Adaptive Human-Swarm Interaction based on Workload Measurement using Functional Near-Infrared Spectroscopy

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...

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Bibliographic Details
Published in:arXiv.org 2024-05
Main Authors: Abioye, Ayodeji O, Landowska, Aleksandra, Hunt, William, Maior, Horia, Ramchurn, Sarvapali D, Naiseh, Mohammad, Banks, Alec, Soorati, Mohammad D
Format: Article
Language:English
Subjects:
Algorithms
Infrared spectra
Infrared spectroscopy
Machine learning
Medical imaging
Near infrared radiation
Workload
Online Access:Get full text
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Summary: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.
ISSN:2331-8422