Cognitive Vigilance Enhancement Using Audio Stimulation of Pure Tone at 250 Hz

In this paper, we propose a novel vigilance enhancement method based on audio stimulation of pure tone at 250 Hz. We induced two different levels of vigilance state; vigilance decrement (VD) and vigilance enhancement (VE). The VD state was induced by performing a modified version of the Stroop Color-Word Task (SCWT) for approximately 45 minutes. Likewise, the VE state was induced by incorporating audio stimulation of 250 Hz into the SCWT for 45 minutes. We assessed the levels of vigilance on 20 healthy subjects by utilizing Electroencephalogram (EEG) signals and machine learning. The EEG signals were analyzed using four types of entropies; Approximate Entropy (AE), Sample Entropy (SE), Fuzzy Entropy (FE), and Differential Entropy (DE). We then quantified vigilance levels using statistical analysis and support vector machines (SVM) classifier. We found that the proposed VE method has significantly reduced the reaction time (RT) by 44% and improved the accuracy of target detection by 25%, (p <; 0.001) compared to VD state. Besides, we found that 30 min of audio stimulation has reduced the RT by 32% from the beginning to the end of VE phase of the experiment. The entropy measures show that the temporal profile of the EEG signals has significantly increased with VE. The classification results showed that SVM technique with DE features across all frequency bands can detect VE levels with accuracy varying between (92.10± 02.24)% to (98.32± 01.14)%, sensitivity of (92.50± 02.33)% to (98.66± 01.00)%, and specificity of (91.70± 02.32)% to (97.99± 01.05)%. Results also showed that the classification performance using DE has outperformed the other entropy measures by an average of +8.07%. Our results demonstrate the effectiveness of the proposed 250 Hz audio stimulation method in improving vigilance level and suggest using it for future cognitive enhancement studies

Neuroprotective Role of Hypothermia in Acute Spinal Cord Injury

Even nowadays, the question of whether hypothermia can genuinely be considered therapeutic care for patients with traumatic spinal cord injury (SCI) remains unanswered. Although the mechanisms of hypothermia action are yet to be fully explored, early hypothermia for patients suffering from acute SCI has already been implemented in clinical settings. This article discusses measures for inducing various forms of hypothermia and summarizes several hypotheses describing the likelihood of hypothermia mechanisms of action. We present our objective neuro-electrophysiological results and demonstrate that early hypothermia manifests neuroprotective effects mainly during the first- and second-month post-SCI, depending on the severity of the injury, time of intervening, duration, degree, and modality of inducing hypothermia. Nevertheless, eventually, its beneficial effects gradually but consistently diminish. In addition, we report potential complications and side effects for the administration of general hypothermia with a unique referment to the local hypothermia. We also provide evidence that instead of considering early hypothermia post-SCI a therapeutic approach, it is more a neuroprotective strategy in acute and sub-acute phases of SCI that mostly delay, but not entirely avoid, the natural history of the pathophysiological events. Indeed, the most crucial rationale for inducing early hypothermia is to halt these devastating inflammatory and apoptotic events as early and as much as possible. This, in turn, creates a larger time-window of opportunity for physicians to formulate and administer a well-designed personalized treatment for patients suffering from acute traumatic SCI

