Recording of heart rate variability (HRV) is a noninvasive and continuous measurement method that allows investigating the autonomic nervous system (ANS) and its reaction to environmental influences. For a precise measurement of HRV data, a carefully chosen study design and environment is required to minimize secondary influences. One major influence to be avoided is movement. However, in the daily routine and for some scientific questions, movement can often not be avoided. If so, a manual or automated method to differentiate between artifacts caused by body movement and the actual psychophysiological effect is needed to ensure the data quality. In this approach, a chest-worn sensor was developed, that measures the heart rate using a single lead ECG and filters the measured change of the HRV caused by movement. Data from an integrated accelerometer is used to detect upper body movements that affect the resting heart rate. The movementcorresponding time stamps are then used to filter the Interbeat Intervals (IBI) accordingly. Functionality and effectiveness of the sensor system have been tested against state-of-the art sports- or clinical devices in varying scenarios. As our test series showed, motion filtering has a decisive effect when motion occurs, two-thirds of all cases showed a significant effect of motion filtering, with small to medium effect sizes for the parameters SD2, SD2/SD1, and SDNN. Thereby, automatic filtering of motion artifacts can help to significantly reduce the need for costly post-processing of distorted data sets. The results show a better data quality of HRV measurement, a method that is commonly used for the investigation of physiological processes in the field of chronic pain, psychology, psychiatry, or sports medicine.

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Hintergrund: Bei der Interaktion zwischen Herz und Psyche wird als ein psychophysiologischer Mechanismus eine Veränderung der Modulationsfähigkeit des autonomen Nervensystems angenommen, die mittels HRV (=heart rate variability) widergespiegelt werden kann. Der Zusammenhang zwischen negativer Befindlichkeit und reduzierter HRV scheint jedoch entgegen häufig publizierten Annahmen nicht konsistent. Außerdem wurde zur zeitlichen Stabilität der HRV-Messungen über eine längere Periode von mehreren Jahren sowie zum Zusammenhang zwischen diastolischer Dysfunktion und HRV bisher noch nicht sehr umfangreich geforscht. Methoden: Es wurden 111 Patienten (60 % M., 70 +/- 17 J.) mit kardiovaskulären Risikofaktoren aus einer Kohortenstudie des Kompetenznetzes Herzinsuffizienz (KNHI) untersucht. Kurzzeit-HRV-Messungen (5 min) wurden in den folgenden drei Phasen durchgeführt: Sechs-Minuten-Gehtest, 6/min Taktatmung und Ruhephase. Zum einen wurde mittels Echokardiographie eine diastolische Dysfunktion bestimmt und den Herzfrequenz- (Hr) und HRV-Werten gegenübergestellt. Zum anderen wurden Selbstbeurteilungsfragebögen zur Befindlichkeit, im Speziellen Depressivität und Angst (HADS), Vitaler Erschöpfung (Maastricht Fragebogen) und gesundheitsbezogener Lebensqualität (SF-36), verwendet und Korrelationen mit den Hr- und HRV-Werten berechnet. Anhand eines Teilkollektivs von 24 Pat. wurden Längsschnittanalysen (Zeitintervall 2-4 J.) zur Hr und HRV durchgeführt. Ergebnisse: Es konnten keine (einheitlich) signifikanten Korrelationen zwischen Befindlichkeit und Hr/HRV festgestellt werden, ebenso nicht für ein Teilpatientenkollektiv ohne Betablockereinnahme. In den Längsschnittanalysen zeigten sich auf Gruppenebene eine relative Stabilität der HRV-Werte und auf individueller Ebene hingegen nur eine geringe bis mäßige Stabilität, und zwar auch bei weitgehend unverändertem kardialem Zustand. Für diese individuellen Veränderungen der HRV-Werte konnte keine Ursache eruiert werden. Hingegen bildete sich bezüglich der Herzfrequenz (Hr) eine deutlich höhere Stabilität im zeitlichen Verlauf ab. Beim Vergleich der HRV-Parameter zwischen zwei Patientengruppen mit und ohne isolierte diastolische Dysfunktion zeigte sich eine nicht signifikant reduzierte HRV bei Patienten mit isolierter diastolischer Dysfunktion. Diskussion: Die Zusammenhänge von Befindlichkeit mit der Hr und der HRV scheinen entgegen häufig publizierten Annahmen nicht konsistent. Die vielen Einflussfaktoren auf die HRV sowie die komplexen Eigenschaften des autonomen Nervensystems stellen eine mögliche Erklärung für die uneinheitlichen Ergebnisse zur HRV dar. In früheren Studien könnte es sich zumindest partiell angesichts jeweils multipler untersuchter Assoziationen um Scheinsignifikanzen handeln. In zukünftigen Studien wäre es sinnvoll bezüglich der HRV strikt zwischen Kurz- und Langzeit-HRV-Messungen und bezüglich der Befindlichkeit zwischen psychischen und körperlichen Symptomen zu unterscheiden. Auch sollte der Einfluss von Medikamenteneinnahmen (herzwirksame Medikamente, Antidepressiva) kontrolliert werden. In den Längsschnittanalysen war bei einer Gruppengröße von nur 24 Patienten die statistische Power für weiter gehende Analysen unzureichend. Der Zusammenhang zwischen diastolischer Dysfunktion und HRV wurde bisher noch nicht sehr umfangreich erforscht, weshalb dieses Ergebnis einen interessanten weiteren Baustein in der aktuellen Forschung darstellt.

