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Introduction: The use of cardiopulmonary bypass (CBP; also known as a heart-lung machine) in newborns with complex congenital heart defects may result in brain damage. Magnetic resonance imaging (MRI) assessments cannot be performed safely because the metal components used to construct CBP devices may elicit adverse effects on patients when they are placed in a magnetic field. Thus, this project aimed to develop a prototype MR-conditional circulatory support system that could be used to perform cerebral perfusion studies in animal models. Methods: The circulatory support device includes a roller pump with two rollers. The ferromagnetic and most of the metal components of the roller pump were modified or replaced, and the drive was exchanged by an air-pressure motor. All materials used to develop the prototype device were tested in the magnetic field according to the American Society for Testing and Materials (ASTM) Standard F2503-13. The technical performance parameters, including runtime/durability as well as achievable speed and pulsation behavior, were evaluated and compared to standard requirements. The behavior of the prototype device was compared with a commercially available pump. Results: The MRI-conditional pump system produced no image artifacts and could be safely operated in the presence of the magnetic field. The system exhibited minor performance-related differences when compared to a standard CPB pump; feature testing revealed that the prototype meets the requirements (i.e., operability, controllability, and flow range) needed to proceed with the planned animal studies. Conclusion: This MR-conditional prototype is suitable to perform an open-heart surgery in an animal model to assess brain perfusion in an MR environment., European surgical research, ISSN:0014-312X, ISSN:1421-9921

Fluids and Barriers of the CNS, 19 (S1), ISSN:2045-8118, s from Hydrocephalus 2022: the Fourteenth Meeting of the Hydrocephalus Society

In this work, a novel, genetic algorithm-based optimization framework (GAOF) has been developed and evaluated to optimize the control parameters of ventricular assist devices (VADs). This framework enables the optimization of complex control structures based on VAD- and patient-specific characteristics by allowing the selection of the numerical model of the human cardiovascular system and the VAD to represent the patient scenario of interest accurately. Additionally, the GAOF can incorporate treatment-specific goals during the definition of the objective functions of the optimization problem and, consequently, promotes the development of treatment-specific VAD controllers. The efficacy of the GAOF was assessed with one- and two-degree-of-freedom physiologic proportional-integral-derivative controllers and a physiologic data-driven iterative learning controller. Two VAD designs and various patient disease scenarios were used to further explore and evaluate the capabilities of the GAOF. The optimized controllers outperformed substantially the hand-tuned controller, which was used as the benchmark, in all the investigated cases. This highlights the potential improvement in the performance of any VAD controller by deploying the GAOF and, consequently, the possibility to increase the survival rates and enhance the quality of life of VAD patients., Biomedical Signal Processing and Control, 85, ISSN:1746-8094

Continuous measurement of vascular and hemodynamic parameters could improve monitoring of disease progression and enable timely clinical decision making and therapy surveillance in patients suffering from cardiovascular diseases. However, no reliable extravascular implantable sensor technology is currently available. Here, we report the design, characterization, and validation of an extravascular, magnetic flux sensing device capable of capturing the waveforms of the arterial wall diameter, arterial circumferential strain, and arterial pressure without restricting the arterial wall. The implantable sensing device, comprising a magnet and a magnetic flux sensing assembly, both encapsulated in biocompatible structures, has shown to be robust, with temperature and cyclic-loading stability. Continuous and accurate monitoring of arterial blood pressure and vascular properties was demonstrated with the proposed sensor in vitro with a silicone artery model and validated in vivo in a porcine model mimicking physiologic and pathologic hemodynamic conditions. The captured waveforms were further used to deduce the respiration frequency, the duration of the cardiac systolic phase, and the pulse wave velocity. The findings of this study not only suggest that the proposed sensing technology is a promising platform for accurate monitoring of arterial blood pressure and vascular properties, but also highlight the necessary changes in the technology and the implantation procedure to allow the translation of the sensing device in the clinical setting., JACC: Basic to Translational Science, 8 (5), ISSN:2452-302X

