Human wellbeing, in a large component, relies on the harmony between the body and the mind. Unfortunately, we often miss or ignore important signals from our bodies, and sometimes this can negatively impact our health. Therefore, the use of intelligent systems that grasp such signals and convey them in an intuitive manner to our minds can result in great health benefits. In this Thesis, we introduce a family of multimedia technologies and techniques aimed at realizing such systems. We call them: Ubiquitous Biofeedback Multimedia Systems. Although the notion of clinical biofeedback has been around for years, we introduce the concept of Ubiquitous Biofeedback where the biofeedback operation is given geographical and temporal ubiquity attributes. A Ubiquitous Biofeedback reference model is introduced in the Thesis to provide an abstract structural representation of the various components at play in a typical non-clinical biofeedback environment. Two systems that implement the reference model’s components are presented. These systems implement the concept of Ubiquitous Biofeedback through the introduction of innovative stress management methods. An important component of these systems guides users through a relaxation routine. Therefore, a mathematical model is developed in the goal of personalizing the relaxation process. Its objective is to suggest relaxation techniques to a user during a stressful episode based on her or his preferences, history of what worked well and appropriateness for the context. The mental stress monitoring mechanism built into the Ubiquitous Biofeedback systems presented in this Thesis relies on the measurement of Heart Rate Variability (HRV). Therefore, HRV based methods for tracking mental stress accumulation and acute manifestations during long term monitoring have been devised. Also, since HRV signals can be plagued by artifacts, several algorithms are contributed to the effort of correcting such occurrences.

L'analyse de la Variabilité de la Fréquence Cardiaque est une méthode de mesure non invasive du Système Nerveux Autonome. Cette méthode d'analyse initialement utilisée dans le domaine clinique s'est progressivement installée dans le domaine de l'activité physique pour diverses applications telles que la détection précoce de la fatigue, le calibrage de l'intensité de l'entraînement, détecter les seuils ventilatoires... Les méthodes d'analyse peuvent être utilisées hors contexte de laboratoire, mais nécessitent néanmoins une attention particulière du point de vue méthodologique pour être cohérentes vis-à-vis des concepts mathématiques ou physiologiques qui les régissent. Chaque étape de cette méthode nécessite une rigueur spécifique pour ne pas conduire à une mauvaise interprétation. Ce document détaille le processus depuis la phase de mesure de l'intervalle RR en étudiant notamment la précision des appareils utilisables sur le terrain ou la correction du périodogramme obtenu en proposant différentes méthodes. Ce travail décrit également les indices de l'analyse de la VFC et les différentes limites techniques et conceptuelles. Les différents facteurs et biais influençant l'état du tonus du Système Nerveux Autonome seront décrits pour faciliter la création d'un protocole et l'analyse des indices de la VFC obtenus. / Heart Rate Variability Analysis is a non-invasive method for the evaluation of the Autonomic Nervous System activity. This analytical method initially used for clinical diagnosis progressively installed in the field of physical activity for various applications such as early detection of overreaching, calibration of training intensity, ventilatory threshold determination... These methods can be used outside the laboratory environment, but still require particular attention from a methodological aspect in order to be consistent with mathematical or physiological concepts underlying. Each step of this method requires a specific discipline not to lead to misinterpretation. This document details the process from the RR interval measurement phase including accuracy assessment of the devices used in the field or signal treatment with artifacts correction proposing several methods. This work details index from HRV analysis with their technical and conceptual limitations. External factors mat influence the Autonomic Nervous System are described to facilitate the protocol creation and results interpretation

O objetivo do presente estudo foi verificar a possibilidade de identificação dos dois limiares metabólicos pelo comportamento da VFC. Para isso, 22 voluntários do gênero masculino [74,5 + 7,99kg, 177,0 + 8cm, 23,86 + 1,69 (índice de massa corporal) e 9,10 % de gordura], habituados à prática do ciclismo, realizaram teste ergométrico em bicicleta estacionária com carga inicial de 120W e incrementos de 30W a cada 3min, até a exaustão. Durante todo o teste foram feitos os registros da freqüência cardíaca (FC) e de sua variabilidade (VFC) e ao final de cada carga foram coletados 25µL de sangue para análise da concentração sangüínea de lactato. Aplicou-se um modelo matemático que ajustou a curva da VFC em três retas e o primeiro e segundo limiar de VFC foram identificados nas intersecções entre as retas. Para identificação do primeiro e segundo limiar de lactato, considerou-se as concentrações fixas de 2,0 e 3,5mM, respectivamente. A análise de variância para medidas repetidas indicou não haver diferenças significativas nas cargas em que os limiares de VFC e de lactato foram encontrados, mostrando que a metodologia proposta pode ser promissora. Entretanto a falta de correlação entre as variáveis indica que novos estudos necessitam ser realizados para confirmação desta possibilidade. / The purpose of this study was to verify the possibility of metabolic thresholds identifications through HRV. For that, 22 male volunteers [74,5 + 7,99kg, 177,0 + 8cm, 23,86 + 1,69 (body mass index) e 9,10 % fat], familiarized to cyclism practice, realized a cycloergometer test with initial load of 120W and 30W increases every 3min., until exhaustion. During all test, it was registered heart rate (HR) and its variability (HRV) and, at the end of each load, it was collected 25mL blood for lactate concentration analysis. It was applied a mathematical model to adjust HRV curve in three straight lines and first and second HRV thresholds were identified in intersections among the lines. For the identification of first and second lactate thresholds, it was considered 2,0 and 3,5mM fixed concentrations, respectively. Variance analysis for repeated measures indicated that there were no significant differences between loads in which HRV and lactate thresholds were found, showing that purposed methodology can be promissor. However, the lack of correlation between variables indicate that new studies must be made to confirm that possibility.