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).

Einleitung: Es wird angenommen, dass die zyklusbedingten, hormonellen Änderungen die vegetative Ansteuerung des Herzens bei normotensiven Frauen beeinflussen. Die Herzfrequenzvariabilität (HRV) stellt einen der am häufigsten untersuchten, nicht-invasiven Parameter des Herz-Kreislauf-Systems dar. Deshalb war es das Ziel dieser Studie, den Verlauf der HRV Parameter bei ausdauertrainierten als auch untrainierten normotensiven Frauen in Abhängigkeit vom Menstruationszyklus zu untersuchen. Methode: Normotensive, untrainierte als auch trainierte Frauen nahmen an der Studie teil. Die Athletinnen absolvierten individuell abgestimmte Trainingspläne (>5h/Woche) während der Studie. Die HRV Messungen wurden in den folgenden fünf Zyklusphasen aufgezeichnet: In der Menstruation (M), der Mitte der Follikel- (MidF), der Ovulations- (O), der Mitte der Luteal- (MidL) und der Pre-Menstruationsphase (PreM). Die Basaltemperatur als auch die Hormonanalysen des Luteinisierenden (LH) und des Follikelstimulierenden Hormons (FSH), des β-17 Östrogens (E2) und des Progesterons (P) dienten der Verifizierung der Zyklusphasen. Die HRV Messungen wurden bei Spontanatmung im Liegen (20 min) wie auch während eines Orthosthase Tests aufgezeichnet. Parameter der Zeit als auch der Frequenzdomäne für Kurzzeitmessungen wurden ausgewertet. Resultate: Alle Frauen hatten einen normotensiven Menstruationszyklus mit typischen hormonellen Schwankungen und einem signifikanten Verlauf (p / Introduction: The autonomic control of the heart is assumed to be affected by endogenous hormonal fluctuations in normal ovulatory females. Analyzing heart rate variability (HRV) had become a tool for the noninvasive measurement of cardiac autonomic control. The purpose of the present study was to investigate the course of the HRV parameters in moderately active as well as in long time endurance trained women during the menstrual cycle. Methods: Normal ovulatory females, untrained and trained were enrolled. Female athletes were involved in individually different training patterns (>5h/week) during the study. HRV recordings were obtained during five different menstrual cycle phases: menstruation (M), middle of follicular (MidF), ovulation (O), middle of luteal (MidL) and pre menstruation phase (PreM). Phases were verified by basal body temperature and analysis of luteinizing hormone (LH), follicular stimulation hormone (FSH), β-17 estrogen (E2) and progesterone (P). HRV measurements took place at subjects’ spontaneous breathing frequency in supine position (20 min) as well as during an orthostatic test. Parameters of short-term recording were calculated in time and frequency domain. Results: All women had normal ovulatory menstrual cycles including typical endogenous hormonal fluctuations; levels of LH, FSH, E2 and P were significantly different (p

The European natural gas market is characterised by higher demand than available supply from own resources. Therefore Europe is a gas net-importing region. The costs of potential problems or disruptions establish the need for an environment which stimulates sufficient investments in transmission line capacities. We examine the effects of the introduction of the recently developed Hogan, Rosellón and Vogelsang (HRV) incentive mechanism into the European natural gas market. In the simulations with GAMS we can confirm all results expected from theory. The validity of these simulation results is confirmed in a structural analysis, which comprised the variation of different exogenous input parameters. Therefore we conclude that the HRV incentive mechanism as a regulatory regime for the European natural gas market would be an advisable alternative, which should be considered in future discussions. (author's abstract) / Series: Working Papers / Research Institute for Regulatory Economics

