If people measure biosignals, they are usually connected via cables to a computer or at least a notebook, which is also pretty bulky. By using a mobile device like an android based smartphone or tablet, along with a wireless system, biosignal acquisition can be much more portable. Signal acquisition could be performed nearly everywhere. A software framework was recently created for g.Nautilus, providing functionality to measure biosignals and do some basic processing like applying digital filters, estimating bandpower or calculating bipolar derivation.
The application fields may be pretty similar to common computer based applications. It’s possible to record and process biosignal data on a mobile android device. A mobile acquisition device can also open up new possibilities. The software could be used for data-logging while walking, hiking or doing sports, among other options. Read more: The Unlimited Possibilities of Wireless EEG
The following images show some EEG recordings with different digital filters and tasks. The pictures show an example app that combines g.Nautilus with Android. The purpose of the app is to view the EEG in real-time and allow the user to apply simple processing steps like digital filters. The configuration dialog allows users to read the serial number of the connected g.Nautilus device. Furthermore, pre-defined grids, including channel numbers and names, can be applied to the selected g.Nautilus device. It is possible to enable or disable channels for data acquisition and apply pre-defined digital filters.
Image 1: This screenshot shows an example, in which 6 channels are selected for data acquisition. A digital bandpass filter from 0.1 to 30 Hz is applied.
The main window of the app allows the user to connect to a device and start a data acquisition with a previously defined configuration and processing. The main window is featuring a data scope to visualize acquired EEG data. It is possible to start or stop a data acquisition in this dialog. Furthermore, it is possible to record data and manipulate the data scope by zooming in or out.
Image 2: This shows an EEG signal, including alpha waves. Data was processed with a 48 to 52 Hz notch filter and a bandpass from 0.1 to 30 Hz.
Image 3: This shows an EEG signal overlaid with the EMG signal created by clenching the teeth.
g.tec created an application programming interface (API) that allows users to interface the wireless g.Nautilus with Android based software. Android Studio can be used for this development, and g.tec provides example code so that you can develop and implement your own applications.