scholarly journals Benchmarking cEEGrid and Solid Gel-Based Electrodes to Classify Inattentional Deafness in a Flight Simulator

2022 ◽  
Vol 2 ◽  
Author(s):  
Bertille Somon ◽  
Yasmina Giebeler ◽  
Ludovic Darmet ◽  
Frédéric Dehais
Keyword(s):  
Brain Activity ◽  
Real Life ◽  
Flight Simulator ◽  
Complex Environments ◽  
Time Frequency ◽  
Cognitive Failures ◽  
Frequency Domains ◽  
Life Tasks ◽  
Small Pool ◽  
The Time Domain

Transfer from experiments in the laboratory to real-life tasks is challenging due notably to the inability to reproduce the complexity of multitasking dynamic everyday life situations in a standardized lab condition and to the bulkiness and invasiveness of recording systems preventing participants from moving freely and disturbing the environment. In this study, we used a motion flight simulator to induce inattentional deafness to auditory alarms, a cognitive difficulty arising in complex environments. In addition, we assessed the possibility of two low-density EEG systems a solid gel-based electrode Enobio (Neuroelectrics, Barcelona, Spain) and a gel-based cEEGrid (TMSi, Oldenzaal, Netherlands) to record and classify brain activity associated with inattentional deafness (misses vs. hits to odd sounds) with a small pool of expert participants. In addition to inducing inattentional deafness (missing auditory alarms) at much higher rates than with usual lab tasks (34.7% compared to the usual 5%), we observed typical inattentional deafness-related activity in the time domain but also in the frequency and time-frequency domains with both systems. Finally, a classifier based on Riemannian Geometry principles allowed us to obtain more than 70% of single-trial classification accuracy for both mobile EEG, and up to 71.5% for the cEEGrid (TMSi, Oldenzaal, Netherlands). These results open promising avenues toward detecting cognitive failures in real-life situations, such as real flight.

scholarly journals Benchmarking cEEGrid and solid gel-based electrodes to classify inattentional deafness in a flight simulator

2021 ◽  
Author(s):  
Bertille Somon ◽  
Yasmina Giebeler ◽  
Ludovic Darmet ◽  
Frédéric Dehais
Keyword(s):  
Brain Activity ◽  
Real Life ◽  
Flight Simulator ◽  
Complex Environments ◽  
Time Frequency ◽  
Cognitive Failures ◽  
Frequency Domains ◽  
Life Tasks ◽  
Small Pool ◽  
The Time Domain

Transfer from experiments in laboratory to real-life tasks is challenging due notably to the inability to reproduce the complexity of multitasking dynamic everyday life situations in a standardized lab condition, and to the bulkiness and invasiveness of recording systems preventing participants from moving freely and disturbing the environment. Here we used a motion flight simulator to induce inattentional deafness to auditory alarms, a cognitive difficulty arising in complex environments. In addition, we assessed the possibility of two low-density EEG systems (a solid gel-based electrode Enobio (Neuroelectrics, Barcelona, Spain) and a gel-based cEEGrid (TMSi, Oldenzaal, Netherlands)) to record and classify brain activity associated with inattentional deafness (misses vs. hits to odd sounds) with a small pool of expert participants. In addition to inducing inattentional deafness (missing auditory alarms) at much higher rates than with usual lab tasks (34.7% compared to the usual 5%), we observed typical inattentional deafness-related activity in the time domain, but also in the frequency and time-frequency domains with both systems. Finally, a classifier based on Riemannian Geometry principles allowed us to obtain more than 70% of single-trial classification accuracy for both mobile EEG, and up to 72.9% for the cEEGrid (TMSi, Oldenzaal, Netherlands). These results open promising avenue towards detecting cognitive failures in real-life situations, such as real flight.

scholarly journals Spillover effects from news to travel and leisure stocks during the COVID-19 pandemic: Evidence from the time and frequency domains

2021 ◽  
pp. 135481662110584
Author(s):  
Ying Wang ◽  
Hongwei Zhang ◽  
Wang Gao ◽  
Cai Yang
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Spillover Effects ◽  
Short Term ◽  
Time Frequency ◽  
Frequency Domains ◽  
Media Hype ◽  
The Time Domain ◽  
The Impact

