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Functional block diagram of the electronic circuit. The circuit comprises three main functional blocks: signal conditioning, wireless interface and supply control. The path of the blood flow signal is indicated by arrows. https://doi.org/10.1371/journal.pone.0227372.g004
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Aortic valve disease is one of the leading forms of complications in the cardiovascular system. The failing native aortic valve is routinely surgically replaced with a bioprosthesis. However, insufficient durability of bioprosthetic heart valves often requires reintervention. Valve degradation can be assessed by an analysis of the blood flow charac...
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Context 1
... device has been designed for bidirectional flow measurement to record forward and reverse flow through the aorta (and the AV). The functional block diagram of the electronic circuitry is depicted in Fig 4. The circuit consists of three main functional blocks: signal conditioning, supply control, and a wireless interface. The raw signal is connected to the circuit through the positive and negative leads E1, E2 and a reference electrode REF (perpendicular to E1 and E2 in the magnet array). ...
Citations
... The magnification factor, also known as the amplification factor or gain, is crucial in understanding how a dynamic system amplifies or attenuates input vibrations at specific frequencies. It is typically depicted as a function of frequency, illustrating the system's behavior over a spectrum of frequencies [56]. ...
... Prosthetic heart valves monitoring. The reference was cited from[56]. ...
Forced-damped vibrations are pivotal in various medical applications, significantly contributing to the examination of tissue mechanical properties, development of medical devices, and understanding of biological systems' complexities. These vibrations represent the dynamic behavior of systems subjected to external forces and damping, where an external force continues to act, and damping determines the rate of energy dissipation. Advanced exploration of damping properties has led to the creation of novel technologies and methods, enhancing our ability to probe and manipulate the complex mechanical dynamics of biological tissues.
... Previously developed devices for blood pressure monitoring include a magnetic flowmeter attached to the aortic valve [13], a wired [12], or battery-powered [14] silicon cuff that uses ultrasonic Doppler shift to detect flow and an application specific integrated circuit (ASIC)-based inductively powered silicon nanowire sensor [15]. These devices, however, are limited to the aortic valve location, require the use of a battery or wire, or need to be placed inside the graft to function. ...
... Each variable in this equation is calculated independently as follows. C. DHA Self-Inductance L DH To simplify the model, the DHA was approximated as a series of intersecting circular loop antennas [13]. Each pair of loops was treated as a cell, and superposition was used to calculate the inductance of each cell separately, given a variable distance from each cell (winding pair) to the external transceiver. ...
This work demonstrates a batteryless, implantable blood-flow sensor with RFID readout. This flexible sensor system was developed specifically for surgical implantation around a blood vessel, without contacting blood to reduce platelet deposition, clotting, and other complications with blood-contacting sensors. A flexible sensor and circuit architecture was adopted to enable a cuff-like form factor for surgical implantation around an artery, vein, or graft without piercing or cutting the vessel. This required development of a flexible RFID data/power antenna using a split-double helix antenna (DHA) which could be opened and closed, unlike a solenoidal or flat spiral antenna. DHAs with diameter of 3- 10 mm were fabricated and characterized on the bench, showing typical coupling coefficient of 0.007 when placed 5 cm from a reader. Prototype implantable DHA systems were developed to wrap around vessels of 3 to 8 mm. A flexible pulsation sensor (FPS) was developed from a piezoresistive carbon black-polydimethylsiloxane (PDMS) nanocomposite, which enabled measurement of vascular distension caused by blood flow. A commercial RFID chip enabled sensor readout to an external transceiver in real time with a sample rate of 12 Hz when immersed in saline test media. Validation experiments on a vascular phantom with simulated stenosis demonstrated blood flow rate monitoring from 200 – 400 mL/min with the capacity to distinguish flow changes as low as 10 mL/min.
