A novel broadband forcecardiography sensor for simultaneous monitoring of respiration, infrasonic cardiac vibrations and heart sounds

The precordial mechanical vibrations generated by cardiac contractions have a rich frequency spectrum. While the lowest frequencies can be palpated, the higher infrasonic frequencies are usually captured by the seismocardiogram (SCG) signal and the audible ones correspond to heart sounds. Forcecardiography (FCG) is a non-invasive technique that measures these vibrations via force sensing resistors (FSR). This study presents a new piezoelectric sensor able to record all heart vibrations simultaneously, as well as a respiration signal. The new sensor was compared to the FSR-based one to assess its suitability for FCG. An electrocardiogram (ECG) lead and a signal from an electro-resistive respiration band (ERB) were synchronously acquired as references on six healthy volunteers (4 males, 2 females) at rest. The raw signals from the piezoelectric and the FSR-based sensors turned out to be very similar. The raw signals were divided into four components: Forcerespirogram (FRG), Low-Frequency FCG (LF-FCG), High- Frequency FCG (HF-FCG) and heart sounds (HS-FCG). A beat-by-beat comparison of FCG and ECG signals was carried out by means of regression, correlation and Bland–Altman analyses, and similarly for respiration signals (FRG and ERB). The results showed that the infrasonic FCG components are strongly related to the cardiac cycle (R2 > 0.999, null bias and Limits of Agreement (LoA) of ± 4.9 ms for HF-FCG; R2 > 0.99, null bias and LoA of ± 26.9 ms for LF-FCG) and the FRG inter-breath intervals are consistent with ERB ones (R2 > 0.99, non-significant bias and LoA of ± 0.46 s). Furthermore, the piezoelectric sensor was tested against an accelerometer and an electronic stethoscope: synchronous acquisitions were performed to quantify the similarity between the signals. ECG-triggered ensemble averages (synchronized with R-peaks) of HF-FCG and SCG showed a correlation greater than 0.81, while those of HS-FCG and PCG scored a correlation greater than 0.85. The piezoelectric sensor demonstrated superior performances as compared to the FSR, providing more accurate, beat-by-beat measurements. This is the first time that a single piezoelectric sensor demonstrated the ability to simultaneously capture respiration, heart sounds, an SCG-like signal (i.e., HF-FCG) and the LF-FCG signal, which may provide information on ventricular emptying and filling events. According to these preliminary results the novel piezoelectric FCG sensor stands as a promising device for accurate, unobtrusive, long-term monitoring of cardiorespiratory functions and paves the way for a wide range of potential applications, both in the research and clinical fields. However, these results should be confirmed by further analyses on a larger cohort of subjects, possibly including also pathological patients

A Novel Broadband Forcecardiography Sensor for Simultaneous Monitoring of Respiration, Infrasonic Cardiac Vibrations and Heart Sounds

The precordial mechanical vibrations generated by cardiac contractions have a rich frequency spectrum. While the lowest frequencies can be palpated, the higher infrasonic frequencies are usually captured by the seismocardiogram (SCG) signal and the audible ones correspond to heart sounds. Forcecardiography (FCG) is a non-invasive technique that measures these vibrations via force sensing resistors (FSR). This study presents a new piezoelectric sensor able to record all heart vibrations simultaneously, as well as a respiration signal. The new sensor was compared to the FSR-based one to assess its suitability for FCG. An electrocardiogram (ECG) lead and a signal from an electro-resistive respiration band (ERB) were synchronously acquired as references on six healthy volunteers (4 males, 2 females) at rest. The raw signals from the piezoelectric and the FSR-based sensors turned out to be very similar. The raw signals were divided into four components: Forcerespirogram (FRG), Low-Frequency FCG (LF-FCG), High-Frequency FCG (HF-FCG) and heart sounds (HS-FCG). A beat-by-beat comparison of FCG and ECG signals was carried out by means of regression, correlation and Bland–Altman analyses, and similarly for respiration signals (FRG and ERB). The results showed that the infrasonic FCG components are strongly related to the cardiac cycle (R2 > 0.999, null bias and Limits of Agreement (LoA) of ± 4.9 ms for HF-FCG; R2 > 0.99, null bias and LoA of ± 26.9 ms for LF-FCG) and the FRG inter-breath intervals are consistent with ERB ones (R2 > 0.99, non-significant bias and LoA of ± 0.46 s). Furthermore, the piezoelectric sensor was tested against an accelerometer and an electronic stethoscope: synchronous acquisitions were performed to quantify the similarity between the signals. ECG-triggered ensemble averages (synchronized with R-peaks) of HF-FCG and SCG showed a correlation greater than 0.81, while those of HS-FCG and PCG scored a correlation greater than 0.85. The piezoelectric sensor demonstrated superior performances as compared to the FSR, providing more accurate, beat-by-beat measurements. This is the first time that a single piezoelectric sensor demonstrated the ability to simultaneously capture respiration, heart sounds, an SCG-like signal (i.e., HF-FCG) and the LF-FCG signal, which may provide information on ventricular emptying and filling events. According to these preliminary results the novel piezoelectric FCG sensor stands as a promising device for accurate, unobtrusive, long-term monitoring of cardiorespiratory functions and paves the way for a wide range of potential applications, both in the research and clinical fields. However, these results should be confirmed by further analyses on a larger cohort of subjects, possibly including also pathological patients