The impact of the COVID-19 pandemic on tourism has received general attention in the literature, while the role of news during the pandemic has been ignored. Using a time-frequency connectedness approach, this paper focuses on the spillover effects of COVID-19-related news on the return and volatility of four regional travel and leisure (T&L) stocks. The results in the time domain reveal significant spillovers from news to T&L stocks. Specifically, in the return system, T&L stocks are mainly affected by media hype, while in the volatility system, they are mainly affected by panic sentiment. This paper also finds two risk contagion paths. The contagion index and Global T&L stock are the sources of these paths. The results in the frequency domain indicate that the shocks in the T&L industry are mainly driven by short-term fluctuations. The spillovers from news to T&L stocks and among these T&L stocks are stronger within 1 month.

Control of a Wheeled Inverted Pendulum: A Nonlinear Time-Frequency Approach

2016 ◽  
Author(s):  
Tanja Baumann ◽  
Steve Suh
Keyword(s):  
Inverted Pendulum ◽  
Discrete Wavelet ◽  
Least Mean Square ◽  
Time Frequency ◽  
Feed Forward Control ◽  
Online Identification ◽  
Wheeled Inverted Pendulum ◽  
Frequency Domains ◽  
Control Concept ◽  
The Time Domain

The wheeled inverted pendulum shown in Fig. 1 is a typical nonlinear system that is both nonholonomic and complex in dynamics. In this paper a novel control concept is applied to stabilize a wheeled inverted pendulum. The suggested controller requires no mathematical simplification or linearization of the system. Online identification and feed-forward control are realized by an adapted filtered-x least mean square algorithm (FXLMS). Using discrete wavelet transform (DWT), control can be exerted in both the time and frequency domains simultaneously. The results show that the proposed controller is robust even when the system is perturbed. The system can also be partially stabilized at positions out of the upper equilibrium. In this case the time domain error is small though the system stays broadband in the frequency domain.

scholarly journals Application of Correlation Analysis for Assessment of Infrasound Signals Emission by Wind Turbines

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6891
Author(s):  
Tomasz Boczar ◽  
Dariusz Zmarzły ◽  
Michał Kozioł ◽  
Daria Wotzka
Keyword(s):  
Correlation Analysis ◽  
Frequency Domain ◽  
Coherence Function ◽  
Wind Farms ◽  
Wavelet Coherence ◽  
Technical Parameters ◽  
Time Frequency ◽  
Frequency Domains ◽  
Frequency Transformations ◽  
The Time Domain

The study reported in this paper is concerned with areas related to developing methods of measuring, processing and analyzing infrasound noise caused by operation of wind farms. The paper contains the results of the correlation analysis of infrasound signals generated by a wind turbine with a rated capacity of 2 MW recorded by three independent measurement setups comprising identical components and characterized by the same technical parameters. The measurements of infrasound signals utilized a dedicated measurement system called INFRA, which was developed and built by KFB ACOUSTICS Sp. z o.o. In particular, the scope of the paper includes the results of correlation analysis in the time domain, which was carried out using the autocovariance function separately for each of the three measuring setups. Moreover, the courses of the cross-correlation function were calculated separately for each of the potential combinations of infrasound range recorded by the three measuring setups. In the second stage, a correlation analysis of the recorded infrasound signals in the frequency domain was performed, using the coherence function. In the next step, infrasound signals recorded in three setups were subjected to time-frequency transformations. In this part, the waveforms of the scalograms were determined by means of continuous wavelet transform. Wavelet coherence waveforms were calculated in order to determine the level of the correlation of the obtained dependencies in the time-frequency domain. The summary contains the results derived from using correlation analysis methods in the time, frequency and time-frequency domains.

scholarly journals Time Latency-Centric Signal Processing: A Perspective of Smart Manufacturing

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7336
Author(s):  
Sharifu Ura ◽  
Angkush Kumar Ghosh
Keyword(s):  
Signal Processing ◽  
Embedded Systems ◽  
Machine Tools ◽  
Real Life ◽  
Smart Manufacturing ◽  
Time Frequency ◽  
Frequency Domains ◽  
Sensor Signals ◽  
Time Latency ◽  
Time And Frequency Domains