... One key feature of the NFC platform is the feasibility of passive devices powered by separate energy sources, usually NFC readers. These are often referred to as 'battery-free' or 'battery-less', differentiating NFC from other wireless platforms, such as Bluetooth and Wi-Fi, which require batteries or other power sources [2][3][4][5][6][7][8][9][10]. Since most modern smartphones are equipped with an NFC function, this technology has become an integral part of our daily lives. ...
Wireless sensor tags in flexible formats have numerous applications; some are commercially available for specific target applications. However, most of these wireless sensor tags have been used for single-sensing applications. In this study, we designed a printed circuit board (PCB) module (13 mm × 13 mm) for near-field communication-enabled sensor tags with both electrical resistance and capacitance read-out channels that enables dual-channel sensing. As part of the wireless sensor tag, a square antenna pattern was printed directly on a flexible poly(ethylene terephthalate) (PET) substrate and integrated into the PCB module to demonstrate a dual-channel temperature and ethylene gas sensor. The temperature and ethylene sensors were printed using a positive temperature coefficient ink and a tin oxide (SnO2) nanoparticle ink, respectively. With dual sensing capabilities, this type of sensor tag can be used in smart packaging for the quality monitoring of fresh produce (e.g., bananas) by tracking temperature and ethylene concentration in the storage/transport environment.
... The sensor showed high accuracy compared to reference measurement during in-vivo experiments; however, it's performance quickly decayed after several hours, limiting the applicability of the sensor for short-term use. Vennemann et al. 87 have presented a wireless and batteryless implantable flow sensor, however the sensor has been validated only in an in-silico environment. Considering the VAD-supported patients, a new approach for integrating a pressure sensor at the inflow cannula to measure the LV pressure has been developed by v. Petersdorff-Campen et al. 88 . ...
... As depicted in Fig. 4.7c, the PF-PIDC showed a slightly increased RMSE of 0. 24 during the afterload experiment (Exp2). In this setting, the PDD-ILC also presented higher RMSE and maximum error throughout the entire experiment, achieving an RMSE of 0. 87 at the end of the experiment. During the sleepto-wake (Exp3) and contractility variation (Exp4) settings both controllers showed excellent tracking performance, resulting in RMSE and maximum error values similar to the rest-conditions experiment (Fig. 4.7d-e). ...
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.
... Recent reports describe the development of sensors for continuous and real-time monitoring of patients on the basis of magnetic 5 and capacitive 6,7 approaches with capabilities for wireless monitoring of blood-flow rates through the aorta 5 or femoral artery 6 , or of pressures outside the wall of the carotid artery 7 via near-field communication (NFC) 5 and inductive schemes 6,7 , respectively. These NFC and inductive links allow short-range (<4 cm) wireless measurements, compared with the long range capabilities of Bluetooth Low Energy (BLE) communication (meters). ...
Devices for monitoring blood haemodynamics can guide the perioperative management of patients with cardiovascular disease. Current technologies for this purpose are constrained by wired connections to external electronics, and wireless alternatives are restricted to monitoring of either blood pressure or blood flow. Here we report the design aspects and performance parameters of an integrated wireless sensor capable of implantation in the heart or in a blood vessel for simultaneous measurements of pressure, flow rate and temperature in real time. The sensor is controlled via long-range communication through a subcutaneously implanted and wirelessly powered Bluetooth Low Energy system-on-a-chip. The device can be delivered via a minimally invasive transcatheter procedure or it can be mounted on a passive medical device such as a stent, as we show for the case of the pulmonary artery in a pig model and the aorta and left ventricle in a sheep model, where the device performs comparably to clinical tools for monitoring of blood flow and pressure. Battery-less and wireless devices such as these that integrate capabilities for flow, pressure and temperature sensing offer the potential for continuous monitoring of blood haemodynamics in patients.
