  One of the challenges of human-swarm interaction (HSI) is how to manage the
operator's workload. In order to do this, we propose a novel neurofeedback
technique for the real-time measurement of workload using functional
near-infrared spectroscopy (fNIRS). The objective is to develop a baseline for
workload measurement in human-swarm interaction using fNIRS and to develop an
interface that dynamically adapts to the operator's workload. The proposed
method consists of using fNIRS device to measure brain activity, process this
through a machine learning algorithm, and pass it on to the HSI interface. By
dynamically adapting the HSI interface, the swarm operator's workload could be
reduced and the performance improved.