Smart manufacturing employs embedded systems such as CNC machine tools, programable logic controllers, automated guided vehicles, robots, digital measuring instruments, cyber-physical systems, and digital twins. These systems collectively perform high-level cognitive tasks (monitoring, understanding, deciding, and adapting) by making sense of sensor signals. When sensor signals are exchanged through the abovementioned embedded systems, a phenomenon called time latency or delay occurs. As a result, the signal at its origin (e.g., machine tools) and signal received at the receiver end (e.g., digital twin) differ. The time and frequency domain-based conventional signal processing cannot adequately address the delay-centric issues. Instead, these issues can be addressed by the delay domain, as suggested in the literature. Based on this consideration, this study first processes arbitrary signals in time, frequency, and delay domains and elucidates the significance of delay domain over time and frequency domains. Afterward, real-life signals collected while machining different materials are analyzed using frequency and delay domains to reconfirm its (the delay domain’s) significance in real-life settings. In both cases, it is found that the delay domain is more informative and reliable than the time and frequency domains when the delay is unavoidable. Moreover, the delay domain can act as a signature of a machining situation, distinguishing it (the situation) from others. Therefore, computational arrangements enabling delay domain-based signal processing must be enacted to effectively functionalize the smart manufacturing-centric embedded systems.

Simultaneous Time-Frequency Synchronization of Non-Autonomous Chaotic Systems

2013 ◽  
Author(s):  
Meng-Kun Liu ◽  
C. Steve Suh
Keyword(s):  
Chaotic System ◽  
Initial Conditions ◽  
Frequency Control ◽  
Frequency Synchronization ◽  
Time Frequency ◽  
System A ◽  
Frequency Domains ◽  
Control Concept ◽  
On Line ◽  
The Time Domain

A novel chaos control concept is presented for the synchronization of a non-autonomous chaotic circuit system in the time and frequency domains concurrently. The controller effectively eliminates the differences between two chaotic circuits in the time domain and at the same time restores the characteristics of the driving response in the frequency domain. The simultaneous time-frequency control is achieved through manipulating wavelet coefficients, thus not limited by the increasing bandwidth of the chaotic system — a fundamental restraint that deprives contemporary controller designs of validity and effectiveness. The feedforward feature of the control concept prevents errors from re-entering the control loop and inadvertently perturbing the sensitive chaotic system. Because neither closed-form nor linearization is required, the innate, genuine features of the chaotic response are faithfully retained. The on-line identification feature allows the response system to start at arbitrary initial conditions and to be driven by the sinusoidal forcing term of different amplitudes and phases requiring no knowledge of the system parameters.

scholarly journals Novel Burst Suppression Segmentation in the Joint Time-Frequency Domain for EEG in Treatment of Status Epilepticus

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Jaeyun Lee ◽  
Woo-Jin Song ◽  
Hyang Woon Lee ◽  
Hyun-Chool Shin
Keyword(s):  
Status Epilepticus ◽  
Frequency Domain ◽  
Time Domain ◽  
Suppression Ratio ◽  
Likelihood Estimation ◽  
Burst Suppression ◽  
Time Frequency ◽  
Frequency Domains ◽  
Conventional Methods ◽  
The Time Domain

We developed a method to distinguish bursts and suppressions for EEG burst suppression from the treatments of status epilepticus, employing the joint time-frequency domain. We obtained the feature used in the proposed method from the joint use of the time and frequency domains, and we estimated the decision as to whether the measured EEG was a burst segment or suppression segment by the maximum likelihood estimation. We evaluated the performance of the proposed method in terms of its accordance with the visual scores and estimation of the burst suppression ratio. The accuracy was higher than the sole use of the time or frequency domains, as well as conventional methods conducted in the time domain. In addition, probabilistic modeling provided a more simplified optimization than conventional methods. Burst suppression quantification necessitated precise burst suppression segmentation with an easy optimization; therefore, the excellent discrimination and the easy optimization of burst suppression by the proposed method appear to be beneficial.