... A recent study coupled signal processing with machine learning for the evaluation of the mobility recorded by a miniaturized pressure sensor embedded in the prosthetic valve structure [16]. Other studies proposed the use of magnetic sensors embedded in the valve leaflets for the quantification of the transvalvular flow and for the monitoring of leaflets' movements [17,18]. ...
IntraValvular Impedance (IVI) sensing is an innovative concept for monitoring heart valve prostheses after implant. We recently demonstrated IVI sensing feasible in vitro for biological heart valves (BHVs). In this study, for the first time, we investigate ex vivo the IVI sensing applied to a BHV when it is surrounded by biological tissue, similar to a real implant condition. A commercial model of BHV was sensorized with three miniaturized electrodes embedded in the commissures of the valve leaflets and connected to an external impedance measurement unit. To perform ex vivo animal tests, the sensorized BHV was implanted in the aortic position of an explanted porcine heart, which was connected to a cardiac BioSimulator platform. The IVI signal was recorded in different dynamic cardiac conditions reproduced with the BioSimulator, varying the cardiac cycle rate and the stroke volume. For each condition, the maximum percent variation in the IVI signal was evaluated and compared. The IVI signal was also processed to calculate its first derivative (dIVI/dt), which should reflect the rate of the valve leaflets opening/closing. The results demonstrated that the IVI signal is well detectable when the sensorized BHV is surrounded by biological tissue, maintaining the similar increasing/decreasing trend that was found during in vitro experiments. The signal can also be informative on the rate of valve opening/closing, as indicated by the changes in dIVI/dt in different dynamic cardiac conditions.
... In recent years, some attempts have been made to conceive an implantable device for the continuous monitoring of HVP functionality after implantation, in order to detect SLT early. Vennemann et al. [18] realized a wireless and battery-less implantable blood flow sensor, consisting of a permanent magnet array, for the remote monitoring of HVP functionality based on Faraday's law of induction. Another proposal comes from Bailoor et al. [19], who presented a computational "proof-of-concept" study which exploits CFD (Computational Fluid Dynamics) analysis and Supervised Learning to determine the best positioning for embedded pressure sensors near the HVP in order to detect RLM. ...
Subclinical valve thrombosis in heart valve prostheses is characterized by the progressive reduction in leaflet motion detectable with advanced imaging diagnostics. However, without routine imaging surveillance, this subclinical thrombosis may be underdiagnosed. We recently proposed the novel concept of a sensorized heart valve prosthesis based on electrical impedance measurement (IntraValvular Impedance, IVI) using miniaturized electrodes embedded in the valve structure to generate a local electric field that is altered by the cyclic movement of the leaflets. In this study, we investigated the feasibility of the novel IVI-sensing concept applied to biological heart valves (BHVs). Three proof-of-concept prototypes of sensorized BHVs were assembled with different size, geometry and positioning of the electrodes to identify the optimal IVI-measurement configuration. Each prototype was tested in vitro on a hydrodynamic heart valve assessment platform. IVI signal was closely related to the electrodes’ positioning in the valve structure and showed greater sensitivity in the prototype with small electrodes embedded in the valve commissures. The novel concept of IVI sensing is feasible on BHVs and has great potential for monitoring the valve condition after implant, allowing for early detection of subclinical valve thrombosis and timely selection of an appropriate anticoagulation therapy.
... There have been major advances with integrating sensors into cardiovascular (CVS) implants, some of which made it to clinical studies, 201,325−330 and more are in the experimental stage. 33,[368][369][370][371][372]379 Details of the implants that integrate sensors to detect related problems are discussed in the following sections ( Figure 8). ...
... Experimental Studies. Sensor-integrating CVS implants that are still in the experimental study stage comprise stents, 369,370,379 heart valves, 33,371 and pumps. 368,372 At the time of writing this paper, only one heart pump made it to the level of animal studies, 368 where MEMS-based devices which provide accurate blood pressure measurements for the regulation of pump speed and output have been designed, fabricated, and tested in a sheep. ...
