Evaluation of an objective listening effort measure in a selective, multi-speaker listening task using different hearing aid settings

Schäfer, Patrick; Šerman, Maja; Arnold, Mirko; Corona-Strauss, Farah I.; Strauß, Daniel J.; Seidler-Fallbohmer, Brigit; Seidler, Harald

doi:10.1109/embc.2015.7319430

Cited by 9 publications

(8 citation statements)

References 12 publications

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“…Measuring brain activity is an objective method of assessing the physiological impact of engaging with the environment (Keshavarz, Campos, & Berti, 2015;Schäfer et al, 2015). Brain imaging is useful for measuring the effects of unconscious or masked stimuli (Teplan, 2002;Whalen et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

Brain activity, underlying mood and the environment: A systematic review

Norwood

Lakhani

Maujean

et al. 2019

Journal of Environmental Psychology

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This review explores how different environments affect brain activity and associated mood response. MEDLINE, CINAHL, Web of Science, PsychInfo and EMBASE were searched for peer-reviewed literature published prior to February 2019. 26 sources were included and divided into either a laboratory (n = 17) or naturalistic (n = 9) design. Most (n = 16) compared natural environments against urban/non-natural environments. Natural environments were associated with low frequency brainwaves and lower brain activity in frontal areas, indicating comfortable and subjectively restorative feelings. Urban environments appear to induce brain responses associated with negative affect (demonstrated in an overactive amygdala region). Furthermore, urban environments were associated with activation of the posterior cingulate cortex associated with top-down processing/effortful attention. A sensory accumulation effect is suggested, where the realism of an experimental condition, and therefore validity of participant responses, is greater when more senses are engaged. Longitudinal research is needed to determine whether chronic exposure to environments can promote change in brain behaviour.

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Section: Introductionmentioning

confidence: 99%

Brain activity, underlying mood and the environment: A systematic review

Norwood

Lakhani

Maujean

et al. 2019

Journal of Environmental Psychology

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“…The measurement of brain activity is an objective way of assessing the physiological perception of engagement with the landscape, environment, or other objects [ 23 , 24 , 25 ]. Brain imaging is helpful to measure the effects of unconscious stimuli [ 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features

Wang

2022

IJERPH

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This paper puts forward a new method of landscape recognition and evaluation by using aerial video and EEG technology. In this study, seven typical landscape types (forest, wetland, grassland, desert, water, farmland, and city) were selected. Different electroencephalogram (EEG) signals were generated through different inner experiences and feelings felt by people watching video stimuli of the different landscape types. The electroencephalogram (EEG) features were extracted to obtain the mean amplitude spectrum (MAS), power spectrum density (PSD), differential entropy (DE), differential asymmetry (DASM), rational asymmetry (RASM), and differential caudality (DCAU) in the five frequency bands of delta, theta, alpha, beta, and gamma. According to electroencephalogram (EEG) features, four classifiers including the back propagation (BP) neural network, k-nearest neighbor classification (KNN), random forest (RF), and support vector machine (SVM) were used to classify the landscape types. The results showed that the support vector machine (SVM) classifier and the random forest (RF) classifier had the highest accuracy of landscape recognition, which reached 98.24% and 96.72%, respectively. Among the six classification features selected, the classification accuracy of MAS, PSD, and DE with frequency domain features were higher than those of the spatial domain features of DASM, RASM and DCAU. In different wave bands, the average classification accuracy of all subjects was 98.24% in the gamma band, 94.62% in the beta band, and 97.29% in the total band. This study identifies and classifies landscape perception based on multi-channel EEG signals, which provides a new idea and method for the quantification of human perception.

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“…For example, measuring brain activity with various types of brain imaging equipment is an objective method to obtain physiological indicators in contact with the environment [4][5][6]. Brain imaging can measure the effects of unconscious or masked sensations [7,8].…”

Section: Introductionmentioning

confidence: 99%

Electroencephalogram Application for the Analysis of Stress Relief in the Seasonal Landscape

Wang

2021

IJERPH

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This study proposes an integrated approach to assess the psychological and physiological responses of people in natural seasonal landscapes. The questionnaire of restoration outcomes scale (ROS), willingness to visit (WTV), cultural ecosystem services (CES) cognitive classification, and the neuroscientific technique based on electroencephalogram (EEG) measurements were applied. The effects of different landscapes on human perception were studied by comparing the EEG data of different landscape types and different seasons. The coupling relationship between EEG data and stress recovery was also examined. The results showed the following: First, there was a significant difference between the winter landscape and the summer natural landscape. Second, only the winter landscape showed significant gender differences. Third, the values of ROS and WTV in the summer landscape were greater than those in the winter landscape. Fourth, the number of CES in the summer landscape was significantly higher than that in the winter landscape, and the number of CES in water was higher than that in the forest and grassland. Thus, brain wave data and quantified values from questionnaires including ROS, WTV, and CES showed significant seasonality. Therefore, an EEG can be used as a new, more objective tool and method for landscape evaluation and planning in the future.

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Evaluation of an objective listening effort measure in a selective, multi-speaker listening task using different hearing aid settings

Cited by 9 publications

References 12 publications

Brain activity, underlying mood and the environment: A systematic review

Brain activity, underlying mood and the environment: A systematic review

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features

Electroencephalogram Application for the Analysis of Stress Relief in the Seasonal Landscape

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