TCAD Simulation and Analysis of Selective Buried Oxide MOSFET Dynamic Power

Low power consumption has become one of the major requirements for most microelectronic devices and systems. Increasing power dissipation may lead to decreasing system efficiency and lifetime. The BULK metal oxide semiconductor field-effect transistor (MOSFET) has relatively high power dissipation and low frequency response due to its internal capacitances. Although the silicon-on-insulator (SOI) MOSFET was introduced to resolve these limitations, other challenges were introduced including the kink effect in the current-voltage characteristics. The selective buried oxide (SELBOX) MOSFET was then suggested to resolve the problem of the kink effect. The authors have previously investigated and reported the characteristics of the SELBOX structure in terms of kink effect, frequency, thermal and static power characteristics. In this paper, we continue our investigation by presenting the dynamic power characteristics of the SELBOX structure and compare that with the BULK and SOI structures. The simulated fabrication of the three devices was conducted using Silvaco TCAD tools in 90 nm complementary metal oxide semiconductor (CMOS) technology. Simulation results show that the average dynamic power dissipation of the CMOS BULK, SOI and SELBOX are compatible at high frequencies with approximately 54.5 &micro;W. At low frequencies, the SOI and SELBOX showed comparable dynamic power dissipation but with lower values than the BULK structure. The difference in power dissipation between the SELBOX and BULK is in the order of nano watts. This power difference becomes significant at the chip level. For instance, at 1 MHz, SOI and SELBOX exhibit an average dynamic power consumption of 0.0026 &micro;W less than that of the BULK structure. This value cannot be ignored when a chip operates using thousands or millions of SOI or SELBOX MOSFETs

Vigilance Decrement and Enhancement Techniques: A Review

This paper presents the first comprehensive review on vigilance enhancement using both conventional and unconventional means, and further discusses the resulting contradictory findings. It highlights the key differences observed between the research findings and argues that variations of the experimental protocol could be a significant contributing factor towards such contradictory results. Furthermore, the paper reveals the effectiveness of unconventional means of enhancement in significant reduction of vigilance decrement compared to conventional means. Meanwhile, a discussion on the challenges of enhancement techniques is presented, with several suggested recommendations and alternative strategies to maintain an adequate level of vigilance for the task at hand. Additionally, this review provides evidence in support of the use of unconventional means of enhancement on vigilance studies, regardless of their practical challenges

Improved Cognitive Vigilance Assessment after Artifact Reduction with Wavelet Independent Component Analysis

Vigilance level assessment is of prime importance to avoid life-threatening human error. Critical working environments such as air traffic control, driving, or military surveillance require the operator to be alert the whole time. The electroencephalogram (EEG) is a very common modality that can be used in assessing vigilance. Unfortunately, EEG signals are prone to artifacts due to eye movement, muscle contraction, and electrical noise. Mitigating these artifacts is important for an accurate vigilance level assessment. Independent Component Analysis (ICA) is an effective method and has been extensively used in the suppression of EEG artifacts. However, in vigilance assessment applications, it was found to suffer from leakage of the cerebral activity into artifacts. In this work, we show that the wavelet ICA (wICA) method provides an alternative for artifact reduction, leading to improved vigilance level assessment results. We conducted an experiment in nine human subjects to induce two vigilance states, alert and vigilance decrement, while performing a Stroop Color&ndash;Word Test for approximately 45 min. We then compared the performance of the ICA and wICA preprocessing methods using five classifiers. Our classification results showed that in terms of features extraction, the wICA method outperformed the existing ICA method. In the delta, theta, and alpha bands, we obtained a mean classification accuracy of 84.66% using the ICA method, whereas the mean accuracy using the wICA methodwas 96.9%. However, no significant improvement was observed in the beta band. In addition, we compared the topographical map to show the changes in power spectral density across the brain regions for the two vigilance states. The proposed method showed that the frontal and central regions were most sensitive to vigilance decrement. However, in this application, the proposed wICA shows a marginal improvement compared to the Fast-ICA

