Maltese researchers have developed Artificial Intelligence software that allows people with restricted mobility to control a motorised bed using their brain signals.

Called BrainApp, the brain-controlled human-machine interface has reached prototype stage.

It can also be extended to other uses beyond motorised beds. “BrainApp provides an alternative means of control to individuals who cannot control standard interfaces, to give them more independence and a better quality of life,” project coordinator Tracey Camilleri,  from the University of Malta’s Department of Systems and Control Engineering, said.

There was a gap in the market, she said. If a person wanted to control a device using brain signals, they could buy a headset but there was a missing link between the headset and the device to be controlled. BrainApp, she said, is the first customisable prototype of what could become a whole suite of apps to control different machines.

Project manager Kenneth Camilleri, from the Centre for Biomedical Cybernetics, emphasised the need for more funding so that local researchers could take the prototype to the next level.

The €136,335 BrainApp project was funded by the Malta Council for Science and Technology and was carried out by the University of Malta in collaboration with development firm Eight Eight (88.eu). Speaking during an event held at

Esplora, Tracey Camilleri and Kenneth Camilleri explained that BrainApp is built on existing technologies but seeks to improve the user experience and comfort levels.

Brain-computer interfaces have been around for a long time, allowing people to interact with an external device directly from the brain. However, for many years, the most effective interfaces were invasive and required the implantation of devices into the brain. As technology evolved, the EEG (Electroencephalography) interface provided a non-invasive option, with electrodes placed on specific locations on the human skull. BrainApp uses EEG technology.

Comfortable headgear reads and relates the brain signals into the BrainApp software that then reads and relays that message to the device (in this case a motorised bed) using algorithms.

BrainApp users can turn on the system with a double blink, select their bed position by looking at an icon for two or three seconds and correct any wrongly selected choice with a double blink.

The software uses machine learning technology, which means that it learns as the user makes use of it.

It can be used for countless other purposes beyond motorised beds. “It could provide alternative means of communication and control, assist rehabilitation, help detect diseases and provide mental state warnings, among others,” Kenneth Camilleri said.