Seven years follow‐up of ballistocardiogaphy

This work serves as a method description, where ballistocardiography (BCG) and pulse waves were used to study longer term alterations of heart-vasculature system. BCG and pulse signals were recorded from one person in sitting position by using Electromechanical Film (EMFi) sensors during 7 years time interval. ECG, BCG, carotid pulse (CP) signal from the right side of the neck near the carotid artery and the left ankle pulse wave (in five recordings) were recorded from one person. Duration of the signal components according to R wave from the ECG, amplitudes and spectral components of the signals were studied. Pulse wave velocity (PWV) values were calculated in order to compare aortic blood pressure (BP) to values obtained with commercial Omron BP measurement device. The time domain properties of CP and BCG signals during seven years time remained fairly stable within the same person. Also when the signals were estimated visually in spectral domain from the seat BCG and especially from the CP, no major differences were found. Minor alterations in the frequency of the spectral spikes may be due to heart rate changes between measurements or due to slight changes in the arterial elasticity having an influence to the spectral traces. Obtained PWV values followed closely BP changes measured with Omron BP measurement device

Carotid and radial pulse feature analysis with EMFi sensor

The purpose of this work is to show the potential of Electromechanical Film (EMFi) sensor in vascular elasticity studies when pulse wave features from carotid pulse (CP) and radial pulse are studied. ECG, seat ballistocardiogram (BCG) and pulse signals from the limbs and CP were recorded from 48 working aged men in sitting position. Duration and amplitudes of the signal components from the ballistic seat signal, CP and radial pulse according to R wave of the ECG were studied. Several calculated parameters used to obtain vasculature stiffness information were compared with Bland-Altman (BA) plots and with Pearson correlation in order to study, whether CP and radial pulse give consistent information about vascular elasticity. Results from the BA plots and Pearson correlation show that elastic information obtained from the CP and radial pulse signals clearly differ from each other. The elasticity changes along the arterial tree seen in local pulse signals reflect also to the form of the seat BCG signal

Development of a bed-based nighttime monitoring toolset

Doctor of PhilosophyDepartment of Electrical and Computer EngineeringSteven WarrenA movement is occurring within the healthcare field towards evidence-based or preventative care-based medicine, which requires personalized monitoring solutions. For medical technologies to fit within this framework, they need to adapt. Reduced cost of operation, ease-of-use, durability, and acceptance will be critical design considerations that will determine their success. Wearable technologies have shown the capability to monitor physiological signals at a reduced cost, but they require consistent effort from the user. Innovative unobtrusive and autonomous monitoring technologies will be needed to make personalized healthcare a reality. Ballistocardiography, a nearly forgotten field, has reemerged as a promising alternative for unobtrusive physiological monitoring. Heart rate, heart rate variability, respiration rate, movement, and additional hemodynamic features can be estimated from the ballistocardiogram (BCG). This dissertation presents a bed-based nighttime monitoring toolset designed to monitor BCG, respiration, and movement data motivated by the need to quantify the sleep of children with severe disabilities and autism – a capability currently unmet by commercial systems. A review of ballistocardiography instrumentation techniques (Chapter 2) is presented to 1) build an understanding of how the forces generated by the heart are coupled to the measurement apparatus and 2) provide a background of the field. The choice of sensing modalities and acquisition hardware and software for developing the unobtrusive bed-based nighttime monitoring platform is outlined in Chapters 3 and 4. Preliminary results illustrating the system’s ability to track physiological signals are presented in Chapter 5. Analyses were conducted on overnight data acquired from three lower-functioning children with autism (Chapters 6 and 9) who reside at Heartspring, Wichita, KS, where results justified the platform’s multi-sensor architecture and demonstrated the system’s ability to track physiological signals from this sensitive population over many months. Further, this dissertation presents novel BCG signal processing techniques – a signal quality index (Chapter 7) and a preprocessing inverse filter (Chapter 8) that are applicable to any ballistocardiograph. The bed-based nighttime monitoring toolset outlined in this dissertation presents an unobtrusive, autonomous, robust physiological monitoring system that could be used in hospital-based or personalized, home-based medical applications that consist of short or long-term monitoring scenarios