Aiming to address clinical requirements subsequent to SARS-CoV-2-related pulmonary disease, multiple research groups and industry groups carried out intensive studies to develop pandemic ventilators (PDVs). In vitro testing to critically evaluate the specific performance of the developed apparatuses is an essential requirement. This study presents a test protocol which promotes a test-oriented, iterative, and agile assessment and consecutive development of such PDVs. It allows for fast identification of specific characteristics of each PDV in the individual test features. The test protocol includes an evaluation of the accuracy of control systems and instruments at changing parameters, the oxygen dynamics, and the response to trigger signals. The test environment is a mechanical lung, which allows reproducing various lung mechanics and to simulate active breathing cycles. A total of three PDVs that are under development were iteratively tested, with a Hamilton T1 as a reference. Continuous testing of the PDVs under development enables quick identification of critical application aspects that deserve further improved. Based on the present test protocol, the ventilators demonstrate a promising performance justifying continued development., Frontiers in Medical Technology, 4

A high-quality, low-cost ventilator, dubbed HEV, has been developed by the particle physics community working together with biomedical engineers and physicians around the world. The HEV design is suitable for use both in and out of hospital intensive care units, provides a variety of modes and is capable of supporting spontaneous breathing and supplying oxygen-enriched air. An external air supply can be combined with the unit for use in situations where compressed air is not readily available. HEV supports remote training and post market surveillance via a Web interface and data logging to complement standard touch screen operation, making it suitable for a wide range of geographical deployment. The HEV design places emphasis on the ventilation performance, especially the quality and accuracy of the pressure curves, reactivity of the trigger, measurement of delivered volume and control of oxygen mixing, delivering a global performance which will be applicable to ventilator needs beyond the COVID-19 pandemic. This article describes the conceptual design and presents the prototype units together with a performance evaluation., Royal Society Open Science, 9 (3), ISSN:2054-5703

In this backstory, researchers from Swiss Federal Institute of Technology (ETH Zurich) who initiated an interdisciplinary program to generate innovative solutions for different cardiovascular diseases, such as myocardial infarction, valvular replacement, and movement-based rehabilitation therapy, discuss the benefits and challenges of interdisciplinary research., iScience, 25 (10), ISSN:2589-0042

Continuous flow ventricular assist devices (cfVADs) constitute a viable and increasingly used therapy for end-stage heart failure patients. However, they are still operating at a fixed-speed mode that precludes physiological cfVAD response and it is often related to adverse events of cfVAD therapy. To ameliorate this, various physiological controllers have been proposed, however, the majority of these controllers do not account for the lack of pulsatility in the cfVAD operation, which is supposed to be beneficial for the physiological function of the cardiovascular system. In this study, we present a physiological data- driven iterative learning controller (PDD-ILC) that accurately tracks predefined pump flow trajectories, aiming to achieve physiological, pulsatile, and treatment-driven response of cfVADs. The controller has been extensively tested in an in-silico environment under various physiological conditions, and compared with a physiologic pump flow proportional-integral-derivative controller (PF-PIDC) developed in this study as well as the constant speed (CS) control that is the current state of the art in clinical practice. Additionally, two treatment objectives were investigated to achieve pulsatility maximization and left ventricular stroke work (LVSW) minimization by implementing copulsation and counterpulsation pump modes, respectively. Under all experimental conditions, the PDD-ILC as well as the PF-PIDC demonstrated highly accurate tracking of the reference pump flow trajectories, outperforming existing model-based iterative learning control approaches. Additionally, the developed controllers achieved the predefined treatment objectives and resulted in improved hemodynamics and preload sensitivities compared to the CS support., Frontiers in Cardiovascular Medicine, 9, ISSN:2297-055X

