An Assessment of Psychological Noise Reduction by Landscape Plants

The emphasis in the term ‘Green Transportation’ is on the word ‘green’. Green transportation focuses on the construction of a slow transport system with a visually pleasing, easy and secure trip environment composed of urban parks, green roadside spaces and some other space that is full of landscape plants. This trip environment encourages residents to make trip choices that reduce fuel consumption and pollution and is one of the most important ways of popularizing green transportation. To study the psychological benefits provided by urban parks and other landscape environments, we combined a subjective approach (a questionnaire) with an objective quantitative approach (emotional tests using an electroencephalogram; EEG). Using a questionnaire survey, we found that 90% of the subjects believed that landscape plants contribute to noise reduction and that 55% overrated the plants’ actual ability to attenuate noise. Two videos (showing a traffic scene and a plant scene) were shown to 40 participants on video glasses. We detected and recorded EEG values with a portable electroencephalograph, and a comparison between the results of the two groups revealed that there was a highly significant asymmetry between the EEG activity of the vegetation scene and traffic scene groups. The results suggest that the emotions aroused by noise and visual stimuli are manifested in the synchronization of beta frequency band and the desynchronization of alpha frequency band, indicating that landscape plants can moderate or buffer the effects of noise. These findings indicate that landscape plants provide excess noise attenuating effects through subjects’ emotional processing, which we term ‘psychological noise reduction’

Physiological-based Driver Monitoring Systems: A Scoping Review

A physiological-based driver monitoring system (DMS) has attracted research interest and has great potential for providing more accurate and reliable monitoring of the driver’s state during a driving experience. Many driving monitoring systems are driver behavior-based or vehicle-based. When these non-physiological based DMS are coupled with physiological-based data analysis from electroencephalography (EEG), electrooculography (EOG), electrocardiography (ECG), and electromyography (EMG), the physical and emotional state of the driver may also be assessed. Drivers’ wellness can also be monitored, and hence, traffic collisions can be avoided. This paper highlights work that has been published in the past five years related to physiological-based DMS. Specifically, we focused on the physiological indicators applied in DMS design and development. Work utilizing key physiological indicators related to driver identification, driver alertness, driver drowsiness, driver fatigue, and drunk driver is identified and described based on the PRISMA Extension for Scoping Reviews (PRISMA-Sc) Framework. The relationship between selected papers is visualized using keyword co-occurrence. Findings were presented using a narrative review approach based on classifications of DMS. Finally, the challenges of physiological-based DMS are highlighted in the conclusion. Doi: 10.28991/CEJ-2022-08-12-020 Full Text: PD

The Effect of Noise Exposure on Cognitive Performance and Brain Activity Patterns

Background: It seems qualitative measurements of subjective reactions are not appropriate indicators to assess the effect of noise on cognitive performance. In this study, quantitative and combined indicators were applied to study the effect of noise on cognitive performance. Materials and Methods: A total of 54 young subjects were included in this experimental study. The participants’ mental work load and attention were evaluated under different levels of noise exposure including, background noise, 75, 85 and 95 dBA noise levels. The study subject’s EEG signals were recorded for 10 minutes while they were performing the IVA test. The EEG signals were used to estimate the relative power of their brain frequency bands. Results: Results revealed that mental work load and visual/auditory attention is significantly reduced when the participants are exposed to noise at 95 dBA level (P<0.05). Results also showed that with the rise in noise levels, the relative power of the Alpha band increases while the relative power of the Beta band decreases as compared to background noise. The most prominent change in the relative power of the Alpha and Beta bands occurs in the occipital and frontal regions of the brain respectively. Conclusions: The application of new indicators including brain signal analysis and power spectral density analysis is strongly recommended in the assessment of cognitive performance during noise exposure. Further studies are suggested regarding the effects of other psychoacoustic parameters such as tonality, noise pitch (treble or bass) at extended exposure levels

Study, definition and analysis of pilot/system performance measurements for planetary entry experiments

Definition analysis for experimental prediction of pilot performance during planetary entr

Mind The Perception And Emotional Response To Design:: Emerging Methodology

Design involves constant decision-making. The decision process is influenced by sets of conditions or parameters; some controllable, such as the business context, and some unpredictable and uncertain, such as stakeholders' preference. Design decisions related to user's perceptions and emotional response to sustainable features (daylight and green space) and aesthetic value (look and feel) are generally hard to evaluate and quantify. Typically, user response is solicited following construction, in post-occupancy evaluation studies. However, decisions with long-term impacts are often irreversible after implementation; therefore, decision-makers must seriously evaluate the design proposals(alternatives) before arriving at a decision. This paper presents an experiment conducted combining an immersive virtual environment and electroencephalogram (EEG) as a promising tool to evaluate design options during the early design stage of a project. More precisely, the objective is to (a) develop a data-driven approach for design evaluation and (b) understand the correlation between the end users' preference and emotional state. To our knowledge, this is the first time that the combination of virtual reality technology and brainwave response monitoring has been proposed to study the design validation method in architecture

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 317)

This bibliography lists 182 reports, articles and other documents introduced into the NASA scientific and technical information system in November, 1988

Assessing the Decision-Making Process in Human-Robot Collaboration Using a Lego-like EEG Headset

Human-robot collaboration (HRC) has become an emerging field, where the use of a robotic agent has been shifted from a supportive machine to a decision-making collaborator. A variety of factors can influence the effectiveness of decision-making processes during HRC, including the system-related (e.g., robot capability) and human-related (e.g., individual knowledgeability) factors. As a variety of contextual factors can significantly impact the human-robot decision-making process in collaborative contexts, the present study adopts a Lego-like EEG headset to collect and examine human brain activities and utilizes multiple questionnaires to evaluate participants’ cognitive perceptions toward the robot. A user study was conducted where two levels of robot capabilities (high vs. low) were manipulated to provide system recommendations. The participants were also identified into two groups based on their computational thinking (CT) ability. The EEG results revealed that different levels of CT abilities trigger different brainwaves, and the participants’ trust calibration of the robot also varies the resultant brain activities

Parent-led massage and sleep EEG for term-born infants: A randomized controlled parallel-group study

AIM: To examine the impact of parent-led massage on the sleep electroencephalogram (EEG) features of typically developing term-born infants at 4 months. METHOD: Infants recruited at birth were randomized to intervention (routine parent-led massage) and control groups. Infants had a daytime sleep EEG at 4 months and were assessed using the Griffiths Scales of Child Development, Third Edition at 4 and 18 months. Comparative analysis between groups and subgroup analysis between regularly massaged and never-massaged infants were performed. Groups were compared for sleep stage, sleep spindles, quantitative EEG (primary analysis), and Griffiths using the Mann-Whitney U test. RESULTS: In total, 179 out of 182 infants (intervention: 83 out of 84; control: 96 out of 98) had a normal sleep EEG. Median (interquartile range) sleep duration was 49.8 minutes (39.1-71.4) (n = 156). A complete first sleep cycle was seen in 67 out of 83 (81%) and 72 out of 96 (75%) in the intervention and control groups respectively. Groups did not differ in sleep stage durations, latencies to sleep and to rapid eye movement sleep. Sleep spindle spectral power was greater in the intervention group in main and subgroup analyses. The intervention group showed greater EEG magnitudes, and lower interhemispherical coherence on subgroup analyses. Griffiths assessments at 4 months (n = 179) and 18 months (n = 173) showed no group differences in the main and subgroup analyses. INTERPRETATION: Routine massage is associated with distinct functional brain changes at 4 months