새로운 심탄도 계측 시스템의 응용 -연속혈압 추정과 생체인식

학위논문 (박사)-- 서울대학교 대학원 : 협동과정 바이오엔지니어링전공, 2014. 8. 김희찬.심탄도 (Ballistocardiogram)는 심박에 동기되어 발생하는 우리 몸의 미세한 진동을 측정한 신호이다. 비침습적으로 심혈관계의 활동을 관찰할 수 있다는 장점 때문에, 20세기 초반에 심탄도의 해석에 대한 많은 연구가 이루어졌다. 그러나 초음파 기기 등 심혈관계 관련 질병들을 진단할 수 있는 새로운 기술들이 개발되면서 상대적으로 실용적이지 못한 특성을 가진 심탄도에 대한 관심은 1970년대 이후에 급격히 줄어들었다. 새로운 센서들의 등장과 마이크로프로세서, 신호처리 기술들의 발전에 힘입어 심탄도 연구는 다시 활기를 띠고 있다. 그러나 이러한 발전들에도 불구하고 심탄도는 의자나 침대 등 상당한 부피를 차지하는 사물을 이용하여 계측되고, 분석을 위해서는 동기화 된 심전도가 동시에 측정되어야 하는 등 측정상의 번거로움이 있다. 또한, 심탄도는 개인 간에는 물론 한 개인에게서도 파형에 많은 변이를 보여 신호의 일관된 해석에 어려움이 있다. 본 학위논문에서는, 이러한 측정 측면과 신호처리 측면에서 현 심탄도 응용의 한계점을 극복할 수 있는 방안을 마련하여, 심탄도의 실질적인 활용 범위를 더욱 확장할 수 있는 방안에 대해 연구하였다. 우선, 심탄도를 심전도와 동시에 무구속적으로 잴 수 있는 필름기반의 패치타입 센서를 개발하였다. 압전소자의 양면에 복수개의 전극을 패터닝하고 각각의 전극에 독립된 기능을 부여해 회로에 연결함으로써 필름 한 장으로 물리적인 신호 (심탄도)와 전기적인 신호(심전도)의 동시 측정이 가능하게 하였다. 센서를 가슴에 부착하였을 때 심전도의 특징적인 R 피크과 심탄도의 특징적인 J 피크를 확인하여 기능을 확인할 수 있었으며, 추가적으로 R-J 간격이 수축기 혈압과 음의 상관관계를 가짐을 이용하여 개발된 센서로 혈압을 추정할 수 있었다. 센서를 통해 예측한 수축기 혈압 오차의 평균값과 표준편차는 각각 -0.16 mmHg와 4.12mmHg으로, 미국과 영국의 혈압계 가이드라인을 모두 만족시킬 수 있었다. 다음으로, 심탄도의 변이적 특성을 새로운 생체인식 기법으로 발전시키는 방안에 대한 연구를 진행하였다. 이를 위하여 심탄도 한 파형 내의 특이점들을 기반으로 특징 벡터를 추출하고 기계학습을 통해 특징들의 변이를 개인들 간의 변이와 한 개인 내에서의 변이로 구분 하였다. 추출된 특징들을 이용하여 35명의 피험자들에게 실험해 본 결과, 단일 심박신호로는 90.20%의 확률로 개개인을 구분할 수 있었으며 7개의 연속된 심박신호로는 98%이상의 성능을 낼 수 있었다. 또한 약 일주일 간격을 두고 반복하여 측정한 데이터와 운동을 통해 심박수가 변화된 데이터의 적용을 통해서 심탄도를 이용한 생체인식 방법의 재현성을 확인할 수 있었다.Ballistocardiogram (BCG) is a recording of body movement, which is generated in synchronous with the heartbeats. Studies on BCG were a field of intense research in the past decades, since it could provide a non-invasive means to monitor cardiovascular activities. However, such interests have slowly diminished after 1970s due to its impractical characteristics compared to the new technologies (i.e. echocardiography) that diagnose cardiovascular system. Studies on BCG are now on its resurgence era, with advent of new sensors, microprocessor, and the signal processing techniques. Notable differences of todays BCG researches, compared to the past ones, are on the emergence of non-diagnostic applications of BCG. Sleep analysis, heartbeat detection and the estimation of pre-ejection time are the few examples of BCG applications that were previously non-existent. Despite these advancements, however, practical usage of BCG has yet to become reality. One reason for this is in its difficulties in instrumentation. In a number of researches, BCGs are often recorded with