Implementation of an Educational Wireless Biopotential Recorder Application
Tassi, Tatiana (2016)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2016092214474
https://urn.fi/URN:NBN:fi:amk-2016092214474
Tiivistelmä
The goal of the project was to implement a system to record electroencephalography biopotential measurements, and to send them wirelessly to a cloud storage service. Moreover, the application should allow the user to view and manage the recorded data using a browser. The application was planned to be used for educational purposes as a part of courses at Metropolia University of Applied Sciences. The EEG measurements were recorded using an OpenBCI 32bit board while the software application was implemented using Python 2.
The measurements consisted of a potential difference between each of the input electrodes and a reference electrode. The voltages were produced by the activity of the neurons closest to the area where the electrode was positioned. Displaying the measured voltages from each individual channel over time allowed the user to detect patterns in the signals produced by brain activity. In particular, patterns within defined frequency ranges correlated to specific types of brain activities.
The result of the project was an application which allows users to easily record EEG signals, which are then transmitted to and stored in the Metropolia cloud. The recordings can be viewed using the web application implemented as part of the project. In addition to displaying the recordings stored in the cloud, the application allows user to manage and organize the recordings based on parameters such as the patient from which they have been measured, the course of which the recording session is a component, and the instructor responsible for each course.
The initial goal of the project was achieved successfully. However, several improvements are possible as regards the security and the quality of the user experience of the application. Moreover, the system requires to be adapted to eventual future changes to the Metropolia cloud infrastructure. Nevertheless, the current state of the project can be useful as an educational tool and as a foundation for future development.
The measurements consisted of a potential difference between each of the input electrodes and a reference electrode. The voltages were produced by the activity of the neurons closest to the area where the electrode was positioned. Displaying the measured voltages from each individual channel over time allowed the user to detect patterns in the signals produced by brain activity. In particular, patterns within defined frequency ranges correlated to specific types of brain activities.
The result of the project was an application which allows users to easily record EEG signals, which are then transmitted to and stored in the Metropolia cloud. The recordings can be viewed using the web application implemented as part of the project. In addition to displaying the recordings stored in the cloud, the application allows user to manage and organize the recordings based on parameters such as the patient from which they have been measured, the course of which the recording session is a component, and the instructor responsible for each course.
The initial goal of the project was achieved successfully. However, several improvements are possible as regards the security and the quality of the user experience of the application. Moreover, the system requires to be adapted to eventual future changes to the Metropolia cloud infrastructure. Nevertheless, the current state of the project can be useful as an educational tool and as a foundation for future development.