High-Performance Accelerometer Based On Asymmetric Gapped Cantilevers For Physiological Acoustic Sensing

Continuous or mobile monitoring of physiological sounds is expected to play important role in the emerging mobile healthcare field. Because of the miniature size, low cost, and easy installation, accelerometer is an excellent choice for continuous physiological acoustic signal monitoring. However, in order to capture the detailed information in the physiological signals for clinical diagnostic purpose, there are more demanding requirements on the sensitivity/noise performance of accelerometers. In this thesis, a unique piezoelectric accelerometer based on the asymmetric gapped cantilever which exhibits significantly improved sensitivity is extensively studied. A meso-scale prototype is developed for capturing the high quality cardio and respiratory sounds on healthy people as well as on heart failure patients. A cascaded gapped cantilever based accelerometer is also explored for low frequency vibration sensing applications such as ballistocardiogram monitoring. Finally, to address the power issues of wireless sensors such as wireless wearable health monitors, a wide band vibration energy harvester based on a folded gapped cantilever is developed and demonstrated on a ceiling air condition unit

ELECTRO-MECHANICAL DATA FUSION FOR HEART HEALTH MONITORING

Heart disease is a major public health problem and one of the leading causes of death worldwide. Therefore, cardiac monitoring is of great importance for the early detection and prevention of adverse conditions. Recently, there has been extensive research interest in long-term, continuous, and non-invasive cardiac monitoring using wearable technology. Here we introduce a wearable device for monitoring heart health. This prototype consists of three sensors to monitor electrocardiogram (ECG), phonocardiogram (PCG), and seismocardiogram (SCG) signals, integrated with a microcontroller module with Bluetooth wireless connectivity. We also created a custom printed circuit board (PCB) to integrate all the sensors into a compact design. Then, flexible housing for the electronic components was 3D printed using thermoplastic polyurethane (TPU). In addition, we developed peak detection algorithms and filtering programs to analyze the recorded cardiac signals. Our preliminary results show that the device can record all three signals in real-time. Initial results for signal interpretation come from a recurrent neural network (RNN) based machine learning algorithm, Long Short-Term Memory (LSTM), which is used to monitor and identify key features in the ECG data. The next phase of our research will include cross-examination of all three sensor signals, development of machine learning algorithms for PCG and SCG signals, and continuous improvement of the wearable device