a sensor attached to bulky objects, for example bed or chair. Also, a synchronously measured electrocardiogram (ECG) is required for the accurate analysis of BCG, therefore, increases the system complexity. Morphological variability of BCG is another limiting factor. Waveforms of BCG are reported to vary among subjects and even in a same person. Such characteristics of BCG impose difficulties in its consistent interpretation and in drawing meaningful information. In this dissertation, we first propose a sensor, namely BE-patch, which can record both the BCG and ECG using a ferro-electret film. As the sensor is thin and flexible and features reduced complexity, it suits for wearable applications in terms both of user compliance and power consumption. The fabrication method of BE-patch and its application in blood pressure estimation is reported in Chapter 2. Using the time delay of R-peak of ECG and J-peak of BCG (so-called, R-J interval), which showed the negative relationship with changes in blood pressure, the beat-by-beat systolic blood pressure (SBP) is estimated. The mean error of the estimated SBP and its standard deviation were ?0.16 and 4.12 mm Hg, respectively and their performance met both the Association for the Advancement of Medical Instrumentation and the British Hypertension Society guidelines. In Chapter 3, the variable aspect of BCG is re-analyzed to develop a biometric application. Waveforms of BCG were described using features and their variability was separated to the inter-individual and the intra-individual variations by applying supervised learning algorithms. The result showed the potential utility of BCG as biometric signal, by achieving identification accuracy of 90.20% using only a cycle of BCG. Then identification increased to 98% when multiple beats were used, and reproducible with time and changes in heart-rates. In Chapter 4, the thesis work is summarized, and future directions to further develop the proposed sensor and applications are discussed.Abstract i List of Tables v List of Figures vi 1. Introduction １ 1.1. History of BCG Research １ 1.2. Recent Advances ７ 1.3. Goal of Thesis Work ９ 2. Blood Pressure Estimation １３ 2.1. Introduction １３ 2.2. Principles of BP Estimation １６ 2.3. Methods ２１ 2.4. Results and Discussions ２６ 2.5. Conclusion ２８ 3. Biometric Application ２９ 3.1. Introduction ２９ 3.2. Methods ３９ 3.3. Results and Discussions ４８ 3.4. Conclusion ５６ 4. Conclusions and Discussions ５７ Bibliography ６５ 국문초록 ７１Docto

