Estimation of skin conductance at low frequencies using measurements at higher frequencies for EDA applications

One-Channel Wearable Mental Stress State Monitoring System

Assessments of stress can be performed using physiological signals, such as electroencephalograms (EEGs) and galvanic skin response (GSR). Commercialized systems that are used to detect stress with EEGs require a controlled environment with many channels, which prohibits their daily use. Fortunately, there is a rise in the utilization of wearable devices for stress monitoring, offering more flexibility. In this paper, we developed a wearable monitoring system that integrates both EEGs and GSR. The novelty of our proposed device is that it only requires one channel to acquire both physiological signals. Through sensor fusion, we achieved an improved accuracy, lower cost, and improved ease of use. We tested the proposed system experimentally on twenty human subjects. We estimated the power spectrum of the EEG signals and utilized five machine learning classifiers to differentiate between two levels of mental stress. Furthermore, we investigated the optimum electrode location on the scalp when using only one channel. Our results demonstrate the system's capability to classify two levels of mental stress with a maximum accuracy of 70.3% when using EEGs alone and 84.6% when using fused EEG and GSR data. This paper shows that stress detection is reliable using only one channel on the prefrontal and ventrolateral prefrontal regions of the brain.

Sensors Capabilities, Performance, and Use of Consumer Sleep Technology

Sleep is crucial for the proper functioning of bodily systems and for cognitive and emotional processing. Evidence indicates that sleep is vital for health, well-being, mood, and performance. Consumer sleep technologies (CSTs), such as multisensory wearable devices, have brought attention to sleep and there is growing interest in using CSTs in research and clinical applications. This article reviews how CSTs can process information about sleep, physiology, and environment. The growing number of sensors in wearable devices and the meaning of the data collected are reviewed. CSTs have the potential to provide opportunities to measure sleep and sleep-related physiology on a large scale.

Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review

The electrodermal activity (EDA) signal is an electrical manifestation of the sympathetic innervation of the sweat glands. EDA has a history in psychophysiological (including emotional or cognitive stress) research since 1879, but it was not until recent years that researchers began using EDA for pathophysiological applications like the assessment of fatigue, pain, sleepiness, exercise recovery, diagnosis of epilepsy, neuropathies, depression, and so forth. The advent of new devices and applications for EDA has increased the development of novel signal processing techniques, creating a growing pool of measures derived mathematically from the EDA. For many years, simply computing the mean of EDA values over a period was used to assess arousal. Much later, researchers found that EDA contains information not only in the slow changes (tonic component) that the mean value represents, but also in the rapid or phasic changes of the signal. The techniques that have ensued have intended to provide a more sophisticated analysis of EDA, beyond the traditional tonic/phasic decomposition of the signal. With many researchers from the social sciences, engineering, medicine, and other areas recently working with EDA, it is timely to summarize and review the recent developments and provide an updated and synthesized framework for all researchers interested in incorporating EDA into their research.

Optimal combination of electrodes and conductive gels for brain electrical impedance tomography

BACKGROUND

Electrical impedance tomography (EIT) is an emerging imaging technology that has been used to monitor brain injury and detect acute stroke. The time and frequency properties of electrode-skin contact impedance are important for brain EIT because brain EIT measurement is performed over a long period when used to monitor brain injury, and is carried out across a wide range of frequencies when used to detect stroke. To our knowledge, no study has simultaneously investigated the time and frequency properties of both electrode and conductive gel for brain EIT.

METHODS

In this study, the contact impedance of 16 combinations consisting of 4 kinds of clinical electrode and five types of commonly used conductive gel was measured on ten volunteers' scalp for a period of 1 h at frequencies from 100 Hz to 1 MHz using the two-electrode method. And then the performance of each combination was systematically evaluated in terms of the magnitude of contact impedance, and changes in contact impedance with time and frequency.

RESULTS

Results showed that combination of Ag⁺/Ag⁺Cl^- powder electrode and low viscosity conductive gel performed best overall (Ten 20^® in this study); it had a relatively low magnitude of contact impedance and superior performance regarding contact impedance with time (p < 0.05) and frequency (p < 0.05).

CONCLUSIONS

Experimental results indicates that the combination of Ag⁺/Ag⁺Cl^- powder electrode and low viscosity conductive gel may be the best choice for brain EIT.