Wireless electroencephalogram monitoring system for deciphering neurological disorders using brain connectivity patterns

Abstract

Over the last two decades, there has been a tremendous increase in research activity on brain connectivity studies and its application in different neurological disorders. Studies have been focused on different connectivity patterns generated and potential biomarkers that could be derived to find the etymology of the disorder. In this review, the focus is on the utilization of wireless electroencephalogram monitoring system for functional connectivity analysis and its capacity for deciphering neurological disorders. The paper reviews different methods adopted to estimate connectivity and the possible convergence of connectivity patterns in four neurological disorders: epilepsy, autism spectrum disorder, Alzheimer and Parkinson's disease. The paper reviews the current status of connectivity research in the aforementioned neurological disorders and its potential in developing a smart e‐health service.

Efficacy of real-time audio biofeedback on physiological strains for simulated tasks with medium and heavy loads

“…Heard et al (2018) surveyed these metrics and stated that EEG, heart rate/heart rate variability, skin temperature, and skin impedance conform "sensitivity" criteria with the ability to reliably detect physical workload levels where at least three published articles show the corresponding evidences. Subjective evaluation tools including Borg Rating of Perceived Exertion (Borg RPE) scale, Borg CR-10 scale, Pain Estimation Charts-The McGill Pain Questionnaire, and Visual Analog (VA) scale have also been adopted to assess physical workloads (Dadashi et al, 2022;DiDomenicoa and Nussbaum, 2008;Mehta and Agnew, 2015). Among these scales, Borg CR-10 scale is sensitive to physical demand changes (DiDomenicoa and Nussbaum, 2008;Shariat et al, 2018;Zamunér et al, 2011).…”

“…Subjective evaluation tools including Borg Rating of Perceived Exertion (Borg RPE) scale, Borg CR-10 scale, Pain Estimation Charts-The McGill Pain Questionnaire, and Visual Analog (VA) scale have also been adopted to assess physical workloads (Dadashi et al, 2022;DiDomenicoa and Nussbaum, 2008;Mehta and Agnew, 2015). Among these scales, Borg CR-10 scale is sensitive to physical demand changes (DiDomenicoa and Nussbaum, 2008;Shariat et al, 2018;Zamunér et al, 2011). The Borg RPE was suggested by CDC (2022) to fairly estimate the physical exertion subjectively a person experiences during physical activity.…”

“…Subjective measurements are easier to conduct to evaluate physical workloads associated with the tasks, however, real-time monitoring of physical workloads is impractical. With the encouraging development of smart wearable systems, physiological responses (strains) such as heart rate/heart rate variability (Mitratza et al, 2022;Umer et al, 2022), electroencephalogram (EEG)/ Electrocardiogram (ECG) (Das and Puthankattil, 2022;Mitratza et al, 2022), skin temperature (Mitratza et al, 2022), skin impedance (Huang et al 2022), etc. can be continuously and feasibly monitored in various industrial or laboratory settings associated with tasks.…”