Physiological Information Analysis Using Unobtrusive Sensors: BCG from Load-Cell Based Infants' Bed and ECG from Patch Electrode

학위논문 (박사)-- 서울대학교 대학원 : 바이오엔지니어링전공, 2016. 8. 박광석.The aging population, chronic diseases, and infectious diseases are major challenges for our current healthcare system. To address these unmet healthcare needs, especially for the early prediction and treatment of major diseases, acquiring physiological information of different types has emerged as a promising interdisciplinary research area. Unobtrusive sensing techniques are instrumental in constructing a routine health management system, because they can be incorporated in daily life without confining individuals or causing any discomfort. This dissertation is dedicated to summarizing our research on monitoring of cardiorespiratory activities by means of unobtrusive sensing methods. Ballistocardiography and electrocardiography, which record the activity of the cardiorespiratory system with respect to mechanical or electrical characteristics, are both being actively investigated as important physiological signal measurement that provide the information required to monitor human health states. This research was carried out to evaluate the feasibility of new application methods of unobtrusive sensing that not been investigated significantly in previous investigations. We also tried to incorporate improvement essential for bringing these technologies to practical use. Our first device is a non-confining system for monitoring the physiological information of infants using ballistocardiography technology. Techniques to observe continuous biological signals without confinement may be even more important for infants since they could be used effectively to detect respiratory distress and cardiac abnormalities. We also expect to find extensive applications in the field of sleep research for analyzing sleep efficiency and sleep patterns of infants. Specifically, the sleep of infants is closely related to their health, growth, and development. Children who experience abnormal sleep and activity rhythms during their early infantile period are more prone to developing sleep-related disorders in late childhood, which are also more difficult to overcome. Therefore, studying their sleep characteristics is extremely important. Although ballistocardiography technology seems to represent a possible solution to overcome the limitations of conventional physiological signal monitoring, most studies investigating the application of these methods have focused on adults, and few have been focused on infants. To verify the usefulness of ballistocardiogram (BCG)-based physiological measurement in infants, we describe a load-cell based signal monitoring bed and assess an algorithm to estimate heartbeat and respiratory information. Four infants participated in 13 experiments. As a reference signal, electrocardiogram (ECG) and respiration signals were simultaneously measured using a commercial device. The proposed automatic algorithm then selected the optimal sensor from which to estimate the heartbeat and respiratory information. The results from the load-cell sensor signals were compared with those of the reference signals, and the heartbeat and respiratory information were found to have average performance errors of 2.55% and 2.66%, respectively. We believe that our experimental results verify the feasibility of BCG-based measurements in infants. Next, we developed a small, light, ECG monitoring device with enhanced portability and wearability, with software that contains a peak detection algorithm for analyzing heart rate variability (HRV). A mobile ECG monitoring system, which can assess an individuals condition efficiently during daily life activities, could be beneficial for management of their health care. A portable ECG monitoring patch with a minimized electrode array pad, easily attached to a persons chest, was developed. To validate the devices performance and efficacy, signal quality analysis in terms of robustness under motion, and HRV results obtained under stressful conditions were assessed by comparing the developed device with a commercially available ECG device. The R-peak detection results obtained with the device exhibited a sensitivity of 99.29%, a positive predictive value of 100.00%, and an error of 0.71%. The device also exhibited less motional noise than conventional ECG recording, being stable up to a walking speed of 5 km/h. When applied to mental stress analysis, the device evaluated the variation in HRV parameters in the same way as a reference ECG signal, with very little difference. Thus, our portable ECG device with its integrated minimized electrode patch carries promise as a form of ECG measurement technology that can be used for daily health monitoring. There is currently an increased demand for continuous health monitoring systems with unobtrusive sensors. All of the experimental results in this dissertation verify the feasibility of our unobtrusive cardiorespiratory activity monitoring system. We believe that the proposed device and algorithm presented here are essential prerequisites toward substantiating the utility of unobtrusive physiological measurements. We also expect this system can help users better understand their state of health and provide physicians with more reliable data for objective diagnosis.Chapter 1. Introduction 1 1.1. Cardiorespiratory signal and its related physiological information 2 1.1.1. Electrocardiogram 2 1.1.2. Ballistocardiogram 3 1.1.3. Respiration 4 1.1.4. Heart rate and breathing rate 5 1.1.5. Variability analysis of heart and respiratory rate 5 1.2. Unobtrusive sensing methods for continuous physiological monitoring 6 1.3. Outline of the dissertation 9 Chapter 2. Development of sensor device for unobtrusive physiological signal measurement 13 2.1. Unobtrusive BCG measurement device for infants health monitoring 13 2.1.1. Specifications of the device 17 2.1.2. Signal processing in hardware 18 2.1.3. Performance of the device 21 2.2. Unobtrusive ECG measurement device for health monitoring in daily life 25 2.2.1. Specifications of the device 26 2.2.2. Signal processing in hardware 28 2.2.3. Performance of the device 30 Chapter 3. Development of algorithm for physiological information analysis from unobtrusively measured signal 35 3.1. Algorithm for automatically analyzing unobtrusively measured BCG signal 35 3.1.1. Process flow of the algorithm 36 3.1.2. Performance evaluation 47 3.2. Algorithm for automatically analyzing unobtrusively measured ECG signal 57 3.2.1. Process flow of the algorithm 57 3.2.2. Performance evaluation 60 3.3. HRV analysis for processing unobtrusively measured signals 63 3.3.1. Optimum HRV algorithm selection in data missing simulation 64 3.3.2. Stress assessment using HRV parameters 67 Chapter 4. Discussion 71 Chapter 5. Conclusion 79 Reference 81 Abstract in Korean 89 Appendix 93Docto

