Electrodermal activity (EDA), an indicator of arousal of the sympathetic nervous system, was investigated as a potential correlate of feeling-of-knowing (FOK) and tip-of-the-tongue (TOT) states. In Experiment 1, skin conductance was measured while participants answered general knowledge questions and made binary FOK and TOT judgments. Significant correlations were found between frequency of skin conductance responses (SCRs) and presence of both FOK and TOT states. In Experiment 2, warmth ratings were used and a follow-up clue session was added to offer participants the opportunity to resolve initially unanswered questions. SCR frequency during TOT states was significantly predictive of resolution during the clue period, although not as predictive as participants' warmth ratings. The potential of EDA as an on-line, non-intrusive measure of metamemory and memory retrieval is discussed.

Electrodermal activity (EDA), an indicator of arousal of the sympathetic nervous system, was investigated as a potential correlate of feeling-of-knowing (FOK) and tip-of-the-tongue (TOT) states. In Experiment 1, skin conductance was measured while participants answered general knowledge questions and made binary FOK and TOT judgments. Significant correlations were found between frequency of skin conductance responses (SCRs) and presence of both FOK and TOT states. In Experiment 2, warmth ratings were used and a follow-up clue session was added to offer participants the opportunity to resolve initially unanswered questions. SCR frequency during TOT states was significantly predictive of resolution during the clue period, although not as predictive as participants' warmth ratings. The potential of EDA as an on-line, non-intrusive measure of metamemory and memory retrieval is discussed.

Thesis (M.A.)--Boston University

Master of Landscape Architecture / Department of Landscape Architecture/Regional and Community Planning / Brent Chamberlain / The physical environment influences mental health and inevitably well-being. While exposure to natural environments shows salubrious health benefits among those who maintain a consistent connection, little is known about how urban environments impact mental health. As urbanization increases worldwide, it is essential to understand the linkages between urbanized environments and public health. This project is guided by the research question: How do different environmental characteristics affect stress-related responses in users? The study will guide individual subjects (n > 30) to walk a designated route, exposing them to different architectural and environmental elements in downtown Manhattan, Kansas. Physiological biofeedback sensors, including electrodermal activity (EDA) and heart rate sensors, will be used monitor physiological behavioral changes; GPS will provide spatial location; and a GoPro camera will provide real-time first-person experience. Data from these sensors will be integrated into a temporal-spatial analysis to ascertain correlations between architectural and environmental elements in space and associated stress responses. Upon completing the walk, participants will take a brief survey asking for their perceptions, both quantitatively and qualitatively, of the different environments they encounter on the walk. Raw data collected from the biofeedback devices will be refined and analyzed spatially using GIS mapping software. This will allow us to visualize any associations between design characteristics and the elicited behavioral responses in order to determine the environmental characteristics that may illicit heightened stress responses. Analysis of the survey data will seek to identify any correlations between physiological and perception-based responses. The intent of the research is to provide a foundation for further studies into how public policy can be better informed and augmented to mitigate potential public health issues caused by urban design. Results will also inform architectural and engineering decision-making processes to further improve urban design by identifying characteristics that may improve or decrease mental health of those living and/or frequenting urban environments.

Chronic stress is endemic to modern society. If we could monitor our mental state, we may be able to develop insights about how we respond to stress. However, it is unfeasible to continuously annotate stress levels all the time. In the studies conducted for this dissertation, a minimally-invasive wearable sensor platform and physiological data processing methods were developed to analyze a number of physiological correlates of mental stress. We present a minimally obtrusive wearable sensor system that incorporates embedded and wireless communication technologies. The system is designed such that it provides a balance between data collection and user comfort. The system records the following stress related physiological and contextual variables: heart rate variability (HRV), respiratory activity, electrodermal activity (EDA), electromyography (EMG), body acceleration, and geographical location. We assume that if the respiratory influences on HRV can be removed, the residual HRV will be more salient to stress in comparison with raw HRV. We develop three signal processing methods to separate HRV into a respiration influenced and residual HRV. The first method consists of estimating respiration-induced portion of HRV using a linear system identification method (autoregressive moving average model with exogenous inputs). The second method consists of decomposing HRV into respiration-induced principal dynamic mode and residual using nonlinear dynamics decomposition method (principal dynamic mode analysis). The third method consists of splitting HRV into respiration-induced power spectrum and residual in frequency domain using spectral weighting method. These methods were validated on a binary discrimination problem of two psychophysiological conditions: mental stress and relaxation. The linear system identification method, nonlinear dynamics decomposition method, and spectral weighting method classified stress and relaxation conditions at 85.2 %, 89.2 %, and 81.5 % respectively. When tonic and phasic EDA features were combined with the linear system identification method, the nonlinear dynamics decomposition method, and the spectral weighting method, the average classification rates were increased to 90.4 %, 93.2 %, and 88.1 % respectively. To evaluate the developed wearable sensors and signal processing methods on multiple subjects, we performed case studies. In the first study, we performed experiments in a laboratory setting. We used the wearable sensors and signal processing methods to discriminate between stress and relaxation conditions. We achieved 81 % average classification rate in the first case study. In the second study, we performed experiments to detect stress in ambulatory settings. We collected data from the subjects who wore the sensors during regular daily activities. Relaxation and stress conditions were allocated during daily activities. We achieved a 72 % average classification rate in ambulatory settings. Together, the results show achievements in recognizing stress from wearable sensors in constrained and ambulatory conditions. The best results for stress detection were achieved by removing respiratory influence from HRV and combining features from EDA.

