Dissertations / Theses on the topic 'Biosignal monitoring'

In order to handle the increasing costs of healthcare more of the care and monitoring will take place in the patient’s home. It is therefore desirable to develop smaller and portable systems that can record important biosignals such as the electrical activity of the heart in the form of an ECG. This project is a continuation on a previous project that developed a shield that can be connected to the GPIO pins of a Raspberry Pi, a credit-card sized computer. The shield contains an ADAS1000, a low power and compact device that can record the electrical activity of the heart along with respiration. The aim of this project was to develop an application that can run on the Raspberry Pi in order to display the captured data from the shield on a screen along with storing the data for further processing. The project was successful in the way that the requirements for the software have been fulfilled.
För att hantera den ökande kostnaden för hälso- och sjukvård kommer en större del av övervakning samt vård att ske i patientens hem. Det kommer därför att vara önskvärt att utveckla mindre system som är lättare att hantera än de större traditionella apparaterna för att samla in vanliga biosignaler som exempelvis ett EKG. Detta projekt är en fortsättning på ett tidigare projekt vars syfte var att framställa en ”sköld” som kan kopplas ihop med en Raspberry Pi via dess GPIO pinnar. Det föregående projektet var lyckat och en sköld innehållande en ADAS1000 som kan samla in bl.a. ett EKG samt andningen framställdes. Syftet med detta projekt var att utveckla en applikation som kan köras på en Raspberry Pi och på så sätt visa den data som samlas in från skölden på en skärm. Det skulle även vara möjligt att spara insamlad data för senare användning. Projektet resulterade i en applikation som uppfyllde dessa krav.

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering
Long-term biosignals acquisitions are an important source of information about the patients’state and its evolution. However, long-term biosignals monitoring involves managing extremely large datasets, which makes signal visualization and processing a complex task. To overcome these problems, a new data structure to manage long-term biosignals was developed. Based on this new data structure, dedicated tools for long-term biosignals visualization and processing were implemented. A multilevel visualization tool for any type of biosignals, based on subsampling is presented, focused on four representative signal parameters (mean, maximum, minimum and standard deviation error). The visualization tool enables an overview of the entire signal and a more detailed visualization in specific parts which we want to highlight, allowing an user friendly interaction that leads to an easier signal exploring. The ”map” and ”reduce” concept is also exposed for long-term biosignal processing. A processing tool (ECG peak detection) was adapted for long-term biosignals. In order to test the developed algorithm, long-term biosignals acquisitions (approximately 8 hours each) were carried out. The visualization tool has proven to be faster than the standard methods, allowing a fast navigation over the different visualization levels of biosignals. Regarding the developed processing algorithm, it detected the peaks of long-term ECG signals with fewer time consuming than the nonparalell processing algorithm. The non-specific characteristics of the new data structure, visualization tool and the speed improvement in signal processing introduced by these algorithms makes them powerful tools for long-term biosignals visualization and processing.

京都大学
0048
新制・課程博士
博士(情報学)
甲第22578号
情博第715号
新制||情||123(附属図書館)
京都大学大学院情報学研究科社会情報学専攻
(主査)教授 黒田 知宏, 教授 守屋 和幸, 教授 吉川 正俊
学位規則第4条第1項該当
Doctor of Informatics
Kyoto University
DFAM