Separating Multiple Moving Sources by Microphone Array Signals for Wayside Acoustic Fault Diagnosis

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Wei Xiong ◽  
Qingbo He ◽  
Zhike Peng
Keyword(s):  
Fault Diagnosis ◽  
Time Domain ◽  
Feature Matching ◽  
Matching Pursuit ◽  
Microphone Array ◽  
Time Frequency ◽  
Moving Sources ◽  
The Time Domain ◽  
Envelope Spectrum ◽  
Threshold Setting

Wayside acoustic defective bearing detector (ADBD) system is a potential technique in ensuring the safety of traveling vehicles. However, Doppler distortion and multiple moving sources aliasing in the acquired acoustic signals decrease the accuracy of defective bearing fault diagnosis. Currently, the method of constructing time-frequency (TF) masks for source separation was limited by an empirical threshold setting. To overcome this limitation, this study proposed a dynamic Doppler multisource separation model and constructed a time domain-separating matrix (TDSM) to realize multiple moving sources separation in the time domain. The TDSM was designed with two steps of (1) constructing separating curves and time domain remapping matrix (TDRM) and (2) remapping each element of separating curves to its corresponding time according to the TDRM. Both TDSM and TDRM were driven by geometrical and motion parameters, which would be estimated by Doppler feature matching pursuit (DFMP) algorithm. After gaining the source components from the observed signals, correlation operation was carried out to estimate source signals. Moreover, fault diagnosis could be carried out by envelope spectrum analysis. Compared with the method of constructing TF masks, the proposed strategy could avoid setting thresholds empirically. Finally, the effectiveness of the proposed technique was validated by simulation and experimental cases. Results indicated the potential of this method for improving the performance of the ADBD system.

scholarly journals Neural alignment predicts learning outcomes in students taking an introduction to computer science course

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meir Meshulam ◽  
Liat Hasenfratz ◽  
Hanna Hillman ◽  
Yun-Fei Liu ◽  
Mai Nguyen ◽  
...  
Keyword(s):  
Computer Science ◽  
Learning Outcomes ◽  
Brain Activity ◽  
Activity Patterns ◽  
Real Life ◽  
Final Exam ◽  
Neural Representations ◽  
Real Life Setting ◽  
The Right ◽  
Mri Study

AbstractDespite major advances in measuring human brain activity during and after educational experiences, it is unclear how learners internalize new content, especially in real-life and online settings. In this work, we introduce a neural approach to predicting and assessing learning outcomes in a real-life setting. Our approach hinges on the idea that successful learning involves forming the right set of neural representations, which are captured in canonical activity patterns shared across individuals. Specifically, we hypothesized that learning is mirrored in neural alignment: the degree to which an individual learner’s neural representations match those of experts, as well as those of other learners. We tested this hypothesis in a longitudinal functional MRI study that regularly scanned college students enrolled in an introduction to computer science course. We additionally scanned graduate student experts in computer science. We show that alignment among students successfully predicts overall performance in a final exam. Furthermore, within individual students, we find better learning outcomes for concepts that evoke better alignment with experts and with other students, revealing neural patterns associated with specific learned concepts in individuals.

scholarly journals What affordances do open-ended real-life tasks offer for sharing student agency in collaborative problem-solving?

2021 ◽  
Author(s):  
Juuso Henrik Nieminen ◽  
Man Ching Esther Chan ◽  
David Clarke
Keyword(s):  
Problem Solving ◽  
Video Recording ◽  
Real Life ◽  
Collaborative Problem Solving ◽  
Student Agency ◽  
Student Groups ◽  
Collaborative Problem ◽  
Mathematical Arguments ◽  
Life Tasks ◽  
Collaborative Construction

AbstractThe important role of student agency in collaborative problem-solving has been acknowledged in previous mathematics education research. However, what remains unknown are the processes of agency in open-ended tasks that draw on real-life contexts and demand argumentation beyond “mathematical”. In this study, we analyse a video recording of two student groups (each consisting of four students) taking part in collaborative problem-solving. We draw on the framework for collaborative construction of mathematical arguments and its interplay with student agency by Mueller et al. (2012). This original framework is supplemented by (i) testing and revising it in the context of open-ended real-life tasks, with (ii) student groups rather than pairs working on the tasks, and by (iii) offering a strengthened methodological pathway for analysing student agency in such a context. Based on our findings, we suggest that the framework suits this new context with some extensions. First, we note that differences in student agency were not only identified in terms of the discourse students drew on, but in how students were able to shift between various discourses, such as between “mathematical” and “non-mathematical” discourses. We identify a novel discourse reflecting student agency, invalidation discourse, which refers to denying other students’ agency by framing their contribution as invalid. Finally, we discuss the need to reframe “mathematical” arguments—and indeed student agency—while the task at hand is open-ended and concerns real-life contexts.

Sign in / Sign up

Export Citation Format

Share Document