OBJECTIVE: The fact that all human action is preceded by brain processes partially observable through neuroimaging devices such as electroencephalography (EEG) is currently being explored in a number of applications. A recent study by Haufe et al (2011 J. Neural Eng. 8 056001) demonstrates the possibility of performing fast detection of forced emergency brakings during driving based on EEG and electromyography, and discusses the use of such neurotechnology for braking assistance systems. Since the study was conducted in a driving simulator, its significance regarding real-world applicability needs to be assessed. APPROACH: Here, we replicate that experimental paradigm in a real car on a non-public test track. MAIN RESULTS: Our results resemble those of the simulator study, both qualitatively (in terms of the neurophysiological phenomena observed and utilized) and quantitatively (in terms of the predictive improvement achievable using electrophysiology in addition to behavioral measures). Moreover, our findings are robust with respect to a temporary secondary auditory task mimicking verbal input from a fellow passenger. SIGNIFICANCE: Our study serves as a real-world verification of the feasibility of electrophysiology-based detection of emergency braking intention as proposed in Haufe et al (2011 J. Neural Eng. 8 056001).
OBJECTIVE: The fact that all human action is preceded by brain processes partially observable through neuroimaging devices such as electroencephalography (EEG) is currently being explored in a number of applications. A recent study by Haufe et al (2011 J. Neural Eng. 8 056001) demonstrates the possibility of performing fast detection of forced emergency brakings during driving based on EEG and electromyography, and discusses the use of such neurotechnology for braking assistance systems. Since the study was conducted in a driving simulator, its significance regarding real-world applicability needs to be assessed. APPROACH: Here, we replicate that experimental paradigm in a real car on a non-public test track. MAIN RESULTS: Our results resemble those of the simulator study, both qualitatively (in terms of the neurophysiological phenomena observed and utilized) and quantitatively (in terms of the predictive improvement achievable using electrophysiology in addition to behavioral measures). Moreover, our findings are robust with respect to a temporary secondary auditory task mimicking verbal input from a fellow passenger. SIGNIFICANCE: Our study serves as a real-world verification of the feasibility of electrophysiology-based detection of emergency braking intention as proposed in Haufe et al (2011 J. Neural Eng. 8 056001).
Authors: Benjamin Blankertz; Laura Acqualagna; Sven Dähne; Stefan Haufe; Matthias Schultze-Kraft; Irene Sturm; Marija Ušćumlic; Markus A Wenzel; Gabriel Curio; Klaus-Robert Müller Journal: Front Neurosci Date: 2016-11-21 Impact factor: 4.677
Authors: Luca Ascari; Anna Marchenkova; Andrea Bellotti; Stefano Lai; Lucia Moro; Konstantin Koshmak; Alice Mantoan; Michele Barsotti; Raffaello Brondi; Giovanni Avveduto; Davide Sechi; Alberto Compagno; Pietro Avanzini; Jonas Ambeck-Madsen; Giovanni Vecchiato Journal: Sensors (Basel) Date: 2021-12-07 Impact factor: 3.576
Authors: Giovanni Vecchiato; Maria Del Vecchio; Jonas Ambeck-Madsen; Luca Ascari; Pietro Avanzini Journal: Cogn Neurodyn Date: 2022-01-11 Impact factor: 3.473
Authors: Daniel E Callan; Cengiz Terzibas; Daniel B Cassel; Masa-Aki Sato; Raja Parasuraman Journal: Front Hum Neurosci Date: 2016-04-27 Impact factor: 3.169