Student musicians were recruited to participate in an experimental repeated measures research design study to identify effects of heart rate variability (HRV) biofeedback training and emotional self-regulation techniques, as recommended by HeartMath® Institute, on music performance anxiety (MPA) and music performance. Fourteen students were randomly assigned to a treatment or control group following a 5 minute unaccompanied baseline performance. Treatment group participants received 4-5 HRV training sessions of 30-50 minutes each. Training included bibliotherapy, using the computerized Freeze-Framer® 2.0 interactive training software, instruction in the Freeze-Frame® and Quick Coherence® techniques of emotional regulation, and also use of an emWave® portable heart rate variability training device for home training. Measures included the State-Trait Anxiety Inventory (STAI), Performance Anxiety Inventory (PAI), Flow State Scale (FSS), average heart rate (HR), and heart rate variability (HRV). Quade's rank transformed ANCOVA was used to evaluate treatment and no-treatment group comparisons. Combined MPA scores showed statistical significance at p=.05 level with large effect size of eta2=.320. Individual measurements of trait anxiety showed a small effect size of eta2=.001. State anxiety measurement showed statistical significance at the p=.10 level with a large effect size eta2=.291. FSS showed no statistical or effect size difference. PAI showed no statistical significance and a large effect size eta2=.149. HR showed no statistical significance and a large effect size eta2=.143. HRV showed statistical significance at p=.000 level and a large effect size eta2=.698. This study demonstrated practical/clinical significance of a relatively quick and inexpensive biofeedback training that had large effect at decreasing mental, emotional, and physiological symptoms of MPA for university students.

京都大学 / 0048 / 新制・課程博士 / 博士(社会健康医学) / 甲第22888号 / 社医博第112号 / 新制||社医||11(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 川上 浩司, 教授 今中 雄一, 教授 稲垣 暢也 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(人間・環境学) / 甲第23272号 / 人博第987号 / 新制||人||233(附属図書館) / 2020||人博||987(吉田南総合図書館) / 京都大学大学院人間・環境学研究科共生人間学専攻 / (主査)教授 林 達也, 教授 船曳 康子, 教授 久代 恵介, 教授 森谷 敏夫 / 学位規則第4条第1項該当 / Doctor of Human and Environmental Studies / Kyoto University / DGAM

<p>Restricted and repetitive behavior (RRB) is a core feature of autism spectrum disorder (ASD). Research suggests that the severity of RRB may be influenced by both environmental variables (e.g., absence of sensory stimulation input) and neurophysiological activity within the body (e.g., atypical regulatory capacity of the autonomic nervous system). Substantial research efforts have been devoted to the assessment of factors that influence the occurrence of RRB in individuals with ASD, which have led to the development of assessment methodologies, such as functional analysis, to identify specific contexts in which RRB occurs, and measures of heart rate variability (HRV) to index the level of neurophysiological activity for individuals with ASD.</p><p>However, despite the increasing consensus that the assessment and treatment of RRB require a more comprehensive approach due to the complexity and heterogeneity of the neurodevelopmental disorder, there exists a paucity in research that addresses both the functional behavioral and neurophysiological dimensions of RRB. This study aimed to address this gap by (a) designing and evaluating the effects of an integrated function-based assessment on identification of the functional subtypes of RRB and (b) examining the relationship between RRB and HRV as an indicator of neurophysiological functioning. The study included six participants, ages four to seven, with ASD. A single-case alternating treatments design, with two conditions simulating low- and high-stimulation environments, was used for the assessment of functional subtypes within each participant. Dependent variables included the duration of RRB and HRV. RRB was measured using MOOSES, a multi-option observation system for experimental studies. HRV was measured using wearable technology that collects blood volume pulse. Visual analysis of time series data as well as nonparametric analyses of the dependent variables were conducted to determine the functional subtypes of RRB and the association between HRV and RRB across participants.</p><p>Study results suggest that (a) the integrated assessment is effective in identifying specific functional subtypes of RRB and (b) HRV is positively correlated with the rate of RRB. The findings of this study offer new insights on the understanding of how underlying environmental and neurophysiological mechanisms may influence the occurrence of RRB in ASD. Furthermore, the study provides an integrated assessment model that can be feasibly implemented in applied settings.</p>

