In just a few years, planes may be able to use an interface to assess the cognitive and emotional states of their pilots and "act" accordingly to ensure the safety and well-being of passengers and flight attendants. Carried out by the ISAE Aeronautics and Space Insititute (Toulouse, France), a recent study has demonstrated the potential benefits of monitoring brain activity in pilots during real flight conditions. It’s an opportunity to discover how neuroergonomics can optimize human-machine interactions.

There is growing interest in the use of tools to monitor individuals’ cognitive performance in their work environment and daily lives. Known as neuroergonomics, this area of research encourages the use of wearable devices to measure the activity of the "brain at work" in an ecologically valid setting. For example, researchers can use functional near-infrared spectroscopic imaging (fNIRS), which has the advantage of leaving the participant (whose efforts are being recorded) free to move. Aeronautics is an ideal “playground” for demonstrating the value of applying the neuroergonomic approach to BCI (Brain Computer Interface) technology. Indeed, a better understanding of the cognitive processes underlying this type of interaction could prove useful for improving both safety and human performance.

The scientific team from ISAE and Drexel University (Philadelphia) used an outpatient technique known as spectroscopy and equipped 28 pilots in order to measure their brain activity on the job. The aim was to precisely measure changes in blood oxygenation in the prefrontal cortex, which is involved in cognitive functions such as problem solving, memory, judgement, and impulse control. Among the volunteer pilots, 14 (average age = 29.25; 3 women / 11 men; average flying hours = 80) were recorded in a flight simulator. The other 14 pilots (average age = 23.07; 1 woman/13 men; average flying hours = 44.07) were recorded under real flight conditions. Whether they were in a virtual or real aircraft cabin, during the flight, each pilot had to perform a series of memorization tasks.

The pilots had to listen to various air traffic control instructions and repeat them. All of the messages began with the aircraft’s call sign, immediately followed by a sequence of flight parameters, and ended with "over." The pilot then had 18 seconds to repeat the instructions. In order to familiarize the subjects with the protocol, a training session was conducted prior to the experiment. Then, each of them had to repeat 20 instructions of varying difficulty in terms of memorization. Half of the messages represented a low load on working memory (the first 2 digits were the same for each flight parameter, for example: speed 140, heading 140, altitude 1400, vertical speed +1400). For the other half of the messages, the values were different for each parameter. The experimenter evaluated the pilot’s ability to repeat the instructions and the fNIRS data were recorded during the task.

The results of this study indicate that pilots working under real flight conditions made more errors and showed more activation in the prefrontal cortex than their colleagues in the simulator. But more importantly (and reassuringly), the pilots performed very well in both conditions (with working memory scores over 76%).

This study demonstrates the need for monitoring pilots’ cognitive load in a real flight situation. According to the authors, it also highlights the potential benefit of having a tool built into the human-machine interface that can “read the pilot’s mind” in real-time and assess his or her attention level and ability to process new information. These ideas take us back to the field of artificial intelligence with the goal of boosting human performance.