Fundação de Amparo a Pesquisa do Estado de Alagoas / Estudos recentes sugerem que a técnica de estimulação elétrica transcraniana (ETCC) pode reduzir a vontade subjetiva de comer e desejo pelo alimento, mostrando-se uma possível ferramenta terapêutica no combate à obesidade. O exercício físico suscita efeitos positivos sobre a manutenção e perda do peso corporal total, balanço energético, regulação do apetite e neuroplasticidade, oxigenação e vascularização cerebral. Desse modo, o objetivo do presente estudo foi verificar o efeito da ETCC, associada à prática de exercício físico, sobre a variabilidade da freqüência cardíaca (VFC) e sensações subjetivas do apetite em humanos obesos. Participaram do estudo nove indivíduos de ambos os sexos. Os sujeitos foram submetidos a duas etapas de procedimentos experimentais. A primeira consistiu na realização de um teste cardiopulmonar máximo no cicloergômetro com protocolo do tipo rampa, a fim de determinar sua capacidade cardiorrespiratória (VO2MAX; FCMAX; CargaMAX). Na segunda etapa, os sujeitos realizaram duas sessões não consecutivas de testes, em que inicialmente permaneceram sentados por 10min, receberam ETCC anódica ou placebo (2mA por 20min), em ordem randomizada e, logo após, executaram sessões isocalóricas (~200kcal) a 70%VO2MAX. Em seguida, permaneceram em recuperação sentados em repouso por 30 minutos. Em todo o protocolo, escalas visuais analógicas para avaliação das sensações subjetivas de apetite, bem como a VFC, foram registradas. Os resultados mostraram que, para os escores médios das sensações de saciedade na condição de ETCC anódica, houve diminuição significativa entre os momentos 30 PÓS EXERCÍCIO vs. todos os momentos analisados (P<0.05). Houve aumento da sensação de fome, em ambas condições de ETCC, entre os momentos 30 PÓS EXERCÍCIO vs. PÓS EXERCÍCIO. No entanto, houve diminuição do desejo pelo alimento após a ETCC anódica (PRÉ ETCC vs. PÓS ETCC; p=0.04), mas não quando os indivíduos receberam ETCC placebo. Quando se associou a ETCC com o exercício, uma diminuição ainda maior foi evidenciada (PRÉ ETCC vs. PÓS EXERCÍCIO; p=0.05). Quanto à VFC, a variável low frequency (LFLOG) demonstrou, em todos os momentos e condições analisados, semelhança em seu comportamento. Por outro lado, as variáveis high frequency (HFLOG) e balanço simpatovagal (LF/HFLOG), apresentaram aumento e diminuição significativas, respectivamente, entre as condições analisadas (placebo e anódica) após a realização da sessão de exercício. Um maior HF e menor LF/HF foram mantidos até o trigésimo minuto de recuperação. Portanto, pode-se concluir que a aplicação da ETCC anódica associada à prática de exercício físico não foi capaz de modificar as respostas hedônicas de fome e saciedade. Porém, a ETCC foi capaz de diminuir o desejo pelo alimento, o que foi potencializado pela associação com o exercício físico. Por outro lado, a ETCC foi capaz de alterar o comportamento do sistema nervoso autonômico cardíaco, propiciando uma maior modulação da atividade parassimpática e diminuição no balanço simpatovagal durante todo o período de recuperação após exercício aeróbio.

This thesis deals with evaluation EKG in terms of classification rhythm and analysis HRV. In theoretic part of work are described basics of heart physiology and its usual pathology, basics of electrocardiography, evaluation EKG and standard methods of HRV evaluation. In practical part are described algorithms used in created application. Mainly describes technique of rhythm evaluation, ectopic rhythms and delineation error elimination, data preparing for HRV evaluation, drift removal from DES and HRV evaluation methods. Created program was tested on CSE and MIT- BIH database records. For lack of suitable data and absence of tested data, it wasn’t possible to test all the classification rules of used algorithms. Tested part of program appears reliable and functional.

