Thesis advisor: Elizabeth Kensinger / Individuals with social anxiety disorder (SAD) tend to have emotional memory biases in the encoding and retrieval of social memories. Research has shown reduced heart rate variability (HRV) in clinical populations suffering from anxiety, including social anxiety. Heightened sympathetic activation—as measured by the electrodermal activity (EDA)—has also been associated with anxiety disorders. The aim of the present study was to examine the relation between HRV, social anxiety, and re-experiencing of emotional autobiographical memories. 44 healthy young adults were recruited from the Boston College campus through SONA. Participants were given an online survey that instructed them to retrieve 40 specific events from the past in response to 40 socially relevant cues. For each event, participants were instructed to provide a brief narrative, make several ratings for the event (on a scale from 1-7), and indicate the specific emotions they experienced both at the time of retrieval and of the event. Approximately one month after the completion of the memory survey, participants engaged in a 2-hour memory retrieval session while undergoing psychophysiological monitoring (heart rate, skin conductance, and respiration). Following the retrieval task, participants completed self-report questionnaires of social anxiety symptom severity and trait emotion regulation strategy (i.e., tendency to reappraise or suppress emotions). The present study found that positive memories had higher re-experiencing ratings as compared to negative memories. Contrary to the original study hypothesis, however, there was no significant interaction between average re-experiencing (or arousal) ratings of positive or negative social autobiographical memories and SAD likelihood. A nonlinear, cubic relationship was found between one of three metrics of HRV and social anxiety symptom severity. A significant effect was found between skin conductance and SAD likelihood, which was likely driven by an almost significance difference in skin conductance between the SAD unlikely and the SAD very probable groups; these findings provide further insight into the relationship between autonomic nervous system (ANS) functioning and social anxiety. Further, the present results suggest the intriguing possibility that there may be a nonlinear relationship between HRV and severity of social anxiety. Future research with a larger sample size is needed to corroborate these findings. / Thesis (BS) — Boston College, 2018. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Psychology.

The electro-optic technique of measuring the cardiovascular pulse wave known as photoplethysmography (PPG) is clinically utilised for noninvasive characterisation of physiological components by dynamic monitoring of tissue optical absorption. There has been a resurgence of interest in this technique in recent years, driven by the demand for a low cost, compact, simple and portable technology for primary care and community-based clinical settings, and the advancement of computer-based pulse wave analysis techniques. PPG signal provides a means of determining cardiovascular properties during the cardiac cycle and changes with ageing and disease. This thesis focuses on the photoplethysmographic signal for cardiovascular assessment. The contour of the PPG pulse wave is influenced by vascular ageing. Contour analysis of the PPG pulse wave provides a rapid means of assessing vascular tone and arterial stiffness. In this thesis, the parameters extracted from the PPG pulse wave are examined in young adults. The results indicate that the contour parameters of the PPG pulse wave could provide a simple and noninvasive means to study the characteristic change relating to arterial stiffness. The pulsatile component of the PPG signal is due to the pumping action of the heart, and thus could reveal the circulation changes of a specific vascular bed. Heart rate variability (HRV) represents one of the most promising quantitative markers of cardiovascular control. Calculation of HRV from the peripheral pulse wave using PPG, called pulse rate variability (PRV), is investigated. The current work has confirmed that the PPG signal could provide basic information about heart rate (HR) and its variability, and highly suggests a good alternative to understanding dynamics pertaining to the autonomic nervous system (ANS) without the use of an electrocardiogram (ECG) device. Hence, PPG measurement has the potential to be readily accepted in ambulatory cardiac monitoring due to its simplicity and comfort. Noncontact PPG (NPPG) is introduced to overcome the current limitations of contact PPG. As a contactless device, NPPG is especially attractive for physiological monitoring in ambulatory units, NICUs, or trauma centres, where attaching electrodes is either inconvenient or unfeasible. In this research, a prototype for noncontact reflection PPG (NRPPG) with a vertical cavity surface emitting laser (VCSEL) as a light source and a high-speed PiN photodiode as a photodetector is developed. The results from physiological experiments suggest that NRPPG is reliable to extract clinically useful information about cardiac condition and function. In summary, recent evidence demonstrates that PPG as a simple noninvasive measurement offers a fruitful avenue for noninvasive cardiovascular monitoring. Key words: Photoplethysmography (PPG), Cardiovascular assessment, Pulse wave contour analysis, Arterial stiffness, Heart rate (HR), Heart rate variability (HRV), Pulse rate variability (PRV), Autonomic nervous system (ANS), Electrocardiogram (ECG).

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.

