Drones have been widely used for search and rescue purposes when disasters such as earthquakes, landslides and shipwrecks strike. Chinese researchers have developed a brain-controlled rescue drone that enables the unmanned aircraft to have a precise and reliable identification function during sandstorms, haze and other low-visibility weather.

According to its developer, a Beijing institution under the China Academy of Launch Vehicle Technology, the drone system mainly comes in the form of a headset with electrodes, which can detect the brain's electrical activity, or brain waves, using electroencephalography (EEG).

Humans' brain waves change according to what we are doing and feeling. When slower brain waves are dominant, we will feel tired, slow or sluggish. When higher frequencies are dominant, we will feel active, excited or hyper-alert.

When users watch drone-captured images from disaster sites transferred in real-time, the sensors on the headset will record and collect the changes in their brain waves. Then, an EEG data-analysis system, after performing a series of analyses and computations, will identify the targets and alert them to the drone.

Users do not need to speak or use gestures.

It's not rare to monitor brain signals, but many advanced laboratory tools still have trouble interpreting them. The brain-controlled system can make up for those shortcomings, said researchers.

The system can read brain waves in milliseconds, allowing the drone to identify targets at almost the same moment as the user.

Most rescue drones use an image-recognition system, which can identify targets after comparing them to reference images stored in the system.

However, in real-world circumstances, if a target is partially covered, or if there is a sandstorm or heavy fog affecting the light in the rescue site, such drones will have difficulty performing their task.

The brain-controlled rescue drone, which identifies targets with the help of the users' eyes, can see what a conventional drone would be unable to detect in complex situations.

Similar to the game of hide-and-seek, even if a hider carelessly shows their foot, the seeker can still see them at a glance, while a machine might not.

Researchers say the system could increase the accuracy of drone-identification abilities by 20 percent.