The present study aims to develop a suitable animal model for evaluating the physiological interactions between cerebrospinal fluid (CSF) dynamics, hemodynamics, and abdominal compartment pressures. We seek to contribute to the enhanced recognition of the pathophysiology of CSF-dependent neurological disorders like hydrocephalus and the improvement of available treatment options. To date, no comprehensive animal model of CSF dynamics exists, and establishing an accurate model will advance our understanding of complex CSF physiology. Persisting knowledge gaps surrounding the communication and pressure propagation between the cerebrospinal space and adjacent anatomical compartments exacerbate the development of novel therapies for neurological diseases. Hence, the need for further investigation of the interactions of vascular, craniospinal, and abdominal pressures remains beyond dispute. Moreover, the results of this animal study support the optimization of in vitro test benches for medical device development, e.g., ventriculoperitoneal shunts. Six female white alpine sheep were surgically equipped with pressure sensors to investigate the physiological values of intracranial, intrathecal, arterial, central venous, jugular venous, vesical pressure, and four differently located abdominal pressures. These values were measured simultaneously during the acute animal trial with sheep under general anesthesia. Both carotid and femoral arterial blood pressure indicate a reliable and comparable representation of the systematic blood pressure. However, the jugular venous pressure and the central venous pressure in sheep in dorsal recumbency do not correlate well under general anesthesia. Furthermore, there is a trend for possible comparability of lateral intraventricular and lumbar intrathecal pressure. Nevertheless, animal body position during measurements must be considered since different body constitutions can alter the horizontal line between the cerebral ventricles and the lumbar subarachnoid space. While intra-abdominal pressure measurement in the four different abdominal quadrants yielded greater inter-individual variability, intra-vesical pressure measurements in our setting delivered comparable values for all sheep. We established a novel and comprehensive ovine animal model to investigate interdependent physiologic pressure propagation and multiparameter influences on CSF dynamics. The results of this study will contribute to further in vitro bench testing, the derivation of novel quantitative models, and the development of a pathologic ovine hydrocephalus model., Frontiers in Neuroscience, 16, ISSN:1662-453X, ISSN:1662-4548

Normal pressure hydrocephalus (NPH) is a chronic and progressive disease that affects predominantly elderly subjects. The most prevalent symptoms are gait disorders, generally determined by visual observation or measurements taken in complex laboratory environments. However, controlled testing environments can have a significant influence on the way subjects walk and hinder the identification of natural walking characteristics. The study aimed to investigate the differences in walking patterns between a controlled environment (10 m walking test) and real-world environment (72 h recording) based on measurements taken via a wearable gait assessment device. We tested whether real-world environment measurements can be beneficial for the identification of gait disorders by performing a comparison of patients’ gait parameters with an aged-matched control group in both environments. Subsequently, we implemented four machine learning classifiers to inspect the individual strides’ profiles. Our results on twenty young subjects, twenty elderly subjects and twelve NPH patients indicate that patients exhibited a considerable difference between the two environments, in particular gait speed (p-value p=0.0073), stride length (p-value p=0.0073), foot clearance (p-value p=0.0117) and swing/stance ratio (p-value p=0.0098). Importantly, measurements taken in real-world environments yield a better discrimination of NPH patients compared to the controlled setting. Finally, the use of stride classifiers provides promise in the identification of strides affected by motion disorders., Sensors, 21 (19), ISSN:1424-8220

