V20. Gender differences in the quantitative EEG in relaxed states and during cognitive or emotional challenges

Dimpfel, W.

doi:10.1016/j.clinph.2015.04.098

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…Similarly, model 1b, which was trained to discriminate based on sex, showed larger beta power (12-18 Hz) for females as the most distinguishing feature. Multiple prior studies have identified similar observations in which beta power has been reported to be higher in female subjects compared to male [55][56][57]. For example, in a similar study that investigated the EEG during rest condition from 1308 subjects, beta activity was found to be the most distinctive attribute in discriminating between male and female subjects [57].…”

Section: Videogame Conditionmentioning

confidence: 60%

Assaying neural activity of children during video game play in public spaces: a deep learning approach

et al. 2019

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Objective. Understanding neural activity patterns in the developing brain remains one of the grand challenges in neuroscience. Developing neural networks are likely to be endowed with functionally important variability associated with the environmental context, age, gender, and other variables. Therefore, we conducted experiments with typically developing children in a stimulating museum setting and tested the feasibility of using deep learning techniques to help identify patterns of brain activity associated with different conditions. Approach. A four-channel dry EEG-based Mobile brain-body imaging data of children at rest and during videogame play (VGP) was acquired at the Children’s Museum of Houston. A data-driven approach based on convolutional neural networks (CNN) was used to describe underlying feature representations in the EEG and their ability to discern task and gender. The variability of the spectral features of EEG during the rest condition as a function of age was also analyzed. Main results. Alpha power (7–13 Hz) was higher during rest whereas theta power (4–7 Hz) was higher during VGP. Beta (13–18 Hz) power was the most significant feature, higher in females, when differentiating between males and females. Using data from both temporoparietal channels to classify between VGP and rest condition, leave-one-subject-out cross-validation accuracy of 67% was obtained. Age-related changes in EEG spectral content during rest were consistent with previous developmental studies conducted in laboratory settings showing an inverse relationship between age and EEG power. Significance. These findings are the first to acquire, quantify and explain brain patterns observed during VGP and rest in freely behaving children in a museum setting using a deep learning framework. The study shows how deep learning can be used as a data driven approach to identify patterns in the data and explores the issues and the potential of conducting experiments involving children in a natural and engaging environment.

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Section: Videogame Conditionmentioning

confidence: 60%

Assaying neural activity of children during video game play in public spaces: a deep learning approach

et al. 2019

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“…Regarding relaxation, concentration, or sleep quality monitoring systems, in [ 44 ], so many differences between genders are identified both in spectral power and in different oscillatory activities for deep sleep states, that the conclusion states that for this type of study, gender should always be taken into account. In [ 45 ], a broader study covering different tasks (eyes open/closed, relaxation, video viewing, and connection tasks) and differences in spectral power are also reported for all cases, reaching the same conclusion.…”

Section: Analysis For Gender Perspective Inclusionmentioning

confidence: 68%

Electronic Design for Wearables Devices Addressed from a Gender Perspective: Cross-Influences and a Methodological Proposal

Romero

Andújar

López-Ongil

2023

Sensors

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The design of wearable devices has been approached from many perspectives over the years, mainly from a functionality, electronics, mechanics, usability, wearability, or product design perspective. However, there is a missing point in these approaches: the gender perspective. Gender intersects with every approach and, considering the interrelationships and dependencies, can achieve a better adherence, reach a wider audience, and even change the conception of the wearables design paradigm. The electronics design addressed from a gender perspective must consider both the morphological and anatomical impacts and those emanating from socialization. This paper presents an analysis of the different factors to consider when designing the electronics of a wearable device, including the functionality to implement, sensors, communications, or the location, together with their interdependencies, and proposes a user-centered methodology that contemplates a gender perspective at every stage. Finally, we present a use case that validates the proposed methodology in a real design of a wearable device for the prevention of gender-based violence cases. For the application of the methodology, 59 experts have been interviewed, 300 verbatims have been extracted and analyzed, a dataset from the data of 100 women has been created and the wearable devices have been tested for a week by 15 users. The electronics design needs to be addressed from a multidisciplinary approach, by rethinking the decisions taken for granted and analyzing the implications and interrelationships from a gender perspective. We need to enroll more diverse people at every design stage and include gender as one of the variables to study.

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“…The present retrospective analysis of several clinical studies was undertaken in order to sort out if there are gender dependent quantitative differences in the absolute spectral power in different brain regions. EEG recordings were taken using the CATEEM Ò technology as described earlier based on 17 electrode positions (Dimpfel, 2014). Spectral power -averaged during recordings of 5 min duration -was compared during relaxed states ''eyes open'' and ''eyes closed'' as well as during different cognitive tasks (concentration test, memory test or math calculation) or watching different videos (animal film, comedy film, Disney film, erotic and sex film) or several TV commercials.…”

mentioning

confidence: 99%

V19. Neural correlates of otolith stimulation: Results of an EEG study

Ertl

Moser

Dieterich

2015

Clinical Neurophysiology

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V20. Gender differences in the quantitative EEG in relaxed states and during cognitive or emotional challenges

Cited by 5 publications

References 2 publications

Assaying neural activity of children during video game play in public spaces: a deep learning approach

Assaying neural activity of children during video game play in public spaces: a deep learning approach

Electronic Design for Wearables Devices Addressed from a Gender Perspective: Cross-Influences and a Methodological Proposal

V19. Neural correlates of otolith stimulation: Results of an EEG study

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