커프리스 방식의 착용형 연속 혈압 모니터링 시스템에 관한 연구

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 협동과정 바이오엔지니어링전공, 2019. 2. 김희찬.고혈압의 조기 진단과 고혈압 환자의 혈압 관리를 위해서는 일상생활에서의 지속적인 혈압 모니터링이 중요하다. 맥파전달시간 (Pulse transit time, PTT) 기반의 혈압 추정 방식이 이를 가능케 하는 방법으로 가장 각광 받고 있지만, 맥파전달시간을 측정하기 위해서는 여러 측정 장치들이 필요하여 일상 생활에서의 사용에 제약이 있으며, 또한 맥파전달시간 만을 이용한 수축기 혈압(Systolic blood pressure, SBP) 추정 능력은 부족함이 있는 것으로 알려져 있다. 본 학위 논문의 첫 번째 목적은 맥파전달시간 측정 시스템을 착용형으로 개발하여 간편하게 맥파전달시간을 측정할 수 있도록 함으로써 일상 생활 중 맥파전달시간을 이용한 연속적인 혈압 모니터링이 가능케 하는 것이다. 이를 위해 광용적맥파 (Photoplethysmogram, PPG) 와 심진도 (Seismocardiogram, SCG)를 동시에 측정하는 가슴 착용형 단일 장치를 개발하여, 심진도로부터 대동맥 판막의 열리는 시점을, 광용적맥파로부터 맥파의 도착 시점을 특정하여 맥파 전달 시간을 측정하였다. 개발된 시스템은 낮은 전력 소모와 소형의 간편한 디자인을 통해 24시간 동안 연속적으로 사용할 수 있도록 설계되었다. 측정된 생체신호로부터 추출된 맥파전달시간 및 기타 혈압 관련 변수들이 기기의 반복 착용에도 변하지 않음을 급간내상관계수(Intra-class correlation, ICC) 분석을 통해 확인하였고 (ICC >0.8), 또한 본 시스템에서 사용된 심진도가 대동맥 판막의 열리는 시점의 레퍼런스가 될 수 있는지도 심저항신호(Impedancecardiogram, ICG)와의 비교를 통해 검증하였다(r=0.79±0.14). 둘째로, 개발된 시스템을 이용하여 기존의 맥파 전달 시간만을 이용한 혈압 추정 방식을 보완하여 수축기 혈압의 추정 능력이 향상된 알고리즘을 개발하였다. 이를 위해, 심진도의 진폭과 맥파 전달 시간을 같이 사용하는 다변수 모델을 수축기 혈압 추정을 위해 제안하였고, 다양한 방법으로 유도된 혈압 변화 상황에서, 기존의 맥파전달시간 혹은 맥파도달시간 (Pulse arrival time, PAT) 만을 이용한 모델과 그 성능을 비교하였다. 또한, 제안된 모델이 간단한 교정절차를 통해 여러 사람에게 적용될 수 있는 가능성을 살펴보았고 더 나아가 일상 생활에서의 사용 가능성에 대해서도 검증하였다. 그 결과로 제안된 모델은 (1) 기존의 맥파전달시간 혹은 맥파도달시간 만을 이용한 모델보다 수축기 혈압 추정 능력 측면에서 더 우수하였고, (각각의 평균절대오차는 4.57, 6.01, 6,11 mmHg 였다.) (2) 간단한 교정절차만을 통해서 여러 사람에게 적용 되었을 때의 추정 능력이 국제 기준에 부합하였으며, (3) 일상 생활에서도 사용자의 아무런 개입이나 제약 없이 지속적인 혈압 모니터링이 가능함을 확인하였다. 결론적으로 본 연구에서 제안하는 착용형 연속 혈압 측정 시스템은 가슴에 부착하는 단일 기기 형태로 그 사용이 간편할 뿐 아니라 일상생활 중에서 맥파전달시간과 심진도의 진폭을 이용하여 향상된 수준의 연속 혈압 모니터링 성능을 제공하였는바, 이를 이용한 모바일 헬스케어 서비스의 가능성을 확인하였다.Continuous blood pressure (BP) monitoring is needed in daily life to enable early detection of hypertension and improve control of BP for hypertensive patients. Although the pulse transit time (PTT)-based BP estimation represents one of most promising approaches, its use in daily life is limited owing to the requirement of multi systems to measure PTT, and its performance in systolic blood pressure (SBP) estimation is not yet satisfactory. The first goal of this study is to develop a wearable system providing convenient measurement of the PTT, which facilitates continuous BP monitoring based on PTT in daily life. A single chest-worn device was developed measuring a photoplethysmogram (PPG) and a seismocardiogram (SCG) simultaneously, thereby obtaining PTT by using the SCG as timing reference of the aortic valve opening and the PPG as timing reference of pulse arrival. The presented device was designed to be compact and convenient to use, and to last for 24h by reducing power consumption of the system. The consistency of BP related parameters extracted from the system including PTT between repetitive measurements was verified by an intra-class correlation analysis, and it was over 0.8 for all parameters. In addition, the use of SCG as timing reference of the aortic valve opening was verified by comparing it with an impedance cardiogram (r = 0.79 ± 0.14). Secondly, the algorithm improving the performance of the SBP estimation was developed by using the presented system. A multivariate model using SCG amplitude (SA) in conjunction with PTT was proposed for SBP estimation, and was compared with conventional models using only PTT or pulse arrival time (PAT) in various interventions inducing BP changes. Furthermore, we validated the proposed model against the general population with a simple calibration process and verified its potential for daily use. The results suggested that (1) the proposed model, which employed SA in conjunction with PTT for SBP estimation, outperformed the conventional univariate model using PTT or PAT (the mean absolute errors were of 4.57, 6.01, and 6.11 for the proposed, PTT, and PAT models, respectively)(2) for practical use, the proposed model showed potential to be generalized with a simple calibrationand (3) the proposed model and system demonstrated the potential for continuous BP monitoring in daily life without any intervention of users or regulations. In conclusion, the presented system provides an improved performance of continuous BP monitoring in daily life by using a combination of PTT and SA with a convenient and compact single chest-worn device, and thus, it can contribute to mobile healthcare services.CONTENTS Abstract i Contents v List of Tables ix List of Figures xi List of Abbreviations xvi Chapter 1 1 General Introduction 1.1. Blood pressure 2 1.2. Pulse transit time 6 1.3. Thesis objective 12 Chapter 2 14 Development of the Wearable Blood Pressure Monitoring System 2.1. Introduction 15 2.2. System overview 17 2.3. Bio-signal instrumentation 21 2.4. Power management 24 2.5. PCB and case design 25 2.6. Software Design 27 2.7. Signal Processing 30 2.8. Experimental setup 34 2.8.1. Repeatability test 34 2.8.2. Verification of SCG-based PEP 35 2.9. Results and Discussion 38 2.9.1. Repeatability test 38 2.9.2. Verification of SCG-based PEP 40 Chapter 3 43 Enhancement of PTT based BP estimation 3.1. Introduction 44 3.2. Method 47 3.2.1. Principle of BP estimation 47 3.2.2. Subjects 49 3.2.3. Study protocol 50 3.2.4. Data collection 56 3.2.5. Data analysis 60 3.2.6. Evaluation standard 64 3.3. Results 67 3.4. Discussion 96 Chapter 4 113 Conclusion 4.1. Thesis Summary and Contributions 114 4.2. Future Direction 116 Bibliography 118 Abstract in Korean 128Docto

