Дисертації з теми "Psychophysiological state"
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Wusk, Grace Caroline. "Psychophysiological Monitoring of Crew State for Extravehicular Activity." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/103386.
Повний текст джерелаDoctor of Philosophy
A spacewalk is one of the most important and physically and mentally challenging tasks that astronauts complete. With next-generation missions to the Moon and Mars, exploration spacewalks will challenge astronauts in reduced-weight environments (1/6 and 1/3 Earth's gravity) with longer, more frequent spacewalks and with less help from mission control. To keep astronauts safe while exploring there is a need to better understand astronaut health and performance (physical and mental) during spacewalks. With knowledge of how astronauts will respond to high workload and stressful events, we can plan missions and design tools that can best assist them during spacewalks on the Moon and Mars when help from Earth mission control is limited. Traditional tools of quantifying mental state are not suitable for real-time assessment during spacewalks. Current methods, including subjective surveys and performance-based computer tests, require time and attention to complete and cannot assess real-time operations. The focus of this dissertation is to create a psychophysiological monitoring tool to measure mental workload during a virtual reality (VR) spacewalk. Psychophysiological monitoring uses physiological measures, like heart rate and breathing rate, to predict psychological state, like high workload or stress. Physiological signals were recorded using commercial wearable devices in two human research studies, one at Virginia Tech and one at NASA Johnson Space Center. With machine learning, computer models can be trained to recognize patterns in physiological measures for different psychological states. Once a model is trained, it can be tested on new data to predict mental workload. To train and test the models, participants in the studies completed high and low workload versions of the VR task. The VR task was specifically designed for this study to simulate and measure performance during a mentally-challenging spacewalk scenario. The participants walked at their own pace on a treadmill while wearing a VR headset to move along a virtual lunar surface, while balancing their time and resources. They were also responsible for identifying and recalling flags along their virtual path. Ultimately, this work tests the limits of extending laboratory psychophysiological monitoring to more realistic environments using wearable devices, and of generalizing predictive models across participants, times, and tasks. This work paves the way for future field studies and real-time implementation to close the loop between human and automation.
Kuroda, Yusuke. "Metamotivational dominance and state in relation to psychophysiological response during exercise." Thesis, Aberystwyth University, 2009. http://hdl.handle.net/2160/caebd8a2-077b-49b1-a9bb-06ecd11c0dfe.
Повний текст джерелаCannon, Jordan. "Statistical analysis and algorithms for online change detection in real-time psychophysiological data." Thesis, University of Iowa, 2009. https://ir.uiowa.edu/etd/342.
Повний текст джерелаThrall, Graham. "Psychosocial and psychophysiological characteristics of atrial fibrillation patients and their influence on the prothrombotic state and prognosis." Thesis, University of Birmingham, 2006. http://etheses.bham.ac.uk//id/eprint/246/.
Повний текст джерелаJurosic, Brianna K. "The Effectiveness of Psychophysiological Relaxation Techniques in Reducing State Anxiety Directed Towards Academic Performance in College Students." Ashland University Honors Theses / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=auhonors1607005364655131.
Повний текст джерелаMarques, Daniel Ruivo. "The hyperarousal hypothesis in psychophysiological insomnia: study of default-mode network and its modification after CBT." Doctoral thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/16787.
Повний текст джерелаA insónia primária é a perturbação do comportamento de sono mais prevalente quer na população clínica quer na comunidade. Uma das formas mais comuns é a insónia psicofisiológica (IP). A hiperativação neuropsicofisiológica, afetiva, cognitiva e comportamental assim como o condicionamento mal-adaptativo entre estímulos associados ao sono e à cama com estímulos indutores de ativação são duas das características mais diferenciadoras desta patologia. Tendo por base a importância que esta perturbação assume em termos de saúde pública, levou-se a cabo 4 estudos empíricos com recurso a ressonância magnética funcional: No primeiro estudo comparou-se a ativação neurobiológica entre um grupo de doentes com IP (n=5) e um grupo de indivíduos saudáveis (n=5) emparelhado quanto ao sexo e à idade quando eram confrontados com palavras que remetiam para preocupações do passado/presente, preocupações do futuro e palavras neutras; no segundo estudo, explorou-se as diferenças na ativação referente à default-mode network (DMN) e outras resting-states nos mesmos grupos do estudo 1; no terceiro e quarto estudos, repetiram-se os mesmos procedimentos para um grupo clínico (N=2) após estes terem sido submetidos a terapia cognitivo-comportamental para a insónia (TCC-I). No geral, verificou-se que os doentes com IP exibiram um padrão generalizado de hiperativação em áreas associadas à DMN quer quando confrontados com estímulos ativadores quer em repouso; em termos de ativação nas resting-states, constatou-se que, em repouso, o grupo clínico apresentou disfunções significativas. Após TCC-I, observou-se que os indicadores disfuncionais verificados nos estudos anteriores se esbateram tendendo a aproximar-se do perfil de ativação dos indivíduos saudáveis. Os resultados obtidos reforçam assim a ideia da hiperativação na insónia ao longo das 24 horas do dia assim como do papel fundamental que a ativação cognitiva parece ter na etiopatogenia e no tratamento da insónia. Para além disso, este trabalho contribui para um melhor entendimento da neurobiologia da insónia e sugere que se podem identificar mecanismos neuronais subjacentes às modificações operadas pela TCC-I.
