The drone rises from the ground and hovers… the young man on the bench has relaxed his mind and now he is watching the drone. He relaxes his mind again and the drone sinks slowly to the ground, controlled by his brain waves.
This sounds like science fiction but it is not. Zhiyi Huang from Computer Science – with a team of computer science and psychology researchers – is developing this Brain Computer Interface with a number of outcomes in mind.
“We have external funding from Chinese companies (Shenzhen Hampoo Science & Technology Co. Ltd and its spinoff EEGSmart) who initially wanted to develop video game controllers using EEG technology, reading brainwaves and translating those into commands that are then sent to the game via Bluetooth. But this work has a number of medical applications also – for people who have limited mobility and also for people who suffer from mood disorders; the Chinese company is interested in following through on these therapeutic uses as well.”
While standard diagnostic EEG readers extend over the whole head and read 32 channels, this is a narrow band that fits around the forehead and reads only one channel. The EEG readings are taken by the headband with a built-in amplifier. This amplifier sends the signals to a small computer via Bluetooth technology, the computer processes the brainwave patterns and translates them into instructions and these instructions are sent via Bluetooth to the drone or video game. The Brain Computer Interface can also be used to control a mouse, allowing people with limited hand or arm movement to use their computers more easily.
“The computer software is quite complicated and it involves a lot of maths! There are machine learning algorithms, as well as signal processing algorithms. We use these very small computers called Raspberry Pi to do the processing.”
Zhiyi and his Computer Science colleagues Xiping Fu (research assistant) and Terence Mayne (programmer) have been working closely with Professor Liz Franz and Phoebe Neo in Psychology and in the coming year will extend this research with Professor Neil McNaughton in Psychology. Professor McNaughton’s expertise in detecting brainwaves that indicate anxiety should help them to develop a system where the headset can pick up building levels of anxiety or depression and activate remedial outputs – either gaming tasks that will lift mood, or music that will encourage the person to relax, or using the drone to train people to relax their minds in stressful situations.
“There are several unsolved issues for us as scientists – can one single EEG channel deliver enough information or will we need to add a few more channels to give greater definition and accuracy? Can we deliver a better neural feedback system to improve outcomes for users?”
The team for the Brain-Computer Interface:
Dr Phoebe Neo, Psychology
Xiping Fu, research assistant, Computer Science
Terence Mayne, programmer, Computer Science
Professor Liz Franz, Psychology
Zhiyi Huang, Computer Science
With help from undergrad contributors Philip Hodder and Patrick Murrow
The team for the mood-related research which will use the BCI system for further research:
Dr Phoebe Neo, Psychology & Computer Science
Professor Neil McNaughton, Psychology
Shenghuan Zhang, PhD student, Computer Science
Zhiyi Huang, Computer Science