Optical brain monitoring for operator training and mental workload assessment
By H. Ayaz, P. Shewokis, S. Bunce, K. Izzetoglu, B. Willems, B. Onaral. NeuroImage, 2012
657 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Surgery
View Paper: https://www.semanticscholar.org/paper/11a5e8c7375f923f9ed1f858cd94ca0d6aa2a47a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
In Radiology, Nuclear Medicine and Imaging
In Surgery
Citations in the corpus
- Mental workload during n-back task—quantified in the prefrontal cortex using fNIRS (2014, background): “Cognitive workload has been assessed for air-traffic controllers in several studies Ayaz et al. (2010, 2012).”
- State of science: mental workload in ergonomics (2015, background): “…a cognitive task is increased (Boag et al. 2006; Halford, Wilson, and Philips 1998), or the bandwidth of a tracking task is increased (driving along a winding road at faster and faster speeds) or the number of aircraft that a controller needs to supervise in his/her sector rises (Ayaz et al. 2012).”
- fNIRS-based brain-computer interfaces: a review (2015, methodology): “Some studies have demonstrated direct decoding of neural correlates corresponding to subjective preferences (Luu and Chau, 2009), deception (Hu et al., 2012), visual stimuli (Faress and Chau, 2013), and others (Ayaz et al., 2009, 2012).”
- Monitoring driver cognitive load using functional near infrared spectroscopy in partially autonomous cars (2016, background): “Pupil dilation, gaze directions and blink rate [12, 13] provide vital information into operator workload and have been used with high levels of success in detecting difficulty levels of in vehicle and driving tasks.”
- Haemodynamic correlates of bilateral 6 Hz transcranial alternating current stimulation during working memory enhancement revealed by fNIRS (2026, unknown): “The testing environment was kept quiet and well lit to ensure data quality (Ayaz et al., 2012).”