Background:Developing novel therapeutic agents to treat amyotrophic lateral sclerosis (ALS) has been difficult due to multifactorial pathophysiologic processes at work. Intrathecal drug administration shows promise due to close proximity of cerebrospinal fluid (CSF) to affected tissues. Development of effective intrathecal pharmaceuticals will rely on accurate models of how drugs are dispersed in the CSF. Therefore, a method to quantify these dynamics and a characterization of differences across disease states is needed. Methods:Complete intrathecal 3D CSF geometry and CSF flow velocities at six axial locations in the spinal canal were collected by T2-weighted and phase-contrast MRI, respectively. Scans were completed for eight people with ALS and ten healthy controls. Manual segmentation of the spinal subarachnoid space was performed and coupled with an interpolated model of CSF flow within the spinal canal. Geometric and hydrodynamic parameters were then gen-erated at 1 mm slice intervals along the entire spine. Temporal analysis of the waveform spectral content and feature points was also completed. Results:Comparison of ALS and control groups revealed a reduction in CSF flow magnitude and increased flow propagation velocities in the ALS cohort. Other differences in spectral harmonic content and geometric comparisons may support an overall decrease in intrathecal compliance in the ALS group. Notably, there was a high degree of vari-ability between cases, with one ALS patient displaying nearly zero CSF flow along the entire spinal canal. Conclusion:While our sample size limits statistical confidence about the differences observed in this study, it was possible to measure and quantify inter-individual and cohort variability in a non-invasive manner. Our study also shows the potential for MRI based measurements of CSF geometry and flow to provide information about the hydro-dynamic environment of the spinal subarachnoid space. These dynamics may be studied further to understand the behavior of CSF solute transport in healthy and diseased states., Fluids and Barriers of the CNS, 17 (1), ISSN:2045-8118

Introduction: In radiotherapy, tumors may move due to the patient’s respiration, which decreases treatment accuracy. Some motion mitigation methods require measuring the tumor position during treatment. Current available sensors often suffer from time delays, which degrade the motion mitigation performance. However, the tumor motion is often periodic and continuous, which allows predicting the motion ahead. Method and Materials: A couch tracking system was simulated in MATLAB and five prediction filters selected from literature were implemented and tested on 51 respiration signals (median length: 103 s). The five filters were the linear filter (LF), the local regression (LOESS), the neural network (NN), the support vector regression (SVR), and the wavelet least mean squares (wLMS). The time delay to compensate was 320 ms. The normalized root mean square error (nRMSE) was calculated for all prediction filters and respiration signals. The correlation coefficients between the nRMSE of the prediction filters were computed. Results: The prediction filters were grouped into a low and a high nRMSE group. The low nRMSE group consisted of the LF, the NN, and the wLMS with a median nRMSE of 0.14, 0.15, and 0.14, respectively. The high nRMSE group consisted of the LOESS and the SVR with both a median nRMSE of 0.34. The correlations between the low nRMSE filters were above 0.87 and between the high nRMSE filters it was 0.64. Conclusion: The low nRMSE prediction filters not only have similar median nRMSEs but also similar nRMSEs for the same respiration signals as the high correlation shows. Therefore, good prediction filters perform similarly for identical respiration patterns, which might indicate a minimally achievable nRMSE for a given respiration pattern., Current Directions in Biomedical Engineering, 3 (2), ISSN:2364-5504

Fluids and Barriers of the CNS, 12, ISSN:2045-8118

Background Intrafractional motion can be a substantial uncertainty in precision radiotherapy. Conventionally, the target volume is expanded to account for the motion. Couch-tracking is an alternative, where the patient is moved to compensate for the tumor motion. However, the couch motion may influence the patient’s stress and respiration behavior decreasing the couch-tracking effectiveness. Methods In total, 100 volunteers were positioned supine on a robotic couch, which moved dynamically and respiration synchronized. During the measurement, the skin conductivity, the heartrate, and the gaze location were measured indicating the volunteer’s stress. Volunteers rated the subjective motion sickness using a questionnaire. The measurement alternated between static and tracking segments (three cycles), each 1 min long. Results The respiration amplitude showed no significant difference between tracking and static segments, but decreased significantly from the first to the last tracking segment (p, Radiation Oncology, 12

