Brain activity measured with fNIRS for the prediction of cognitive workload

Unni, Anirudh; Ihme, Klas; Surm, Henrik; Weber, Lars; Lüdtke, Andreas; Nicklas, Daniela; Jipp, Meike; Rieger, Jochem W.

doi:10.1109/coginfocom.2015.7390617

Cited by 21 publications

(21 citation statements)

References 24 publications

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“…Contrary to our hypothesis and despite previous studies demonstrating that hemodynamic responses can be used to reliably quantify cognitive state and load levels in the bilateral PFC (Basso Moro et al, 2013; Fishburn et al, 2014; Unni et al, 2015; Bonetti et al, 2019), the present study did not find significant differences among optodes when parsed into different regions. Although the lack of regional differences is important, it is worthwhile to note that fNIRS’ spatial resolution is limited by the optical source-detector distance, which is normally 2–3 cm, despite the technology having high temporal resolution (Tak et al, 2016).…”

Section: Discussioncontrasting

confidence: 99%

Does Movement Matter? Prefrontal Cortex Activity During 2D vs. 3D Performance of the Tower of Hanoi Puzzle

Milla

Bakhshipour

Bodt

et al. 2019

Front. Hum. Neurosci.

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In the current study, we used functional near-infrared spectroscopy (fNIRS) to compare prefrontal cortex (PFC) activity in adults as they performed two conditions of the Tower of Hanoi (ToH) disk-transfer task that have equivalent executive function (EF) but different motor requirements. This study explored cognitive workload, here defined as the cognitive effort utilized while problem-solving by performance output. The first condition included a two-dimensional (2D) computerized ToH where participants completed trials using a computer mouse. In contrast, our second condition used a traditional, three-dimensional (3D) ToH that must be manually manipulated. Our aim was to better understand the role of the PFC in these two conditions to detect if PFC activity increases as a function of motor planning. Twenty right-handed, neurotypical adults (10M/10F, = 24.6, SD ± 2.8 years old) participated in two blocks (one per condition) of three 1-min trials where they were asked to solve as many puzzles as possible. These data were analyzed using a mixed effects ANOVA with participants nested within blocks for 2D vs. 3D conditions, presentation order (leading block), individual participants, and regions and additional follow-up statistics. Results showed that changes in oxygenated hemoglobin, ΔHbO, were significantly higher for 3D compared to 2D condition ( p = 0.0211). Presentation order and condition interacted significantly ( p = 0.0015). Notably, a strong correlation between performance and ΔHbO existed between blocks 1 and 2 ( r = −0.69, r 2 = 0.473, p < 0.01) when the 3D condition was initially performed, in contrast to the 2D condition where no significant correlation was seen. Findings also showed a significant decrease in ΔHbO between the first and second block ( p = 0.0015) while performance increased significantly for both 3D and 2D conditions ( p < 0.005). We plan to use this information in the future to narrow the potential points of impairment on the perception-cognition-action continuum in certain developmental disabilities.

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Section: Discussioncontrasting

confidence: 99%

Does Movement Matter? Prefrontal Cortex Activity During 2D vs. 3D Performance of the Tower of Hanoi Puzzle

Milla

Bakhshipour

Bodt

et al. 2019

Front. Hum. Neurosci.

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“…A recent neuroergonomic study of Carrieri and colleagues [ 226 ] used FNIRS measures to objectively evaluate cortical hemodynamic changes occurring in VR environments. There is emerging evidence that FNIRS provides a suitable measure of mental workload [ 253 , 254 ]. The aim of the study of Carrieri et al was to investigate cortex activity in subjects while performing a demanding VR hand-controlled task.…”

Section: Discussionmentioning

confidence: 99%

Review of Three-Dimensional Human-Computer Interaction with Focus on the Leap Motion Controller

Bachmann

Weichert

Rinkenauer

2018

Sensors

118

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Modern hardware and software development has led to an evolution of user interfaces from command-line to natural user interfaces for virtual immersive environments. Gestures imitating real-world interaction tasks increasingly replace classical two-dimensional interfaces based on Windows/Icons/Menus/Pointers (WIMP) or touch metaphors. Thus, the purpose of this paper is to survey the state-of-the-art Human-Computer Interaction (HCI) techniques with a focus on the special field of three-dimensional interaction. This includes an overview of currently available interaction devices, their applications of usage and underlying methods for gesture design and recognition. Focus is on interfaces based on the Leap Motion Controller (LMC) and corresponding methods of gesture design and recognition. Further, a review of evaluation methods for the proposed natural user interfaces is given.