Wearable and Nearable Biosensors and Systems for Healthcare

Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices

Encapsulation of implantable microsensors

Heart function monitoring by attaching an accelerometer directly to the heart ventricle has been established as an effective way of diagnosing ischemia. The method holds a number of advantages over conventional monitoring techniques: high specificity and accuracy surpassing that of electrocardiography, and the ability to conduct non-stop monitoring unlike x-ray imaging. To this date, the drawback has been that the accelerometer-based devices have been too large to be used in the postoperative period, when the patient’s chest is closed. This period is of great interest.The PhD project has focused on developing a heart monitoring device intended to be used on patients recovering from a Coronary Artery Bypass Graft. The device is intended to be used during surgery and for the subsequent recovery period (3-5 days). The project has employed commercial 3-axis accelerometers.This PhD project has contributed to four different generations of devices, each one featuring incremental improvements. The first generation validated the concept, the second outlined the form factor of the device, and the third added extra functionality and revised the form of the implant. The fourth generation device also featured a newer, more compact sensor, which in turn, allowed to further miniaturize the device and evaluate different implant shapes. This evolutionary approach allowed us to formulate testing methodology for the devices. The latest generation devices underwent tests of: leakage current according to IEC60601 standard (current below 0.01 mA), including after cyclical loading of the capsule-cable joint, pull-out force measurements, implant stability evaluation that yielded tilt of no more than 4 degrees