Die langfristigen Folgen von psychischer Fehlbeanspruchung stellen ein beträchtliches Problem unserer modernen Gesellschaft dar. Zur Identifizierung derartiger Fehlbelastungen während der Mensch-Maschine-Interaktion (MMI) kann die objektive, kontinuierliche Messung der psychischen Beanspruchung einen wesentlichen Beitrag leisten. Neueste Entwicklungen in der Sensortechnologie und der algorithmischen Methodenentwicklung auf Basis von KI liefern die Grundlagen zu ihrer messtechnischen Bestimmung. Vorarbeiten zur Entwicklung einer Methode zur neuronalen Beanspruchungsdiagnostik sind bereits erfolgt (Radüntz, 2017). Eine praxisrelevante Nutzung dieser Ergebnisse ist erfolgsversprechend, wenn die Methode mit Wearables kombiniert werden kann. Gleichzeitig sind die Evaluation und bedingungsbezogene Reliabilitätsprüfung der entwickelten Methode zur neuronalen Beanspruchungsdiagnostik in realitätsnahen Umgebungen erforderlich. Im Rahmen von experimentellen Untersuchungen der Gebrauchstauglichkeit von kommerziellen EEG-Registrierungssystemen für den mobilen Feldeinsatz wird die darauf basierende Systemauswahl für die MMI-Praxis getroffen. Die Untersuchungen zur Validierung der kontinuierlichen Methode zur Beanspruchungsdetektion erfolgt am Beispiel des Fluglotsenarbeitsplatzes beim simulierten „Arrival Management“.
The long-term negative consequences of inappropriate mental workload on employee health constitute a serious problem for a digitalized society. Continuous, objective assessment of mental workload can provide an essential contribution to the identification of such improper load. Recent improvements in sensor technology and algorithmic methods for biosignal processing are the basis for the quantitative determination of mental workload. Neuronal workload measurement has the advantage that workload registration is located directly there where human information processing takes place, namely the brain. Preliminary studies for the development of a method for neuronal workload registration by use of the electroencephalogram (EEG) have already been carried out [Rad16, Rad17]. For the field use of these findings, the mental workload assess- ment on the basis of the EEG must be evaluated and its reliability examined with respect to several conditions in realistic environments. A further essential require-ment is that the method can be combined with the innovative technologies of gel free EEG registration and wireless signal transmission. Hence, the presented papers include two investigations. Main subject of the first investigation are experimental studies on the usability of commercially-oriented EEG systems for mobile field use and system selection for the future work. Main subject of the second investigation is the evaluation of the continuous method for neuronal mental workload registration in the field. Thereby, a challenging application was used, namely the arrival management of aircraft. The simulation of the air traffic control environment allows the realisation of realistic conditions with different levels of task load. Furthermore, the work is well contextualized in a domain which is very sensible to human-factors research.

Wearables for health monitoring are rapidly advancing as evidenced by the number of wearable products on the market. More recently, the US Food and Drug Administration approved the Apple Watch for heart monitoring, indicating that wearables are going to be a part of our lives sooner than expected. However, wearables are still based on rigid, conventional electronic materials and fabrication procedures. The use of flexible conducting materials fabricated on flexible substrates allows for more comprehensive health monitoring because of the seamless integration and conformability of such devices with the human skin. Many materials can be used to fabricate flexible electronics such as thin metals, liquid metals, conducting polymers, and 1D and 2D materials. Ti3C2 MXene is a promising 2D material that shows flexibility as well as desirable electronic properties. Ti3C2 MXene is easily processable in aqueous solutions and can be an excellent functional ink for inkjet printing. Here we report the fabrication and the properties of Ti3C2 MXene films inkjet-printed from aqueous dispersions with a nonionic surfactant. The films are uniform and formed with only a few layers on glass and tattoo paper. The MXene films printed on tattoo are used to record ECG signals with comparable signal-to-noise ratio to commercial Ag/AgCl electrodes despite the absence of gels to lower skin-contact impedance. Due to their high charge storage capacity and mixed (ionic and electronic) conductivity, inkjet-printed MXene films open up a new avenue for applications beyond health monitoring.

This research work draws on previous experimental research and aims to further develop and refine a biosignal measurement device that will allow the capture of a swimmer’s biosignals via Bluetooth. It also encompasses the construction of a dashboard that will allow a swimming instructor or coach to monitor and improve the athletes’ swimming practice.
O âmbito deste trabalho incide no desenvolvimento/criação de um dispositivo de medição de biosinais (acelerometria, eletromiografia e eletrocardiografia) para que através de uma conexão via Bluetooth seja feita a captura destes valores num nadador. Abrange ainda o desenvolvimento de um dashboard que permite ao treinador acompanhar e melhorar os treinos de um atleta.

abstract: The recording of biosignals enables physicians to correctly diagnose diseases and prescribe treatment. Existing wireless systems failed to effectively replace the conventional wired methods due to their large sizes, high power consumption, and the need to replace batteries. This thesis aims to alleviate these issues by presenting a series of wireless fully-passive sensors for the acquisition of biosignals: including neuropotential, biopotential, intracranial pressure (ICP), in addition to a stimulator for the pacing of engineered cardiac cells. In contrast to existing wireless biosignal recording systems, the proposed wireless sensors do not contain batteries or high-power electronics such as amplifiers or digital circuitries. Instead, the RFID tag-like sensors utilize a unique radiofrequency (RF) backscattering mechanism to enable wireless and battery-free telemetry of biosignals with extremely low power consumption. This characteristic minimizes the risk of heat-induced tissue damage and avoids the need to use any transcranial/transcutaneous wires, and thus significantly enhances long-term safety and reliability. For neuropotential recording, a small (9mm x 8mm), biocompatible, and flexible wireless recorder is developed and verified by in vivo acquisition of two types of neural signals, the somatosensory evoked potential (SSEP) and interictal epileptic discharges (IEDs). For wireless multichannel neural recording, a novel time-multiplexed multichannel recording method based on an inductor-capacitor delay circuit is presented and tested, realizing simultaneous wireless recording from 11 channels in a completely passive manner. For biopotential recording, a wearable and flexible wireless sensor is developed, achieving real-time wireless acquisition of ECG, EMG, and EOG signals. For ICP monitoring, a very small (5mm x 4mm) wireless ICP sensor is designed and verified both in vitro through a benchtop setup and in vivo through real-time ICP recording in rats. Finally, for cardiac cell stimulation, a flexible wireless passive stimulator, capable of delivering stimulation current as high as 60 mA, is developed, demonstrating successful control over the contraction of engineered cardiac cells. The studies conducted in this thesis provide information and guidance for future translation of wireless fully-passive telemetry methods into actual clinical application, especially in the field of implantable and wearable electronics.
Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2020

Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.

The execution of experimental studies with the retrieval of fisiological data of groups of participants usually makes the researchers use proprietary equipment, with little to no possibility of leaving the laboratory or adapt the capture protocols. The use of mobile devices in coupled with a variety of selected sensors can provide a low cost, portable configuration for the collection of physiological data for investigation. Monipart is a web application that takes advantage of na alredy existing solution for the capture of bio-signals based on mobile devices and improves it by implementing a web module for the parameterization and monitoring of experiments in real-time. The application also offers a friendly environment for the researcher to manage their studies as well as further analisys of the retrieved data. In view of that, the application communicates with a pre-existing collection solution based in mobile devices that uses messages (MQTT) to control and monitor the experiments. The exploration of the collected information is supported by a database designed to handle time-series for added flexibility in the data processing. The application can be easily extended via plugins that can include new functionalities (i.e. specialized viewers for certain types of data) that may be developed by external entities to the project. With this application, the researchers now can plan and follow experiments via a web interface as well as have immediate access to the data.
A realização de estudos experimentais com recolha de dados fisiológicos de grupos de participantes obriga frequentemente os investigadores a usar equipamentos proprietários, com poucas possibilidades de sair do laboratório ou adaptar os protocolos de recolha. A utilização de dispositivos móveis, em conjunto com sensores selecionados, pode proporcionar uma configuração de baixo custo e portátil para a recolha de dados fisiológicos, para investigação. O Monipart é uma aplicação web que tira partido de uma solução já existente para a captura de biossinais baseada em dispositivos móveis e que a evolui no sentido de implementar um módulo web para a configuração e monitorização de experiências em tempo real. A aplicação também oferece um ambiente amigável para os investigadores fazerem a gestão dos seus estudos bem como a posterior análise da informação recolhida. Para isso, a aplicação comunica com a solução de recolha preexistente, baseada em dispositivos móveis, recorrendo a mensagens (MQTT), para controlo e monitorização das experiências. A exploração dos dados obtidos é suportada pelo uso de uma base de dados orientada a séries temporais, para flexibilidade adicional no processamento de dados. A aplicação desenvolvida permite uma fácil extensão via plugins para incluir novas funcionalidades (e.g.: visualizadores especializados para certos tipos de dados) que podem ser desenvolvidas por entidades externas ao projeto. Com este trabalho, os investigadores podem agora planear e acompanhar experiências através de uma interface web, bem como ter um acesso imediato aos dados.
Mestrado em Engenharia Informática