Heart failure (HF) is the final common pathway of many, usually coexisting, cardiovascular diseases (CVDs) that on a global scale affects more than 64 million people. HF results in structural and functional impairment of the ventricles, rendering the heart unable to provide sufficient cardiac output for organ perfusion. Although advanced therapeutical protocols have been developed over the last decades, the absence of adequate monitoring technologies in the outpatient setting limits the surveillance of the therapy. This often results in suboptimal patient management and severe progression of HF. For these patients, the treatment is limited to only two options, namely heart transplantation (HTx) and mechanical circulatory support with ventricular assist devices (VADs). Following their technological advancements, approximately 6.000 VADs are implanted yearly, with the vast majority of the devices being continuous-flow turbodynamic pumps. VAD patients nowadays can reach similar survival rates to HTx-recipients, however, their quality of life (QoL) is diminished. This shortcoming stems from the remaining VAD-related adverse events (AE) that result in high rates of rehospitalizations. These AEs are commonly related to the inability of current VADs to imitate the physiological response with respect to cardiac output adjustment to changing perfusion demands of the patients. By lacking physiological response, VADs are prone to over- or under-pumping conditions that provoke life-threatening events of suction or overload. To pave the burden of such events, many physiological controllers have been proposed for VADs. Although some of these controllers improve the responsiveness of the VADs, none has been implemented in the clinical setting. Shortcomings that restrict the clinical implementation of physiological controllers are the lack of reliable monitoring approaches to provide the feedback parameters, the lack of adaptiveness to changes in the time-varying parameters of the cardiovascular system (CVS), and the enormous variability in patient characteristics that constitute the identification of universal control parameters challenging. In this context, the aim of this thesis was the realization of sensory technology that enable continuous and accurate monitoring of vascular and hemodynamic properties of HF patients, as well as the development of control approaches that restore the physiological response of VADs and, at the same time, account for long-term biological changes of the patient. To achieve the overall aim, four studies were conducted over the course of this thesis. The first study focused on sensing approaches that enable the outpatient surveillance of HF patients and provide the necessary parameters for control purposes. Hence, after exploring various sensing approaches, an extravascular, magnetic-flux sensing device was developed and validated. The sensing device was capable of capturing the waveforms of the arterial wall diameter, arterial circumferential strain and arterial blood pressure (ABP) without restricting the arterial wall. Based on the continuous ABP waveform, the sensor allowed the deduction of pulse wave velocity, respiration frequency, and duration of the systolic phase of the cardiac cycle. The implantable sensing device demonstrated unaffected performance after sterilization, immersion in liquid, and temperature changes, while it was able to accurately capture the monitored parameters in-vitro and in-vivo, under various and extreme physiologic and pathologic conditions induced by cardiopulmonary bypass support. The information hidden in the arterial blood pressure waveform, as well as other vascular properties captured with the implantable sensing device, could offer new capabilities in HF patient management, allowing patient-specific treatment and new prospects in the physiological control of VADs. The objective of the second study was to develop a novel algorithmic approach that can exploit the hemodynamic data provided by the sensing device of the first study, to resolve the unmet need for continuous monitoring of the remaining contractility of HF patients and enable adaptive physiological controllers. To meet this objective, the estimation of the remaining contractility by applying state-of-the-art machine learning models and using left ventricular pressure (LVP) signals was assessed. Specifically, LVP data were generated on an in-vitro, hybrid mock circulation for nine contractility levels by varying preload, afterload, pump speed, and heart rate parameters. Based on these data, the estimation accuracy of two time series classifiers and two graph-based neural networks were evaluated and compared. From the time series classifiers, the dynamic time warping nearest neighbor (DTW-NN) classifier and the support vector (SVM) classifier were selected, while from the plethora of graph-based neural networks, a pre-trained architecture and a custom architecture were implemented. The results showed that all classifiers were able to correctly estimate the contractility level, with accuracy higher than 98%; however, the SVM showed superior performance. The continuous and accurate estimation of the remaining contractility with the developed approach could substantially support patient surveillance, treatment adjustments, and real-time adaptation of the control parameters of physiological controllers. Once the necessary technology and algorithms to allow continuous monitoring of CVS hemodynamics and time-varying properties were realized with the first two studies, the third study aimed to the development of a physiologic data-driven iterative learning controller (PDD-ILC) that achieves physiologic, pulsatile, and treatment-driven VAD response. In detail, the PDD-ILC enabled the generation of preload-adaptive reference pump-flow trajectories based on the Frank-Starling mechanism and treatment objectives, such as pulsatility maximization or left ventricular stroke work (LVSW) minimization. To eliminate the need for a model of the CVS and the pump, the tracking of the reference flow trajectories was achieved by implementing a data-driven iterative learning controller based on signals of LVP and pump flow. The physiologic responsiveness and trajectory tracking of the PDD-ILC was assessed with in-silico experiments that emulated various physiologic conditions, and compared with physiological pump flow proportional-integrative-derivative controller (PF-PIDC) (developed in this study too) as well as the constant speed (CS) control that is the current state-of-the-art in clinical practice. Under all experimental conditions, the PDD-ILC as well as the PF-PIDC showed high accuracy in tracking the reference pump flow trajectories, outperforming existing model-based iterative learning control approaches. Additionally, the developed controllers were able to meet the predefined treatment objectives resulting in improved hemodynamics and preload sensitivities compared to the CS support. The implementation of the PDD-ILC in current VADs would allow artificial pulsatility and patient-specific preload sensitivity, offering new opportunities in VAD patient management. The realization of the PDD-ILC, which features six control parameters, showed that the identification of the control parameters with the non-intuitive, trial-and-error methods that are used nowadays results in suboptimal controllers and restricts the development of patient-specific controllers. As a result, the fourth study of this thesis was dedicated to the development of an optimization framework (GAOF) for VAD control parameters. The GAOF offered the opportunity to develop an objective function based on patient characteristics and treatment objectives and by using genetic algorithm-based optimization algorithms enabled the identification of optimum control parameters. The efficacy of the GAOF was assessed with three control structures of different complexity, two different VAD designs, and various patient disease scenarios. The results showed that the optimized controllers outperformed the hand-tuned controllers. This highlighted the potential improvement in the performance of any VAD controller by deploying the GAOF and, consequently, the possibility to increase the survival rates and enhance the quality of life of VAD patients. In conclusion, the studies conducted in this thesis contribute to the realization of continuous monitoring of the hemodynamic status of HF patients and control algorithms that, through patient- and treatment-specific optimization, enhance the pulsatility and the physiological response of VADs. The combination and implementation of the developed algorithms and sensory technology in the clinical setting may lay the foundation for clinicians to apply and adapt their therapeutic protocols and, hence, improve the survival rates and the QoL of HF patients.