Primary Insomnia is the more prevalent sleep disorder both in clinical and community samples. One of the most frequent subtypes is psychophysiological insomnia (PI). The hyperarousal at different levels – biological, affective, cognitive, and behavioral – and the maladaptive conditioning between sleep-related stimuli and arousal are two major features of PI. Since this is a disorder which assumes an important role in public health, we performed 4 empirical studies recurring to fMRI: In the first study, we compared neurobiological activation between a group of PI patients (n=5) and a sex- and age-matched control group (n=5) when they were exposed to words concerning to past/present worries, future worries and neutral words; in the second study, we explored the activity of default-mode network (DMN) and other brain resting-states in the same groups as study 1; in the third and fourth studies, we repeated both experiments in a clinical group of patients with PI (N=2) after they underwent cognitive-behavioral therapy for insomnia (CBT-I). In general, it was observed that PI patients exhibited a generalized pattern of hyperarousal in several brain areas associated with DMN when they were confronted with affective stimuli and when they were resting in the fMRI scanner. In terms of activation of brain resting networks, we observed that the clinical group presented significant dysfunctions. After CBT-I, it was detected that the dysfunctional indicators observed in previous studies normalize, approaching the activation patterns typical of healthy individuals. The obtained results enhance the idea that the hyperarousal in PI is present during the 24-hours of the day; besides, the key role that cognitive arousal may be in the etiology and therapy of insomnia is also highlighted. In conclusion, this work contributes to a better understanding of neurobiology of insomnia and suggests that it might be possible to identify neural mechanisms underlying modifications accounted by CBT-I.
Кущ, Віталій Сергійович. "Метод підбору та виявлення впливів релаксуючих картин для коригування психофізіологічного стану людини". Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/39383.
Повний текст джерелаThe work contains 70 pages, 25 figures, and 19 tables. 12 sources have been used. Goal: to increase the speed and efficiency of research and adjustment of the psychophysiological state of a person by developing a method of matching and detecting influences of relaxing pictures for human psychophysiological state adjustment. A review of the main provisions of research, data collection, and adjustment of the psychophysiological state of humans. The main problems of processing the collected data for the analysis, matching of relaxing pictures are described and the necessity in the development of methods for matching and detecting influences on a psychophysiological condition of relaxing pictures is defined. A method of matching relaxing pictures for correction of the psychophysiological state of a human on the basis of neural networks is offered. The application of the proposed method allows you to submit a set of parameters: color preference, birthday, favorite color, subjective feelings and get a relaxing picture for sessions to correct the psychophysiological state. A method for detecting influences on the psychophysiological state of a person is proposed, which allows, due to a flexible configuration mechanism for plotting, to build various parameters of research of the psychophysiological state of a person and identify their dependencies and influences on a person. The software of the offered methods of matching and detecting influences of relaxing pictures on a condition of the human which increases the efficiency of work of psychologists on the research of a psychophysiological condition of the person is developed. A software startup project has been developed and an analysis of potential customers and the market has been conducted, which shows that the market is still free from analogs of such a product, but needs it.
Pandey, Amare Ketsela Tesfaye and Amrit. "Empirical Evaluation of Machine Learning Algorithms based on EMG, ECG and GSR Data to Classify Emotional States." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3673.
Повний текст джерелаThe thesis is focused to classify emotional states from physiological signals. Features extraction and selection of the physiological signal was done, which was used for dataset formation and then classification of those emotional states. IAPS pictures were used to elicit emotional/affective states. Experiment was conducted with 13 participants in cognition and Robotics lab using biosensors EMG, ECG and GSR at BTH University. Nine participants data were taken for further preprocessing. We observed in our thesis the classification of emotions which could be analyzed by a combination of psychophysiological signal as Model A and Model B. Since signals of subjects are different for same emotional state, the accuracy was better for single participant than all participants together. Classification of emotional states is useful for HCI and HRI to manufacture emotional intelligence robot. So, it is essential to provide best classifier algorithms which can be helpful to detect emotions for developing emotional intelligence robots. Our work contribution lies in providing best algorithms for emotion recognition for psychophysiological data and selected features. Most of the results showed that SVM performed best with classification accuracy up to 59 % for single participant and 48.05 % for all participants together. For a single dataset and single participant, we found 60.17 % accuracy from MLP but it consumed more time and memory than other algorithms during classification. The rest of the algorithms like BNT, Naive Bayes, KNN and J48 also gave competitive accuracy to SVM. We conclude that SVM algorithm for emotion recognition from a combination of EMG, ECG and GSR is capable of handling and giving better classification accuracy among others. Tally between IAPS pictures with SAM helped to remove less correlated signals and to obtain better accuracies. Still the obtained results are small in percentage. Therefore, more participants are probably needed to get a better accuracy result over the whole dataset.