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“…The majority of studies included here were conducted in a simulator setting, with only nine occurring in an on-road environment ( Harada et al, 2007 ; Shimizu T. et al, 2011 ; Yoshino et al, 2013a , b ; Inoue et al, 2014 ; Orino et al, 2015 , 2017 ; Liu et al, 2017 ; Le et al, 2018 ). However, as described above, the quality of the simulators (e.g., fidelity of the visual environment, amount of visual field encompassed, realism of the simulator to a real automobile) varied between low fidelity desktop computer setups ( Shang et al, 2007 ; Li et al, 2009 , 2018 ; Tomioka et al, 2009 ; Liu, 2014 ; Khan and Hong, 2015 ; Pradhan et al, 2015 ; Unni et al, 2015 ; Ahn et al, 2016 ; Horrey et al, 2017 ; Nguyen et al, 2017 ; Xu G. et al, 2017 ; Xu L. et al, 2017 ; Hidalgo-Munoz et al, 2019 ; Khan et al, 2019 ; Lin et al, 2019 ; Tanveer et al, 2019 ) and more immersive simulated environments ( Nakano et al, 2013 ; Oka et al, 2015 ; FakhrHosseini et al, 2015 ; Foy et al, 2016 ; Foy and Chapman, 2018 ; Huve et al, 2018 , 2019 ; Sturman and Wiggins, 2019 ; Yamamoto et al, 2019 ) including large-scale simulators that comprise a real car mock-up along with a wide field of vision ( Tsunashima and Yanagisawa, 2009 ; Shimizu et al, 2009 ; Orino et al, 2015 ; Nosrati et al, 2016 ; Sibi et al, 2016 , 2017 ; Balters et al, 2017 ; Unni et al, 2017 ; Bruno et al, 2018 ; Chuang et al, 2018 ; Ihme et al, 2018 ; Zhu et al, 2019 ). To minimize motion artifacts, participants in eight studies were specifically instructed to avoid head (and limb) movements ( Li et al, 2009 ; Takahashi et al, 2010 ...…”

Section: Methodological Reviewmentioning

confidence: 99%

A Methodological Review of fNIRS in Driving Research: Relevance to the Future of Autonomous Vehicles

Balters

Baker

Geeseman

et al. 2021

Front. Hum. Neurosci.

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As automobile manufacturers have begun to design, engineer, and test autonomous driving systems of the future, brain imaging with functional near-infrared spectroscopy (fNIRS) can provide unique insights about cognitive processes associated with evolving levels of autonomy implemented in the automobile. Modern fNIRS devices provide a portable, relatively affordable, and robust form of functional neuroimaging that allows researchers to investigate brain function in real-world environments. The trend toward “naturalistic neuroscience” is evident in the growing number of studies that leverage the methodological flexibility of fNIRS, and in doing so, significantly expand the scope of cognitive function that is accessible to observation via functional brain imaging (i.e., from the simulator to on-road scenarios). While more than a decade’s worth of study in this field of fNIRS driving research has led to many interesting findings, the number of studies applying fNIRS during autonomous modes of operation is limited. To support future research that directly addresses this lack in autonomous driving research with fNIRS, we argue that a cogent distillation of the methods used to date will help facilitate and streamline this research of tomorrow. To that end, here we provide a methodological review of the existing fNIRS driving research, with the overarching goal of highlighting the current diversity in methodological approaches. We argue that standardization of these approaches will facilitate greater overlap of methods by researchers from all disciplines, which will, in-turn, allow for meta-analysis of future results. We conclude by providing recommendations for advancing the use of such fNIRS technology in furthering understanding the adoption of safe autonomous vehicle technology.

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Brain activity measured with fNIRS for the prediction of cognitive workload

Cited by 21 publications

References 24 publications

Does Movement Matter? Prefrontal Cortex Activity During 2D vs. 3D Performance of the Tower of Hanoi Puzzle

Does Movement Matter? Prefrontal Cortex Activity During 2D vs. 3D Performance of the Tower of Hanoi Puzzle

Review of Three-Dimensional Human-Computer Interaction with Focus on the Leap Motion Controller

A Methodological Review of fNIRS in Driving Research: Relevance to the Future of Autonomous Vehicles

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