Trabalho de Projeto do Mestrado Integrado em Engenharia Biomédica apresentado à Faculdade de Ciências e Tecnologia
This dissertation aimed to study and evaluate the estimation of Blood pressure, on a continuous and non-invasive basis, to be deployed during surgeries, relying only on extracted features from non-invasive modalities (Photoplethysmography and Electrocardiography). From the Photoplethysmography, features were extracted by means of its pulsatile and non-pulsatile components, as well as the corresponding second derivative of the pulsatile component. Namely, the Pulsatile component amplitude, Non-pulsatile component amplitude, Ratio of pulsatile and non-pulsatile amplitudes, Dicrotic notch amplitude, Reflection index, Heart beat interval and the Ratio between amplitudes of the second derivative waveform of Photoplethysmography (“b” and “a” waves). Two different implementations of Pulse arrival time were also computed (according to [65] and [17]) and included in this feature pool which in its turn required the consideration of Electrocardiography in this experimentation. The nine extracted features from these two biosignals had their relationship quantified in terms of the correlation performance with four different Blood pressure features: Systolic blood pressure, Diastolic blood pressure, Pulse pressure and Mean arterial pressure. This analysis highlighted the strong correlations of the Ratio of “b” and “a” waves amplitudes and Pulse arrival time (computed from [17]) with Systolic, Diastolic and Mean arterial pressures for all patients. The spearman correlation coefficients varied between 71% and 90% for the former and between 75% and 91% for the latter feature. In contrast, Heart beat interval only showed negligible correlations with the blood pressure features. Spearman correlation coefficients varied between 4% and 58%.Furthermore, the Blood Pressure features in investigation were separately estimated from the combination of the nine features previously mentioned through multiple linear regression modelling, for each patient, and confirmed according to a leave-one-out cross validation. Different models were proposed and experimented in order to evaluate the contribution of four major aspects on the estimated Blood pressure features. The influence of the inclusion of Pulse arrival time (and consequent usage of extra electrocardiogram sensors) and Photoplethysmography’s non-pulsatile component in the arranged models was taken into account. The biosignals were also segmented and had the spearman correlation coefficient calculated, for each segment, between the estimated Blood pressure features and the pooled features from Electrocardiography and Photoplethysmography. The segments associated to (very) strong correlations (spearman correlation coefficients above 70%) were assembled to define the training group in the cross validation. This enabled to test the influence, in the built models, of the inclusion of strongly correlated segments of the biosignals, instead of the entire biosignals. At last, the influence of the implemented calibration procedure both in the beginning of the surgery (through the computation of a recursive least squares method) and during the surgery (including a derivation of Pulse arrival time) was studied. These models were validated within British Hypertension Society and Association for the Advancement of Medical Instrumentation protocols, which are considered to be the standards on the evaluation of blood pressure automated measuring systems. These protocols depend on the distribution of the differences between the real and the estimated Blood pressure values. The measuring system to be accepted within the British Hypertension Society protocol requires that at least 50%, 75% and 90% of the mentioned differences to be within 5, 10 and 15 mmHg, respectively, while the Association for the Advancement of Medical Instrumentation demands the standard deviation and the mean of the differences to be lower than or equal to 8 mmHg and 5 mmHg, respectively. The best performing model according to the implied standard protocols didn’t require neither extra electrocardiogram sensors nor the implemented calibrations. This corroborates the key role of the included range of Photoplethysmography features. Pulse pressure estimation was the only to fulfill the two protocols’ requirements while Diastolic blood pressure and Mean arterial pressure estimations only met British Hypertension Society recommendations. At last, Systolic blood pressure estimation didn’t meet neither British Hypertension Society nor Association for the Advancement of Medical Instrumentation protocols. Overall, the strong relationship between blood pressure and Photoplethysmography was corroborated for this data. Larger heterogeneous population would have to be tested in order to be presented reliable conclusions on the continuous and non-invasive Blood pressure estimation solely from Photoplethysmography.
Esta dissertação pretendeu estudar e avaliar a pressão sanguínea estimada, de uma forma continua e não invasiva, a ser implantada durante cirurgias, dependendo apenas de parâmetros extraídos de modalidades não-invasivas (Fotopletismografia e Eletrocardiografia). Da Fotopletismografia, parâmetros foram extraídos através dos seus componentes pulsáteis e não-pulsáteis, assim como a segunda derivada correspondente da componente pulsátil. Nomeadamente, a Amplitude da componente pulsátil, a Amplitude da componente não-pulsátil, o ratio entre as amplitudes pulsáteis e não-pulsáteis, a Amplitude do nó dicrótico, o Índice de reflexão, o Intervalo de batimento cardíaco e o ratio entre as amplitudes da forma de onda da segunda derivada da Fotopletismografia (ondas “a” e “b”). Duas implementações diferentes do Tempo de chegada do pulso foram também calculadas (de acordo com [65] e [17]) e incluídas neste conjunto de parâmetros, o que por sua vez exigiu a consideração da Eletrocardiografia nesta experimentação. A relação entre os nove parâmetros extraídos destes dois biosinais foi quantificada em termos do desempenho da correlação com quatro outros aspetos diferentes da Pressão sanguínea: a Pressão sanguínea sistólica, a Pressão sanguínea diastólica, a Pressão do pulso e a Pressão arterial média. Esta análise destacou a forte correlação entre o ratio das amplitudes das ondas “a” e “b” e o Tempo de chegada do pulso (calculado em [17]), e as Pressões sistólica, diastólica e arterial média, para todos os pacientes. Os coeficientes da correlação spearman variaram entre 71% e 90% para o parâmetro anterior e entre 75% e 91% para o posterior. Por outro lado, o Intervalo do batimento cardíaco mostrou apenas correlações negligenciáveis com os parâmetros da pressão sanguínea. Os coeficientes da correlação de spearman variaram entre 4% e 58%. Além disso, os aspetos sob investigação da Pressão sanguínea foram estimados à parte da combinação dos nove parâmetros previamente mencionados, através da modelação de regressões lineares múltiplas, para cada paciente, e confirmados de acordo com a validação cruzada “leave-one-out”. Diferentes modelos foram propostos e experienciados de modo a avaliar a contribuição de quatro grandes aspetos para os parâmetros da pressão sanguínea estimada. A influência da inclusão do Tempo de chegada do pulso ( e consequente utilização de sensores extra de Eletrocardiograma) e da Componente não-pulsátil da Fotopletismografia nos modelos definidos foi tida em consideração. Os biosinais foram também segmentados e calculou-se, para cada segmento, o coeficiente da correlação de spearman entre os parâmetros da pressão sanguínea estimada e os parâmetros extraídos da Eletrocardiografia e da Fotopletismografia. Os segmentos associados a correlações (muito) fortes (coeficiente da correlação de spearman acima dos 70% ) foram reunidos para definir o grupo de treino da validação cruzada. Isto permitiu testar a influência, nos modelos construídos, da inclusão de segmentos de biosinais fortemente correlacionados ao invés de biosinais na sua totalidade. Por fim, a influência do processo de calibração implementado, tanto no início da cirurgia (através da computação de um método recursivo dos mínimos quadrados), como durante a mesma (incluindo uma derivação do Tempo de chegada de pulso) foi estudada. Estes modelos foram validados à luz dos protocolos da British Hypertension Society e da Association for the Advancement of Medical Instrumentation, que são considerados os sistemas de medição automatizados standard na avaliação da pressão sanguínea. Estes protocolos dependem da distribuição das diferenças entre o valor real e o estimado da pressão sanguínea. O sistema de medição aceite no protocolo da British Hypertension Society requer que pelo menos 50%, 75% e 90% das diferenças mencionadas estejam entre 5, 10 e 15 mmHg, respetivamente, enquanto que a Association for the Advancement of Medical Instrumentation exige que o desvio-padrão e média das diferenças sejam iguais ou inferiores a 8 mmHg e 5 mmHg, respetivamente.O modelo com melhor desempenho e de acordo com os protocolos implicados não exigiu nem sensores de eletrocardiograma extras nem as calibrações implementadas. Isto corrobora o papel fundamental dos parâmetros da Fotopletismografia incluídos. A estimativa da Pressão do pulso foi a única a satisfazer as exigências de ambos os protocolos, enquanto que as estimativas da Pressão sanguínea diastólica e da Pressão arterial média apenas preencheram as exigidas pela British Hypertension Society. Por fim, a estimativa da Pressão sanguínea sistólica não preencheu nenhum dos requisitos dos protocolos. De um modo geral, a forte relação entre Pressão sanguínea e Fotopletismografia foi corroborada pelos dados obtidos. Maiores populações heterógenas teriam de ser testadas de modo a poderem ser apresentadas conclusões de maior fiabilidade.
Outro - Sponsored internship by Philips Electronics Nederlands B.V. from the 11th of February to the 18th of June (4 months) in Philips "Research and development" department in the High tech campus in Eindhoven