amarehenry@gmail.com ; Mobile: 0767042234 amrit.pandey111@gmail.com ; Mobile : 0704763190
Freeburn, Peter D. "A Few Good Men: Narratives of Racial Discrimination Impacting Male African American/Black Officers in the United States Marine Corps." Diss., NSUWorks, 2018. https://nsuworks.nova.edu/shss_dcar_etd/95.
Повний текст джерелаNogueira, Pedro Gonçalo Ferreira Alves. "Emotional State Regulation in Interactive Environments: A Psychophysiological Adaptive Approach for Affect-Inductive Experiences." Tese, 2016. https://hdl.handle.net/10216/91925.
Повний текст джерелаNogueira, Pedro Gonçalo Ferreira Alves. "Emotional State Regulation in Interactive Environments: A Psychophysiological Adaptive Approach for Affect-Inductive Experiences." Doctoral thesis, 2016. https://hdl.handle.net/10216/91925.
Повний текст джерелаLadd, Sandra Lee. "Cardiovascular psychophysiological and behavioral evidence for an affective implicit priming mechanism." Thesis, 2014. https://hdl.handle.net/2144/15289.
Повний текст джерелаFaria, Helena Margarida de Gouveia. "Towards the Identification of Psychophysiological States in EEG." Dissertação, 2018. https://repositorio-aberto.up.pt/handle/10216/113148.
Повний текст джерелаFaria, Helena Margarida de Gouveia. "Towards the Identification of Psychophysiological States in EEG." Master's thesis, 2018. https://repositorio-aberto.up.pt/handle/10216/113148.
Повний текст джерелаLai, Li-Yun, and 賴麗筠. "The Effects of Natural Elements on Visual and Auditory Experiences of Tranquility and Psychophysiological States under Noisy Environments." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/4u9g9g.
Повний текст джерела國立勤益科技大學
景觀設計系
106
Nowadays, traffic noise has become one of the major noise sources in the urban environment which can cause some physical and psychological problems and concerns. In order to improve the quality of the urban environment, this study aims to explore the influence of intervening sensory experience of different natural elements in urban traffic noise environment on space users' tranquility and emotional state. The research is mixing quantitative and qualitative methods. The quantitative data were collected through questionnaires and physiological feedback, while the qualitative data of the emotional reaction process of individual experience were recorded via interviews. Participants were randomly assigned to the green-plant group and the waterscape group. Each participant experienced three sensory stimulations (one for each week), including visual stimulus(green plant/falling water scene), auditory stimulus (bird/water sound), and audio-visual stimulus (green plant and bird sound/falling water and water sound).The results show that experiencing natural elements (green elements and water elements) through three sensory stimulations in the noise environment can not only improve user's tranquility and positive emotions, but also reduce negative emotions significantly. On visual and audio-visual sensory stimulations, compared to water elements, experiencing green elements can enhance user's tranquility, positive emotions, and reduce anxiety. In the physiological benefits, experiencing the natural element through auditory and audio-visual sensory can increase LF% and decrease HF%, which means that intervening natural sounds to the environment can make people feel excited and arousal. Experiencing the green elements through auditory and audio-visual sensory can improve HRV indicating that adding the bird sounds to the noise environment, user would feel emotionally relieved. Overall, experiencing the green elements through audio-visual sensory is able to promote most positive effects. Experiencing the water element through three types of stimulations, users can all significantly improve tranquility, reduce negative emotions, and decrease blood pressure. In addition, experiencing the water element through auditory and audio-visual sensory, users can increase LF% and decrease HF%. The similar trend is found in the qualitative analysis. Most participants state that listening to the bird sounds would have a pleasant feeling, and adding water elements can make them calmer. The results of the emotional reaction process show that participants turn their attention to green plants or waterscape and ignore the effect of noise when they experience visual sensory stimulation. Under auditory sensory stimulation, participants pay attention to listening to the natural sound and feel it can overwhelm the noise to achieve noise reduction. Participants believe that the audio-visual sensory experience of natural elements can achieve the effect of blocking noise and make people more tranquility. Furthermore, when the "green plant and bird sound" element is added to the noise environment, participants can have more pleasant emotions. When the "Waterscape and water sound" element is added to the noise environment, most participants express their calm emotions. Among them, water sound can make participants feel the microclimate change of environment, which makes them feel refreshed. "Waterscape and water sound" can induce richer emotional responses (such as curious, interesting) than "green plant and bird sound". The results can provide the design reference to improve urban noise environment and increase environmental quality.