Workload detection based on EEG device for Teleoperation of a Mobile Robot

EMANUEL SLAWIÑSKI; VICENTE MUT; VIVIANA MOYA; EDUARDO COUTO

Mar del Plata

Congreso; XVII Reunión de trabajo en Procesamiento de la Información y Control; 2017

Universidad Nacional de Mar del Plata

This paper proposes a brain signals based methodto evaluate a human operator workload while teleoperating amobile robot in presence of time delay. The procedure based ondenoising and decomposition wavelet transform can be applied toraw EEG signals, analyzing the energy in the delta band to detectfour states of cognitive workload. The index obtained is validatedusing the NASA-TLX question nary and quantitative metrics liketime-to-complete the task and error of path tracking.