Physical activity is a constant in life, prolonging since the primordial times until now as an intrinsic element of human condition, though his character have suffered a transmutation, going from a need, by the predatory nature of the human being, for an option in escaping sedentary habits of contemporary society. Despite the enormous benefits of sports practice, there are also some negative consequences associated, namely the emergence of muscular injuries provided by the installation of fatigue, due to an overload on time or in the intensity of training. The consequences of an injury are drastic, conditioning the quotidian of the injured and carrying high costs for the health system, establishing this problem as the starting point of the present work. Although investigations on this subject have recently appeared, yet is not common to find commercial solutions for evaluating fatigue and with the capability of warning the user about the risk of injury. In order to avoid the fatigue consequences, is proposed the implementation of a computational system for physiological signal processing - Electromyographic (EMG) and Electrocardiographic (ECG) - extracting multiple indexes with informative potential at fatigue level. There is provided an automatic evaluation of the state of fatigue assured by the definition of a Global Fatigue Index that synthesises information from distinct individual fatigue indexes and implementation of a Classification System, with the capability of giving to the user the indication if the physical activity is originating the approximation or deviation from fatigue state. The computer system was built for a future integration as a plugin on a signal acquisition software. This framework is a specialized tool for acquiring and processing of the physiological signals collected in equipments such as bitalino and biosignalsplux, being directed to the practice of indoor cycling.