Health monitoring has experienced a significant transformation over the last few decades. Through a series of technological breakthroughs, new monitoring devices allow to reduce the constant need of medical personnel in follow-up care. These series of inventions are driven by the increased number of patients, which contrasts with an upcoming shortage of healthcare professionals. As a result, new health monitoring devices aim to measure biomarkers, with as little as possible intervention from medical personnel, in a cost-effective, reliable and portable manner. One of the technologies capable of fulfilling this goal is “Soft, Conductive Nanocomposites”. These new types of materials have the ability to seamlessly interface with the human body without causing any damage to it. Their intrinsic softness, as well as their electrical properties turns them into well suited candidates to continuously perform healthcare monitoring while reducing the need of healthcare professionals. Although they have been heavily explored in the last two decades, continuous improvements are still being presented, and new fields of applications are being investigated. In this thesis, I present a thorough analysis of these materials, in the context of biomedical applications, which has been of interest in the Laboratory of Biosensors and Bioelectronics for the last decade. Furthermore, I also explored new methods which expand the current capabilities to control the electrical properties of these materials. I demonstrate manipulation of nanowires using magnetic forces thereby creating ordered structures with interesting electrical properties when embedded in soft, conductive nanocomposites. In addition, I illustrate the potential of these materials in a clinical setting by presenting a soft, biocompatible strain sensor which can continuously measure the volume of the left ventricle of the heart in a post-surgery scenario. The strain sensor was sutured on the apex of the heart. Changes in volume of the left ventricle were related to changes in the resistance of the strain sensor, produced due to deformation of the myocardium. The sensor was evaluated in-vitro and in-vivo. Finally, I present a feasibility study to build a point-of-care biosensing tool. In a similar manner, point-of-care diagnostics are intended to conduct biosensing conveniently and immediately on patients, with no intervention of healthcare professionals. The main limitation currently faced by this type of technology is the high ionic content encountered in physiological fluids, which poses a fundamental physical problem due to the “Debye screening effect”. I propose using conformation changing aptamers in combination with thin gold films as a solution to overcome this effect, and elaborate on the methods to realize such platform. Although analyte detection was hindered due to technical problems, and hence it is not presented, I provide feasibility results and possible solutions that would help to solve these problems. In conclusion, this thesis is an attempt to develop new tools to conduct health monitoring with minimal intervention of medical personnel, which can be obtained by following different paths of research. In this case: sensing biomedical signals with soft, conductive nanocomposites and thin metal films.