Characterization, Classification, and Genesis of Seismocardiographic Signals

Seismocardiographic (SCG) signals are the acoustic and vibration induced by cardiac activity measured non-invasively at the chest surface. These signals may offer a method for diagnosing and monitoring heart function. Successful classification of SCG signals in health and disease depends on accurate signal characterization and feature extraction. In this study, SCG signal features were extracted in the time, frequency, and time-frequency domains. Different methods for estimating time-frequency features of SCG were investigated. Results suggested that the polynomial chirplet transform outperformed wavelet and short time Fourier transforms. Many factors may contribute to increasing intrasubject SCG variability including subject posture and respiratory phase. In this study, the effect of respiration on SCG signal variability was investigated. Results suggested that SCG waveforms can vary with lung volume, respiratory flow direction, or a combination of these criteria. SCG events were classified into groups belonging to these different respiration phases using classifiers, including artificial neural networks, support vector machines, and random forest. Categorizing SCG events into different groups containing similar events allows more accurate estimation of SCG features. SCG feature points were also identified from simultaneous measurements of SCG and other well-known physiologic signals including electrocardiography, phonocardiography, and echocardiography. Future work may use this information to get more insights into the genesis of SCG

Advances in materials strategies, circuit designs, and informatics for wearable, flexible and stretchable electronics with medical and robotic applications

The future of medical electronics should be flexible, stretchable and skin-integrated. While modern electronics become increasing smaller, faster and energy efficient, the designs remain bulky and rigid due to materials and processing limitations. The miniaturization of health monitoring devices in wearable form resembles a significant progress towards the next-generation medical electronics. However, there are still key challenges in these wearable electronics associated with medical-grade sensing precision, reliable wireless powering, and materials strategy for skin-integration. Here, I present a series of systematic studies from materials strategies, circuit design to signal processing on skin-mounted electronic wearable devices. Several types of Epidermal Electronic Systems (EES) develop applications in dermatology, cardiology, rehabilitation, and wireless powering. For skin hydration measurement, fundamental studies of electrode configurations and skin-electrode impedance reveal the optimal sensor design. Furthermore, wireless operation of hydration sensor was made possible with direct integration on skin, and on porous substrates that collect and analyze sweats. Additionally, I present an epidermal multi-functional sensing platform that could provide a control-feedback loop through electromyogram and current stimulation; and a mechano-acoustic device that could capture vibrations from muscle, heart, and throat as diagnostic tools or human-machine interface. I developed a modularized epidermal radio-frequency energy transfer epidermal device to eliminate batteries and power cables for wearable electronics. Finally, I present a clinical study that validates a commercialized ESS on patients with nerve disorders for electromyography monitoring during peripheral nerve and spinal cord surgeries

A comparison between novel FPGA-based pad monitoring system using ballistocardiography and the conventional systems for synchronization and gating of CMRI at 3 tesla: A pilot study

This pilot pre-clinical study demonstrates the applicability of a new type of pneumatic cardiac triggering (PCT) for cardiac imaging. The pilot research compares the novel FPGA-based pad monitoring system for cardiac triggering using ballistocardiography (BCG) with conventional systems based on electrocardiography (ECG) and photoplethysmography (PPG). The implemented system enables cardiac triggering without the need to fix the sensors to the patient's body. This unique approach has the potential to reduce the preparation time for examination and the examination itself and to increase patient's comfort. The pilot pre-clinical study was conducted on 10 subjects at the Siemens Prisma 3T MRI Scanner within the CEITEC Multimodal and Functional Imaging Laboratory - Central European Institute of Technology, Masaryk University, upon the approval of the Ethics Committee. In total, 748 peaks (heart beats) were detected, with 7.347 correctly identified as true positive peaks, 140 incorrectly detected as false positive peaks, and 106 missed peaks (false negative). For all subjects, the total accuracy reached 96.31% and F1 score reached 98.18%. The applicability of the proposed BCG system was also analyzed in terms of objective (BRISQUE, NIQE, PIQE) and subjective evaluation of the images by 10 experts. The study compares images from two basic cardiac sequences - TRUE FISP (Free Induction Decay Steady-State Precession) and PSIR (Phase Sensitive Inversion Recovery) sequences. The BCG system achieves comparable results with the most frequently used and most accurate clinical ECG system used as gold standard. The results prove that the BCG signal captured by our new sensor can be used as a substitute for ECG signal during MRI exam with reliability of 97%.Web of Science84170414