Brain Connectivity Analysis Under Semantic Vigilance and Enhanced Mental States

In this paper, we present a method to quantify the coupling between brain regions under vigilance and enhanced mental states by utilizing partial directed coherence (PDC) and graph theory analysis (GTA). The vigilance state is induced using a modified version of stroop color-word task (SCWT) while the enhancement state is based on audio stimulation with a pure tone of 250 Hz. The audio stimulation was presented to the right and left ears simultaneously for one-hour while participants perform the SCWT. The quantification of mental states was performed by means of statistical analysis of indexes based on GTA, behavioral responses of time-on-task (TOT), and Brunel Mood Scale (BRMUS). The results show that PDC is very sensitive to vigilance decrement and shows that the brain connectivity network is significantly reduced with increasing TOT, p &lt; 0.05. Meanwhile, during the enhanced state, the connectivity network maintains high connectivity as time passes and shows significant improvements compared to vigilance state. The audio stimulation enhances the connectivity network over the frontal and parietal regions and the right hemisphere. The increase in the connectivity network correlates with individual differences in the magnitude of the vigilance enhancement assessed by response time to stimuli. Our results provide evidence for enhancement of cognitive processing efficiency with audio stimulation. The BRMUS was used to evaluate the emotional states of vigilance task before and after using the audio stimulation. BRMUS factors, such as fatigue, depression, and anger, significantly decrease in the enhancement group compared to vigilance group. On the other hand, happy and calmness factors increased with audio stimulation, p &lt; 0.05.In this paper, we present a method to quantify the coupling between brain regions under vigilance and enhanced mental states by utilizing partial directed coherence (PDC) and graph theory analysis (GTA). The vigilance state is induced using a modified version of stroop color-word task (SCWT) while the enhancement state is based on audio stimulation with a pure tone of 250 Hz. The audio stimulation was presented to the right and left ears simultaneously for one-hour while participants perform the SCWT. The quantification of mental states was performed by means of statistical analysis of indexes based on GTA, behavioral responses of time-on-task (TOT), and Brunel Mood Scale (BRMUS). The results show that PDC is very sensitive to vigilance decrement and shows that the brain connectivity network is significantly reduced with increasing TOT, p &lt; 0.05. Meanwhile, during the enhanced state, the connectivity network maintains high connectivity as time passes and shows significant improvements compared to vigilance state. The audio stimulation enhances the connectivity network over the frontal and parietal regions and the right hemisphere. The increase in the connectivity network correlates with individual differences in the magnitude of the vigilance enhancement assessed by response time to stimuli. Our results provide evidence for enhancement of cognitive processing efficiency with audio stimulation. The BRMUS was used to evaluate the emotional states of vigilance task before and after using the audio stimulation. BRMUS factors, such as fatigue, depression, and anger, significantly decrease in the enhancement group compared to vigilance group. On the other hand, happy and calmness factors increased with audio stimulation, p &lt; 0.05

Assessment of spinal cord injury via sparse modeling of somatosensory evoked potential signals

Abstract The morphological differences between somatosensory evoked potential (SEP) signals from a normal spinal pathway and spinal pathway affected by spinal cord injury (SCI) provide an indication of the degree of SCI. A sparse representation of the fit between these signals is proposed in this paper as an SCI assessment method. The proposed method is tested on actual SEP signals collected from rodents that have been subjected to spinal transection. Results indicate that the proposed method provides a robust measure of the different degrees of SCI resulting from transection of the spinal cord

Novel modeling of somatosensory evoked potentials for the assessment of spinal cord injury

Abstract Objective: Previous work has shown that differences in the somatosensory evoked potential (SEP) signals between a normal spinal pathway and spinal pathway affected by spinal cord injury (SCI) provide a means to study the degree of injury. This paper proposes a novel quantitative SCI assessment method using time-domain SEP signals. Methods: A pruned and unstructured fit between SEP signals from a normal spinal pathway and a spinal pathway affected by SCI is developed using methods inspired by recent results in sparse reconstruction theory. The coefficients from the resulting fit are used to develop a quantitative assessment of SCI that is tested on actual SEP signals collected from rodents that have been subjected to partial and complete spinal cord transection. Results: The proposed method provides a rich parametric measure that integrates SEP amplitude, time latency, and morphology, while exhibiting a high degree of correlation with existing subjective and quantitative SCI assessment methods. Conclusion: The proposed SCI encapsulates a model of the injury to quantify SCI. Significance: The proposed SCI quantification method may be used to complement existing SCI assessment methods