... Sensors were developed for heart valves to monitor valve opening and detect any thrombosis or malfunction that may occur at an early stage. 371 Dedicated electrodes were also embedded in the structure of the heart valve prosthesis to generate a local electric field that is altered by the valve leaflets during their cyclic opening and closure movements. 33 This can be used to measure electric impedance and detect any thrombus formation that may alter the motion of the leaflets. ...
Because of the aging human population and increased numbers of surgical procedures being performed, there is a growing number of biomedical devices being implanted each year. Although the benefits of implants are significant, there are risks to having foreign materials in the body that may lead to complications that may remain undetectable until a time at which the damage done becomes irreversible. To address this challenge, advances in implantable sensors may enable early detection of even minor changes in the implants or the surrounding tissues and provide early cues for intervention. Therefore, integrating sensors with implants will enable real-time monitoring and lead to improvements in implant function. Sensor integration has been mostly applied to cardiovascular, neural, and orthopedic implants, and advances in combined implant-sensor devices have been significant, yet there are needs still to be addressed. Sensor-integrating implants are still in their infancy; however, some have already made it to the clinic. With an interdisciplinary approach, these sensor-integrating devices will become more efficient, providing clear paths to clinical translation in the future.
... (f) Biosignal data measured by the device [52]. (g-i) Construction of an NFC heart valve monitoring device [53]. ...
... The current consumed by the NFC chip (SL13A) was 150 μA and the current consumed by the circuit for sensing was 230 μA; therefore, the resulting device's final power consumption was 1.3 mW. The device with an effective sampling rate of 60.2 Hz presents a form factor optimized for miniaturization of the magnetic ring structure [53]. Figure 6g provides a schematic diagram of an implantable magnetic flow sensor attached to the ascending aorta. ...
Near-field communication (NFC) is a low-power wireless communication technology used in contemporary daily life. This technology contributes not only to user identification and payment methods, but also to various biomedical fields such as healthcare and disease monitoring. This paper focuses on biomedical applications among the diverse applications of NFC. It addresses the benefits of combining traditional and new sensors (temperature, pressure, electrophysiology, blood flow, sweat, etc.) with NFC technology. Specifically, this report describes how NFC technology, which is simply applied in everyday life, can be combined with sensors to present vision and opportunities to modern people.
... More recently, Vennemann et al. developed an implantable magnetic blood flow sensor (Figure 7c), being the wirelessly transmitted to the patient's smartphone for in-depth processing. The wireless operation could be sustained as long as an NFC (near field communication)-enabled smartphone is in the vicinity of the implant and transmitting power through inductive coupling [132]. [131] and (c) illustration of the heart valve monitoring system, which communicates the data by wireless [132]. ...
... The wireless operation could be sustained as long as an NFC (near field communication)-enabled smartphone is in the vicinity of the implant and transmitting power through inductive coupling [132]. [131] and (c) illustration of the heart valve monitoring system, which communicates the data by wireless [132]. ...
... Besides those, there is also the presence of printing methods, essentially screen and transfer printing. [131] and (c) illustration of the heart valve monitoring system, which communicates the data by wireless [132]. ...
Biosensors devices have attracted the attention of many researchers across the world. They have the capability to solve a large number of analytical problems and challenges. They are future ubiquitous devices for disease diagnosis, monitoring, treatment and health management. This review presents an overview of the biosensors field, highlighting the current research and development of bio-integrated and implanted biosensors. These devices are micro- and nano-fabricated, according to numerous techniques that are adapted in order to offer a suitable mechanical match of the biosensor to the surrounding tissue, and therefore decrease the body’s biological response. For this, most of the skin-integrated and implanted biosensors use a polymer layer as a versatile and flexible structural support, combined with a functional/active material, to generate, transmit and process the obtained signal. A few challenging issues of implantable biosensor devices, as well as strategies to overcome them, are also discussed in this review, including biological response, power supply, and data communication.