Le sepsis tardif, défini comme une infection systémique chez les nouveaux nés âgés de plus de 3 jours, survient chez environ 7% à 10% de tous les nouveau-nés et chez plus de 25% des nouveau-nés de très faible poids de naissance qui sont hospitalisés dans les unités de soins intensifs néonatals (USIN). Les apnées et bradycardies (AB) spontanées récurrentes et graves sont parmi les principaux indicateurs précoces cliniques de l'infection systémique chez les prématurés. L'objectif de cette thèse est de déterminer si la variabilité du rythme cardiaque (VRC), la respiration et l'analyse de leurs relations aident au diagnostic de l'infection chez les nouveaux nés prématurés par des moyens non invasifs en USIN. Par conséquent, on a effectué l'analyse Mono-Voie (MV) et Bi-Voies (BV) sur deux groupes sélectionnés de nouveau-nés prématurés: sepsis (S) vs. non-sepsis (NS). (1) Tout d'abord, on a étudié la série RR non seulement par des méthodes de distribution (moy, varn, skew, kurt, med, SpAs), par les méthodes linéaire: le domaine temporel (SD, RMSSD) et dans le domaine fréquentiel (p_VLF, p_LF, p_HF), mais aussi par les méthodes non–linéaires: la théorie du chaos (alphas, alphaF) et la théorie de l'information (AppEn, SamEn, PermEn, Regul). Pour chaque méthode, nous étudions trois tailles de fenêtre 1024/2048/4096, puis nous comparons ces méthodes afin de trouver les meilleures façons de distinguer S de NS. Les résultats montrent que les indices alphaS, alphaF et SamEn sont les paramètres optimaux pour séparer les deux populations. (2) Ensuite, la question du couplage fonctionnel entre la VRC et la respiration nasale est adressée. Des relations linéaires et non-linéaires ont été explorées. Les indices linéaires sont la corrélation (r²), l'indice de la fonction de cohérence (Cohere) et la corrélation temps-fréquence (r2t,f) , tandis que le coefficient de régression non-linéaire (h²) a été utilisé pour analyser des relations non-linéaires. Nous avons calculé les deux directions de couplage pendant l'évaluation de l'indice h2 de régression non-linéaire. Enfin, à partir de l'ensemble du processus d'analyse, il est évident que les trois indices (r2tf_rn_raw_0p2_0p4, h2_rn_raw et h2_nr_raw) sont des moyens complémentaires pour le diagnostic du sepsis de façon non-invasive chez ces patients fragiles. (3) Après, l'étude de faisabilité de la détection du sepsis en USIN est réalisée sur la base des paramètres retenus lors des études MV et BV. Nous avons montré que le test proposé, basé sur la fusion optimale des six indices ci-dessus, conduit à de bonnes performances statistiques. En conclusion, les mesures choisies lors de l'analyse des signaux en MV et BV ont une bonne répétabilité et permettent de mettre en place un test en vue du diagnostic non invasif et précoce du sepsis. Le test proposé peut être utilisé pour fournir une alarme fiable lors de la survenue d'un épisode d'AB tout en exploitant les systèmes de monitoring actuels en USIN. / Late-onset sepsis, defined as a systemic infection in neonates older than 3 days, occurs in approximately 10% of all neonates and in more than 25% of very low birth weight infants who are hospitalized in Neonatal Intensive Care Units (NICU). Recurrent and severe spontaneous apneas and bradycardias (AB) is one of the major clinical early indicators of systemic infection in the premature infant. Various hematological and biochemical markers have been evaluated for this indication but they are invasive procedures that cannot be repeated several times. The objective of this Ph.D dissertation was to determine if heart rate variability (HRV), respiration and the analysis of their relationships help to the diagnosis of infection in premature infants via non-invasive ways in NICU. Therefore, we carried out Mono-Channel (MC) and Bi-Channel (BC) Analysis in two selected groups of premature infants: sepsis (S) vs. non-sepsis (NS). (1) Firstly, we studied the RR series not only by distribution methods (moy, varn, skew, kurt, med, SpAs), by linear methods: time domain (SD, RMSSD) and frequency domain (p_VLF, p_LF, p_HF), but also by non-linear methods: chaos theory (alphaS, alphaF) and information theory (AppEn, SamEn, PermEn, Regul). For each method, we attempt three sizes of window 1024/2048/4096, and then compare these methods in order to find the optimal ways to distinguish S from NS. The results show that alphaS, alphaF and SamEn are optimal parameters to recognize sepsis from the diagnosis of late neonatal infection in premature infants with unusual and recurrent AB. (2) The question about the functional coupling of HRV and nasal respiration is addressed. Linear and non-linear relationships have been explored. Linear indexes were correlation (r²), coherence function (Cohere) and time-frequency index (r2t,f), while a non-linear regression coefficient (h²) was used to analyze non-linear relationships. We calculated two directions during evaluate the index h2 of non-linear regression. Finally, from the entire analysis process, it is obvious that the three indexes (r2tf_rn_raw_0p2_0p4, h2_rn_raw and h2_nr_raw) were complementary ways to diagnosticate sepsis in a non-invasive way, in such delicate patients.(3) Furthermore, feasibility study is carried out on the candidate parameters selected from MC and BC respectively. We discovered that the proposed test based on optimal fusion of 6 features shows good performance with the largest Area Under Curves (AUC) and the least Probability of False Alarm (PFA). As a conclusion, we believe that the selected measures from MC and BC signal analysis have a good repeatability and accuracy to test for the diagnosis of sepsis via non-invasive NICU monitoring system, which can reliably confirm or refute the diagnosis of infection at an early stage.

<p>Sudden unexpected death in epilepsy (SUDEP) is a fatal complication of epilepsy that kills 1̃2 of every 10,000 epileptic patients every year. SUDEP has proven difficult to study because it frequently occurs unobserved and cannot be predicted. What limited clinical data exists suggests that SUDEP occurs as a cardiorespiratory collapse immediately following a seizure. In this work, I explore how a group of autonomic reflexes termed collectively as “oxygen‐conserving reflexes (OCRs)” lead to sudden death when activated during seizures. I also demonstrate multiple physiological parallels between the OCR‐mediated deaths that I report and the clinical data on cases of human SUDEP. Additionally, I explore the neural pathway underlying OCRs, identify the carotid body as a potential target for intervention, and demonstrate the efficacy of electroceutical intervention in reducing the mortality risk of OCR activation during seizures. This work seeks to both offer a neural explanation for SUDEP as well as present a promising target and means for potential intervention.</p>