As the world population ages, the healthcare system is facing new challenges in treating more patients at a lower cost than today. One trend in addressing this problem is to increase the opportunities of in-home care. To achieve this there is a need for safe and cost-effective monitoring systems. Biosignal PI is an ongoing open-source project created to develop a flexible and affordable platform for development of stand-alone devices able to measure and process physiological signals. This master thesis project, performed at the department of Medical Sensors, Signals and System at the School of Technology and Health, aimed at further develop the Biosignal PI software by constructing a new flexible software framework architecture that could be used for measurement and processing of different types of biosignals. The project also aimed at implementing features for Heart Rate Variability(HRV) Analysis in the Biosignal PI software as well as developing a graphical user interface(GUI) for the Raspberry PI hardware module PiFace Control and Display. The project developed a new flexible abstract software framework for the Biosignal PI. The new framework was constructed to abstract all hardware specifics into smaller interchangeable modules, with the idea of the modules being independent in handling their specific task making it possible to make changes in the Biosignal PI software without having to rewrite all of the core. The new developed Biosignal PI software framework was implemented into the existing hardware setup consisting of an Raspberry PI, a small and affordable single-board computer, connected to ADAS1000, a low power analog front end capable of recording an Electrocardiography(ECG). To control the Biosignal PI software two different GUIs were implemented. One GUI extending the original software GUI with the added feature of making it able to perform HRV-Analysis on the Raspberry PI. This GUI requires a mouse and computer screen to function. To be able to control the Biosignal PI without mouse the project also created a GUI for the PiFace Control and Display. The PiFace GUI enables the user to collect and store ECG signals without the need of an big computer screen, increasing the mobility of the Biosignal PI device.   To help with the development process and also to make the project more compliant with the Medical Device Directive a couple of development tools were implemented such as a CMake build system, integrating the project with the Googletest testing framework for automated testing and the implementation of the document generator software Doxygen to be able to create an Software Documentation.    The Biosignal PI software developed in this thesis is available through Github at https://github.com/biosignalpi/Version-A1-Rapsberry-PI / Allt eftersom världens befolkning åldras, ställs sjukvården inför nya utmaningar i att behandla fler patienter till en lägre kostnad än idag. En trend för att lösa detta problem är att utöka möjligheterna till vård i hemmet.För att kunna göra detta finns det ett ökande behov av säkra och kostnadseffektiva patientövervakningssystem. Biosignal PI är ett pågående projekt med öppen källkod som skapats för att utveckla en flexibel och prisvärd plattform för utveckling av fristående enheter som kan mäta och bearbeta olika fysiologiska signaler. Detta examensarbete genomfördes vid institutionen för medicinska sensorer, signaler och system vid Skolan för Teknik och Hälsa. Projektet syftade till att vidareutveckla den befintliga mjukvaran för Biosignal PI genom att skapa ett nytt flexibelt mjukvaruramverk som kan användas för mätning och bearbetning av olika typer av biosignaler.Projektet syftade också till att utvidga mjukvaran och lägga till funktioner för att kunna genomföra hjärtfrekvensvariabilitets(HRV) analys i Biosignal PIs mjukvara, samt att utveckla ett grafiskt användargränssnitt(GUI) för hårdvarumodulen PiFace Control and Display. Projektet har utvecklat ett nytt flexibelt mjukvaruramverk för Biosignal PI. Det nya ramverket konstruerades för att abstrahera alla hårdvaruspecifika delar in i mindre utbytbara moduler, med tanken att modulerna ska vara oberoende i hur de hanterar sin specifika uppgift. På så sätt ska det vara möjligt att göra ändringar i Biosignal PIs programvara utan att behöva skriva om hela mjukvaran.Det nyutvecklade Biosignal PI ramverket implementerades i det befintliga hårdvaru systemet, som består av en Raspberry PI, liten och prisvärd enkortsdator, ansluten till ADAS1000, en analog hårdvarumodul med möjlighet att registrera ett elektrokardiografi(EKG/ECG). För att kontrollera Biosignal PI programmet har två olika grafiska användargränssnitt skapats.Det ena gränssnitt är en utvidgning av original programvaran med tillagd funktionalitet för att kunna göra HRV-Analys på Raspberry PI, detta gränssnitt kräver dock mus och dataskärm för att kunna användas.För att kunna styra Biosignal PI utan mus och skärm skapades det även ett gränssnitt för PiFace Control and Display. PiFace gränssnittet gör det möjligt för användaren att samla in och lagra EKG-signaler utan att behöva en stor datorskärm, på så sätt kan man öka Biosignal PI systemets mobilitet. För att underlätta utvecklingsprocessen, samt göra projektet mer förenligt med det medicintekniska regelverket, har ett par utvecklingsverktyg integrerats till Biosignal PI projektet såsom CMake för kontroll av kompileringsprocessen, test ramverket Googletest för automatiserad testning samt integrering med dokumentations generatorn Doxygen för att kunna skapa en dokumentation av mjukvaran.

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