무구속 센서를 이용한 생체정보의 분석: 로드셀을 이용한 영유아 심탄도 측정 및 패치형 전극을 이용한 심전도 측정

Abstract

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.