used to have the dashboard entirely configured. To access the dashboard use the Raspberry's IP and port 18000 (e.g. 127.0.0.1:18000).
After initialized the Grafana's container, it is necessary to set the dashboard to visualize the database. By default the user and password are admin / admin, in the sequence you can define another password, all steps to set the predefined dashboard in the Grafana are list below in the figure.
Inside the folder 'processing' there are two files, the first file (start_processing.sh) is used to download the necessary libraries, after the download the second line call the other file (processing.py). The python code has the goal to receive all data from the C++ code via socket, the python code opens UDP sockets as server.
In the first part of the code are defined the libraries, in the second part are difined the global variables of the code, the function socket.socket(socket.AF_INET, socket.SOCK_DGRAM) define the protocol and bind('',18002) is used to define the IP address and port of the socket server. In the third part of the code is defined the functions, in this part there is the 'register_datasabe' function used to make the connection with the database and post the data. The variable DSN = 'dbname=bitalino user=postgres host=database' define the database, user and host that will be used and the variable SQL = 'INSERT INTO patients (name, ecg, eda, time) VALUES (%s, %s, %s, %s)' define what it is the table that will be saved all data and categories.
Finally, in the fourth part is the main function, a loop that opens the socket and receives the information from the acquisition application. Each data is received from the C++ code with a different caracter for identify the kind of data and is converted into the correct format. After all data are received, the program call the function 'register_datasabe' to make the connection with the database and post the data.
The first step to use the application it is define the bluetooth address in the acquisition.cpp file in the variable BITalino dev("xx:xx:xx:xx:xx:xx"). In the acquisition.cpp file there are others options to configure the system, for example the channels that will be monitored (channel 1 = ECG; channel 2 = EDA) or the port of the sockets, all these options are described in the code.
The next step must change the path in the bash to the path with all files, now it is possible generate the executable file using the command make. After this, the application is able to use with the command ./acquisition. Turn on the BITalino and fill name and last name to start the acquisition. To finish the acquisition it is necessary tap the 'enter' in the keyboard to stop the acquisition and disconnect properly the BITalino.
-
List Images:
docker image ls -
List Containers:
docker container ls -a -
List Volumes:
docker volume ls -
List Networks:
docker network ls -
Remove Unnecessary Volumes:
docker volume prune -
Remove Unnecessary Networks:
docker network prune -
Remove Images:
docker image rm xxxxxx -
Remove Containers:
docker image rm xxxxxx -
Remove Volumes:
docker image rm xxxxxx -
Remove Networks:
docker image rm xxxxxx
-
Up Docker-Compose with Logs:
docker-compose up -
Up Docker-Compose without Logs:
docker-compose up -d -
Check Docker-Compose:
docker-compose ps -
Down Docker-Compose:
docker-compose down -
Logs of Docker-Compose:
docker-compose logs -t -f -
Logs of Processing Application:
docker-compose logs -t -f processing -
Logs of Database Application:
docker-compose logs -t -f database -
Logs of Dashboard Application:
docker-compose logs -t -f web -
Check the Creation of Database:
docker-compose exec database psql -U postgres -f ./database/check.sql -
Check the Database:
docker-compose exec database psql -U postgres -d bitalino -c 'select * from patients'