No description available.

With the growth of wearable devices capable of measuring physiological signals, affective computing is becoming more popular than before that gradually will remove our cognitive approach. One of the physiological signals is the electrodermal activities (EDA) signal. We explore how video stimulus that might arouse fear affect the EDA signal. To better understand EDA signal, two different medians, a scene from a movie and a scene from a video game, were selected to arouse fear. We conducted a user study with 20 participants and analyzed the differences between medians and proposed a method capable of detecting the highlights of the stimulus using only EDA signals. The study results show that there are no significant differences between two medians except that users are more engaged with the content of the video game. From gathered data, we propose a similarity measurement method for clustering different users based on how common they reacted to different highlights. The result shows for 300 seconds stimulus, using a window size of 10 seconds, our approach for detecting highlights of the stimulus has the precision of one for both medians, and F1 score of 0.85 and 0.84 for movie and video game respectively. / Master of Science / In this work, we explore different approaches to analyze and cluster EDA signals. Two different medians, a scene from a movie and a scene from a video game, were selected to arouse fear. By conducting a user study with 20 participants, we analyzed the differences between two medians and proposed a method capable of detecting highlights of the video clip using only EDA signals. The result of the study, shows there are no significant differences between two medians except that users are more engaged to the content of the video game. From gathered data, we propose a similarity measurement method for clustering different user based on how common they reacted to different highlights.

Electrodermal responding (EDR) and heart rate (HR) were assessed for seven subjects participating in a reaction time task consequated with monetary bonuses (250, 100, and 10), monetary penalties (250,100, and 10), and a monetary neutral value (00). Unlike previous research employing group designs and a tonic measure (i.e., mean over long periods of time), this study utilized a single-subject design and a phasic measure (i.e., mean over 2-s intervals). Heart rate data was too variable for meaningful analysis. EDR data showed that the peak levels of EDR were higher for penalties than for the corresponding values of bonuses (e.g., -250 vs. +250) for most subjects. Similarly, peak levels of EDR were generally higher during sessions in which consequences were presented than in sessions during which consequences were absent.

The first aim was to determine the baseline psychophysiological correlates in healthy subjects as a first necessary step towards the long-term goal of application the psychophysiological techniques in diagnostics mood and cognitive disorders. The second aim was to establish an easily applicable set of tests for evaluating emotional and memory processes by non-invasive psychophysiological methods. EEG, GSR, and eye-tracking data from 100 participants without any neurological or psychiatric disorders were obtained during watching affective pictures and performing memory tests. The spectral powers were computed for each 500 ms of the stimuli in theta, alpha, beta1, beta2 and beta3 bands in 12 areas of the brain. Lower alpha and higher beta3 power was related to higher emotional intensity. Negative emotions were distinguished in spatio-temporal changes of beta1 power and positive emotions showed higher beta3 power in right temporal region. Memory encoding showed higher alpha power. Lower theta and higher alpha power in central regions and overall increase of beta bands were observed during successful memory retrieval. A summary of spatio-temporal spectral correlates to emotional and memory processes was provided by this work. Key words: Electroencephalography, electrodermal activity, psychophysiology,...

Although tic disorders are diagnosed as neurological disorders, neurobehavioral models suggest that tics are controlled by premonitory urges that may be conditioned to become aversive through childhood, and that tics are exhibited to alleviate such phenomena. However, only indirect measures have been used to assess the presence of the premonitory urge. This study utilized self-report and GSR measurements to examine whether a punishing contingency conditioned stimuli to be aversive during conditions of tic suppression and whether punishing contingencies exacerbate aversive private phenomena in two adults. Results indicated that conditions of response cost (RC) and differential reinforcement (DRO) were effective at reducing the number of tics compared to baseline. Moreover, GSR was unrelated to urge and suppression conditions despite higher self-reported urge ratings in DRO and RC conditions. Implications of findings are discussed.