Patients suffering from heart failure cannot provide sufficient cardiac output for organ perfusion, such that effective medical treatment is required. Three therapies for the treatment of heart failure have been clinically established: pharmacological treatment, heart transplantation, and implantation of a left-ventricular assist device (LVAD). Despite the efficacy of these therapies, survival rates remain unsatisfactorily low. The continuous monitoring of hemodynamic parameters can improve survival, as it supports timely and effective clinical decision making. The hemodynamics of the healthy heart are very sensitive to the left-ventricular (LV) volume. Hence, the LV volume is a promising hemodynamic parameter for clinical decision making. In addition, an LV volume measurement could be used for physiological feedback control of an LVAD, presumably increasing his or her quality of life and reducing the probability of adverse events. The aim of this thesis was to identify key requirements for an LV volume sensor, investigate possible measurement principles and evaluate the three most promising sensor concepts in terms of their sensitivity and accuracy. The LV volume cannot easily be measured remotely, because the requirements for a real-time portable sensor are highly complex. An LV volume sensor needs to be implemented in such a way that traumatic injury is avoided and the areas of foreign surfaces in the body are not increased. The sensor should be small enough to be safely implanted or attached to the body surface. The LV volume measurement should be continuous and robust to changes in heart geometry, posture or hematocrit. Computer tomography, magnetic resonance imaging, various forms of impedance measurement, pressure measurement, echocardiography and strain sensors have been proposed to estimate the LV volume. However, none of them meets all of the above requirements. An implantable, biocompatible and robust LV volume sensor remains to be developed. Three concepts for the real-time LV volume measurement are proposed in this thesis: Acoustic resonance, ultrasonic distance and the QRS amplitude of the electrocardiogram. The concepts were evaluated in a testing environment suitable to their current stage of development: in-silico, in-vitro, in-vivo and in the setting of an experimental clinical study. All measurement priniciples were sensitive to the LV volume. The achievable LV volume accuracies were assessed using a Bland-Altman analysis. The accuracies for the acoustic concept could not be evaluated as the principle was only assessed in-silico and lacked the possibility to account for noise. The ultrasonic distance approach yielded estimation accuracies for the LV volume smaller than 20% in human heart phantoms in vitro. The QRS-amplitude in vivo measurement rendered LV volume estimation accuracies smaller than 20%. The experimental clinical study revealed a small, but significant correlation between the QRS amplitude on the body surface and the mean pulmonary arterial pressure. The three concepts presented are all atraumatic, small enough, capable of real-time measurement and should be sufficiently robust as they can be placed close to the heart. The QRS amplitude is the most promising concept to be implemented in the near future, particularly because of the electrode size. The ultrasonic distance measurement is equally convincing in terms of accuracy, but requires more effort for miniaturization and efficient data processing. The influence of hematocrit changes on both measurement principles should be investigated carefully in subsequent studies. In conclusion, continuous measurement of LV volume is possible and will likely increase survival rates in heart failure patients in the future.