Multimodal Physiological Monitoring During Virtual Reality Piloting Tasks

This dataset includes multimodal physiologic, flight performance, and user
interaction data streams, collected as participants performed virtual flight
tasks of varying difficulty. In virtual reality, individuals flew an
"Instrument Landing System" (ILS) protocol, in which they had to land an
aircraft mostly relying on the cockpit instrument readings. Participants were
presented with four levels of difficulty, which were generated by varying wind
speed, turbulence, and visibility. Each of the participants performed 12 runs,
split into 3 blocks of four consecutive runs, one run at each difficulty, in a
single experimental session. The sequence of difficulty levels was presented
in a counterbalanced manner across blocks. Flight performance was quantified
as a function of horizontal and vertical deviation from an ideal path towards
the runway as well as deviation from the prescribed ideal speed of 115 knots.
Multimodal physiological signals were aggregated and synchronized using Lab
Streaming Layer. Descriptions of data quality are provided to assess each data
stream. The starter code provides examples of loading and plotting the time
synchronized data streams, extracting sample features from the eye tracking
data, and building models to predict pilot performance from the physiology
data streams.