Functional Near-Infrared Spectroscopy Adaptive Cognitive Training System (FACTS) for Cognitive Underload and Overload Prevention: A Feasibility Study

Ung, Wei Chun; Mériaudeau, Fabrice; Kiguchi, Masashi; Tang, Tong Boon

doi:10.1109/access.2020.3024867

Cited by 3 publications

(5 citation statements)

References 58 publications

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“…1) Behavioral Performance: Based on the findings of the closed-loop brain training [21], every subject managed to achieve and solve a minimum of third difficulty level for the mental arithmetic task. Due to the difference in attempted difficulty levels across subjects, it was not possible to one-by-one compare the difficulty level.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, the peak of task-evoked HR is taken into consideration as the recovery duration scales proportionally with it, and a novel vector phase diagram is specifically designed to detect (with a set of design criteria) if the task-evoked HR had returned to baseline. The proposed method was assessed with a block-design fNIRS dataset containing hemodynamic measurements over the prefrontal cortex (PFC) of 24 human subjects [21]. At both interand intra-subject analyses, we hypothesize that the estimation of mental workload improves with an optimal baseline detected with our novel vector phase method.…”

Section: Although This Technique Has Demonstrated a Significantmentioning

confidence: 99%

“…3. A 3 × 11 probe layout with a standard source-detector distance of 30 mm was used to cover the entire PFC in [21]. In accordance to the international 10-20 system [24], sources 23 and 28 were constantly placed at the positions T4 and T3, respectively.…”

Section: T N Hbo and T Nmentioning

confidence: 99%

“…In accordance to the international 10-20 system [24], sources 23 and 28 were constantly placed at the positions T4 and T3, respectively. The authors [21] have permitted the use of the figure.…”

Section: T N Hbo and T Nmentioning

confidence: 99%

“…The proposed method was applied on the lab-based fNIRS dataset published in [21]. Briefly, 10-Hz sampling rate fNIRS data were collected from a total of 38 right-handed healthy university students performing mental arithmetic task using a closed-loop brain training system, specifically to optimize the mental workload at WM-related brain region.…”

Section: B Fnirs Datasetmentioning

confidence: 99%

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Optimizing Mental Workload Estimation by Detecting Baseline State Using Vector Phase Analysis Approach

Lim

Ung

Chan

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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Improper baseline return from the previous task-evoked hemodynamic response (HR) can contribute to a large variation in the subsequent HR, affecting the estimation of mental workload in brain-computer interface systems. In this study, we proposed a method using vector phase analysis to detect the baseline state as being optimal or suboptimal. We hypothesize that selecting neuronal-related HR as observed in the optimal-baseline blocks can lead to an improvement in estimating mental workload. Oxygenated and deoxygenated hemoglobin concentration changes were integrated as parts of the vector phase. The proposed method was applied to a block-design functional near-infrared spectroscopy dataset (total blocks = 1384), measured on 24 subjects performing multiple difficulty levels of mental arithmetic task. Significant differences in hemodynamic signal change were observed between the optimal-and suboptimal-baseline blocks detected using the proposed method. This supports the effectiveness of the proposed method in detecting baseline state for better estimation of mental workload. The results further highlight the need of customized recovery duration. In short, the proposed method offers a practical approach to detect task-evoked signals, without the need of extra probes.

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Section: Discussionmentioning

confidence: 99%

Section: Although This Technique Has Demonstrated a Significantmentioning

confidence: 99%

Section: T N Hbo and T Nmentioning

confidence: 99%

Section: T N Hbo and T Nmentioning

confidence: 99%

Section: B Fnirs Datasetmentioning

confidence: 99%

See 3 more Smart Citations

Optimizing Mental Workload Estimation by Detecting Baseline State Using Vector Phase Analysis Approach

Lim

Ung

Chan

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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Real-time recognition of different imagined actions on the same side of a single limb based on the fNIRS correlation coefficient

Liu

et al. 2022

Biomedical Engineering / Biomedizinische Technik

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Functional near-infrared spectroscopy (fNIRS) is a type of functional brain imaging. Brain-computer interfaces (BCIs) based on fNIRS have recently been implemented. Most existing fNIRS-BCI studies have involved off-line analyses, but few studies used online performance testing. Furthermore, existing online fNIRS-BCI experimental paradigms have not yet carried out studies using different imagined movements of the same side of a single limb. In the present study, a real-time fNIRS-BCI system was constructed to identify two imagined movements of the same side of a single limb (right forearm and right hand). Ten healthy subjects were recruited and fNIRS signal was collected and real-time analyzed with two imagined movements (leftward movement involving the right forearm and right-hand clenching). In addition to the mean and slope features of fNIRS signals, the correlation coefficient between fNIRS signals induced by different imagined actions was extracted. A support vector machine (SVM) was used to classify the imagined actions. The average accuracy of real-time classification of the two imagined movements was 72.25 ± 0.004%. The findings suggest that different imagined movements on the same side of a single limb can be recognized real-time based on fNIRS, which may help to further guide the practical application of online fNIRS-BCIs.

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Neural mechanisms underlying state mental fatigue: a systematic review and activation likelihood estimation meta-analysis

Salihu

Jaberzadeh

2022

Reviews in the Neurosciences

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Sustained performance of cognitive tasks could lead to the development of state mental fatigue characterized by subjective sensation of mental weariness and decrease in cognitive performance. In addition to the occupational hazards associated with mental fatigue, it can also affect physical performance reducing endurance, balance, and sport-specific technical skills. Similarly, mental fatigue is a common symptom in certain chronic health conditions such as multiple sclerosis affecting quality of life of the patients. Despite its widely acknowledged negative impact, the neural mechanisms underlining this phenomenon are still not fully understood. We conducted a systematic review and activation likelihood estimation (ALE) meta-analysis of functional neuroimaging studies investigating the effect of mental fatigue due to time-on-task (TOT) on brain activity to elucidate the possible underlying mechanisms. Studies were included if they examined change in brain activity induced by experimental mental fatigue (TOT effect) or investigated the relationship between brain activity and subjective mental fatigue due to TOT. A total of 33 studies met the review’s inclusion criteria, 13 of which were included in meta-analyses. Results of the meta-analyses revealed a decrease in activity with TOT in brain areas that constitute the cognitive control network. Additionally, an increased activity with TOT, as well as negative relationship with subjective mental fatigue was found in parts of the default mode network of the brain. The changes in cognitive control and the default mode networks of the brain due to state mental fatigue observed in this study were discussed in relation to the existing theories of mental fatigue.

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Functional Near-Infrared Spectroscopy Adaptive Cognitive Training System (FACTS) for Cognitive Underload and Overload Prevention: A Feasibility Study

Cited by 3 publications

References 58 publications

Optimizing Mental Workload Estimation by Detecting Baseline State Using Vector Phase Analysis Approach

Optimizing Mental Workload Estimation by Detecting Baseline State Using Vector Phase Analysis Approach

Real-time recognition of different imagined actions on the same side of a single limb based on the fNIRS correlation coefficient

Neural mechanisms underlying state mental fatigue: a systematic review and activation likelihood estimation meta-analysis

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