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

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

A wearable heart monitor at the ear using ballistocardiogram (BCG) and electrocardiogram (ECG) with a nanowatt ECG heartbeat detection circuit

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 132-137).This work presents a wearable heart monitor at the ear that uses the ballistocardiogram (BCG) and the electrocardiogram (ECG) to extract heart rate, stroke volume, and pre-ejection period (PEP) for the application of continuous heart monitoring. Being a natural anchoring point, the ear is demonstrated as a viable location for the integrated sensing of physiological signals. The source of periodic head movements is identified as a type of BCG, which is measured using an accelerometer. The head BCG's principal peaks (J-waves) are synchronized to heartbeats. Ensemble averaging is used to obtain consistent J-wave amplitudes, which are related to stroke volume. The ECG is sensed locally near the ear using a single-lead configuration. When the BCG and the ECG are used together, an electromechanical duration called the RJ interval can be obtained. Because both head BCG and ECG have low signal-to-noise ratios, cross-correlation is used to statistically extract the RJ interval. The ear-worn device is wirelessly connected to a computer for real time data recording. A clinical test involving hemodynamic maneuvers is performed on 13 subjects. The results demonstrate a linear relationship between the J-wave amplitude and stroke volume, and a linear relationship between the RJ interval and PEP. While the clinical device uses commercial components, a custom integrated circuit for ECG heartbeat detection is designed with the goal of reducing power consumption and device size. With 58nW of power consumption, the ECG circuit replaces the traditional instrumentation amplifier, analog-to-digital converter, and signal processor with a single chip solution. The circuit demonstrates a topology that takes advantage of the ECG's characteristics to extract R-wave timings at the chest and the ear in the presence of baseline drift, muscle artifact, and signal clipping.by David Da He.Ph.D

Methods for Doppler Radar Monitoring of Physiological Signals

Unobtrusive health monitoring includes advantages such as long-term monitoring of rarely occurring conditions or of slow changes in health, at reasonable costs. In addition, the preparation of electrodes or other sensors is not needed. Currently, the main limitation of remote patient monitoring is not in the existing communication infrastructure but the lack of reliable, easy-to-use, and well-studied sensors.The aim of this thesis was to develop methods for monitoring cardiac and respiratory activity with microwave continuous wave (CW) Doppler radar. When considering cardiac and respiration monitoring, the heart and respiration rates are often the first monitored parameters. The motivation of this thesis, however, is to measure not only rate-related parameters but also the cardiac and respiratory waveforms, including the chest wall displacement information.This dissertation thoroughly explores the signal processing methods for accurate chest wall displacement measurement with a radar sensor. The sensor prototype and measurement setup choices are reported. The contributions of this dissertation encompass an I/Q imbalance estimation method and a nonlinear demodulation method for a quadrature radar sensor. Unlike the previous imbalance estimation methods, the proposed method does not require the use of laboratory equipment. The proposed nonlinear demodulation method, on the other hand, is shown to be more accurate than other methods in low-noise cases. In addition, the separation of the cardiac and respiratory components with independent component analysis (ICA) is discussed. The developed methods were validated with simulations and with simplified measurement setups in an office environment. The performance of the nonlinear demodulation method was also studied with three patients for sleep-time respiration monitoring. This is the first time that whole-night measurements have been analyzed with the method in an uncontrolled environment. Data synchronization between the radar sensor and a commercial polysomnographic (PSG) device was assured with a developed infrared (IR) link, which is reported as a side result.The developed methods enable the extraction of more useful information from a radar sensor and extend its application. This brings Doppler radar sensors one step closer to large-scale commercial use for a wide range of applications, including home health monitoring, sleep-time respiration monitoring, and measuring gating signals for medical imaging