This work is focused on fractal dimension utilization for heart rate variability analysis. Both the theory of heart rate variability and the methods of HRV analysis in time domain and using the fractal dimesion are summarized. Short comparsion of time domain and fractal dimension method is presented.

Autonomic control of the heart results in variations in the intervals between heart beats, known as heart rate variability. One of the defining components of autonomic control is the baroreflex, a negative feedback controller that balances heart rate and blood pressure. The baroreflex is under constant command from the branches of the autonomic nervous system. To better understand how the autonomic nervous system commands the baroreflex, a baroreflex reflexogenic animal protocol was carried out. Heart rate variability analysis and baroreflex sensitivity were used to quantify the neural control of the heart. This thesis reconfirmed the existence of sexually dimorphic properties in the baroreflex through the use of heart rate variability analysis and baroreflex sensitivity. It was discovered that there are many caveats to utilizing heart rate variability analysis, which have to be addressed both in the experimental protocol and the signal processing technique. Furthermore, it was suggested that the slope method for quantifying baroreflex sensitivity also has many caveats, and that other baroreflex sensitivity methods are likely more optimal for quantifying sustained activation of the baroreflex. By utilizing various heart rate variability signal processing algorithms to assess autonomic tone in Sprague-Dawley rats during rest and sustained electrical activation of the baroreflex, the null hypothesis was rejected.

Depressive Störungen sind Erkrankungen mit hoher Prävalenz und weitreichenden Beeinträchtigungen für das Leben Betroffener, sie bergen Risiken für Rezidive und Chronifizierung. Eine Vielzahl diagnostischer und therapeutischer Verfahren und Methoden steht zur Verfügung, um depressiven Patienten zu helfen, doch erreicht diese Hilfe längst nicht alle. Die digitale Revolution und der Einzug mobiler Geräte wie Smartphones oder tragbarer Sensorgeräte in den Alltag eröffnen neue Möglichkeiten und Wege sich diesen Herausforderungen für die Behandlung depressiv Erkrankter zu stellen. Der Markt an Apps für das Selbst-Monitoring und das Krankheitsmanagement bei Depression wächst beständig, doch ob und in welchem Umfang Depressive solche Angebote wahrnehmen ist wenig erforscht. Die vorliegende Arbeit zu Präferenzen und Wünschen potentieller Nutzer versucht hier Antworten zu finden. Mobile Systeme aus Smartphones, Apps und tragbaren Sensoren können einen Beitrag zum Krankheitsmanagement bei Depression leisten und so die Versorgung Erkrankter verbessern. Mit Hilfe solcher Geräte und Apps lassen sich subjektive oder objektive Daten messen, verarbeiten, evaluieren und für Selbstmanagement, Diagnose und Therapie nutzbar machen. Kontinuierlich im Lebensalltag erhobene objektive Daten wie Bewegung, Aktivitäten, Schlaf als auch physiologische Parameter wie Hautleitfähigkeit oder Herzaktivität sind von unschätzbarem Wert, um Patienten frühzeitig auf Symptome, Wahrnehmungs- und Verhaltensveränderungen aufmerksam zu machen. Die Untersuchung der Veränderungen in der Herzfrequenz (Heart Rate Varibitly, HRV) und depressiven Symptomen stellt einen wichtigen Ansatz für die Suche nach reliablen Bio-Markern für Depression dar. Um objektiven Bioparametern wie HRV in Zukunft in mobilen Systemen zum Selbst-Monitoring und individuellen Krankheitsmanagement bei Depression einsetzen zu können ist aber ein besseres Verständnis der Zusammenhänge zwischen beiden nötig. Die vorliegende Arbeit versucht, weitere Einsicht in den Zusammenhang zwischen Veränderungen in der HRV und dem Krankheitszustand bei Depression zu liefern.:Einführung S5 Publikationsmanuskript 1 S15 Publikationsmanuskript 2 S23 Zusammenfassung S31 Literaturverzeichnis S32 Appendix S43 Darstellung des eigenen Beitrags S44 Selbstständigkeitserklärung S46 Publikationen und Vorträge S47 Danksagung S48