Electroencephalogram Detection for Insomnia Patients: A Preliminary Study

Abstract

Measurement of insomnia is currently generally carried out by medical practitioners by looking at the patient's condition accompanied by symptoms that refer to insomnia. In contrast, minimal quantitative measurements were found. This study proposes an alternative measurement with the acquisition of brainwave activity through electroencephalogram (EEG) in identifying sleep disorders. Insomnia is a common sleep disorder that can make it difficult to fall asleep difficult to stay asleep, or cause waking up too early and not being able to go back to sleep. Insomnia not only weakens energy levels and moods, but also a person's health, performance, and quality of life. This sleep disorder appears due to several factors, such as anxiety, stress, depression, bipolar disorder, or trauma. Photic stimulation is given as an attempt to find a person's body's response to light. Late adolescents with insomnia symptoms with an age range of 17-25 years were included as respondents, had previously been given a simulation test related to the treatment of sleep disorders, and identified severe, moderate, and mild insomnia. Acquisition using Narosky Mindwave Mobile 2 with the electrode in forehead position, Fp1. This study compares several types of insomnia data acquisition from previous studies and obtains patterns of insomniacs based on photic stimulation.

Remote Wearable Neuroimaging Devices for Health Monitoring and Neurophenotyping: A Scoping Review

“…Ecological momentary assessment (EMA), a research methodology that involves observing subjects in their natural environment [8], addresses the limitations of traditional neuroimaging techniques, which often lack real-world applicability [9]. Traditional approaches often involve simplified, decontextualized tasks that fail to capture the complexities of natural human behaviors and environments [10]. By integrating technologies like wearable neuroimaging devices into everyday settings, researchers can gather more ecologically valid data.…”

“…It captures the electrical activity of the brain at various frequency bands, where different frequencies serve as biomarkers of different health conditions. For example, alpha waves, which are in a relatively high frequency range (8)(9)(10)(11)(12), are associated with relaxation and calmness. In contrast, beta waves, which are lower in frequency (with a range of 12-30 Hz), are associated with highly demanding mental activity such as analytical thought and anxiety [15].…”