Wenxi Chen
Associate Professor
Xin Zhu
Assistant Professor
Tang Shunqing
Visiting Researcher
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Wenxi Chen Associate Professor |
Xin Zhu Assistant Professor |
Tang Shunqing Visiting Researcher |
BIT lab is seeking to 1. develop diversified modalities for daily monitoring of vital signs persistently by making use of mathematical means and various physical/chemical principles, 2. perform physiological modeling and data mining to reveal statistical links between the incidence of various chronic diseases and longterm dynamics of health condition, 3. construct an integrated infrastructure, "SHIP" (scalable healthcare integrated platform) for lifelong health promotion and seamless coverage of the life care cycle from womb to tomb, by utilizing the latest ICT achievement 4. and foster a new discipline “Metrology of Health” or “Healthology”.
In AY 2011, Prof. Chen's research activities continued focusing on the ICT-based healthcare domain to pursue a systematic total solution for daily monitoring of vital signs and health management. Prof. Chen conducted several projects. These studies headed towards a system development, including a series of instrumentation for seamless and persistent monitoring of vital signs without disturbing subjects in daily life environment, and an Internet-based infrastructure. Cooperative studies with two local nursing homes for the elderly were implemented to collect elderly data and to assess the system performance through field trial. Various data mining algorithms were developed to objectively characterize the subject’s health condition change. Ph.D. candidate Ming Huang won the Encouragement Prize for Recovery of the paper competition of JpCOMPEmbs11 organized by IEEE Japan Chapter of Engineering in Medicine and Biology Society in 2011 that title is “Inverse Modeling for Heat Conduction Problem in Human Abdominal Phantom”.
Prof. Zhu's researches were focused on computer simulation of heart and biomedical signal processing. In AY2011, Prof. Zhu conducted the Grants-In-Aid for Scientific Research (No. 21500297) of deriving right precordial leads in the higher intercostal spaces from standard 12 lead ECG for the diagnosis of Brugada syndrome. He also participated the researches in automatic detection of atrial fibrillation, and the longterm monitoring of systolic blood pressure. Two master students, Mr. Takano and Ms Tsunoda graduated in 2012 spring under the supervision of Prof. Zhu.
A patent by Prof Chen and Prof Zhu was registered (No.4863047) in Japan.
Ying Chen and Wenxi Chen. Long-term Tracking of a Patient's Health Condition Based on Pulse Rate Dynamics during Sleep. Annals of Biomedical Engineering, 39(12):2922-2934, 2011.
This article proposed a method to track the changes in health condition of a patient after coronary stenting over seven successive seasons based on daily pulse rate (PR). The pulse signal was recorded by an unconstrained monitoring system during sleep. Seasonal PR dynamics were evaluated by both linear measures, including time domain and frequency domain indexes, and nonlinear measures such as noise limit (NL), detection rate (DR), sample entropy (SampEn), and Poincare plots. NL and DR were derived using the noise titration method. Significant changes in seasonal indexes of the patient were evaluated statistically. The results show that an overall downward trend of the PR dynamics corresponds to changes in the patient’s health condition that began in winter and developed in spring and worsened most seriously in the following summer. The monthly and seasonal orbits of PR nonlinearity of the patient were plotted and observed to follow different trajectory compared with a healthy subject. These results indicate the feasibility of applying dynamics of PR as a potential prognostic tool for detecting early changes in a patient’s health condition and also for understanding the temporal transition of health condition over a long-term period.
Weijia Lu, Daming Wei, Xin Zhu, and Wenxi Chen. A computer model based on real anatomy for electrophysiology study. Advances in Engineering Software,, 42(7):463-476, 2011.
In order to investigate the pattern of wave propagation on atria in both sinus rhythm and arrhythmia, we constructed a computational model based on real anatomy. The original anatomic data which encompasses morphological and geometrical knowledge was created from a whole-body set of 2 mm interval magnetic resonance imaging (MRI) images of a male volunteer and represented in stl format. The anatomic data was firstly discretized into spherical cells in equal size. Then the anisotropy of conduction velocity (CV) and conductivity were introduced into this model in definition of special conduction system. Nygren cell model was adopted to calculate the action potential (AP) waveform of each cell. Restitution of AP duration (APD) and it on CV were also introduced in this model. The pattern of activation propagation could be investigated on a perspective 3D scene after the excitation simulation. The isochronal map and the electrocardiograms (ECGs) were also produced. In this study, We used two experiments to verify this model as well as demonstrated its application in electrophysiological study: one was conducted under sinus rhythm, while in the other, two trains of boost pacings alternatively acted on the vena cava and the opening of the pulmonary vein. An identical excitation pattern described in previous studies was observed in first experiment. While in the second experiment, a foci triggered atrial fibrillation was seen on the epicardial surface.
Ming Huang and Wenxi Chen. Theoretical study on the inverse mod eling of deep body temperature measurement. Physiological Measurement, 33(3):429-443, 2012.
We evaluated the theoretical aspects of monitoring the deep body temperature distribution with the inverse modeling method. A two-dimensional model was built based on anatomical structure to simulate the human abdomen. By integrating biophysical and physiological information, the deep body temperature distribution was estimated from cutaneous surface temperature measurements using an inverse quasilinear method. Simulations were conducted with and without the heat effect of blood perfusion in the muscle and skin layers. The results of the simulations showed consistently that the noise characteristics and arrangement of the temperature sensors were the major factors affecting the accuracy of the inverse solution. With temperature sensors of 0.05 °C systematic error and an optimized 16-sensor arrangement, the inverse method could estimate the deep body temperature distribution with an average absolute error of less than 0.20 °C. The results of this theoretical study suggest that it is possible to reconstruct the deep body temperature distribution with the inverse method and that this approach merits further investigation.
Linlin Jiang, Zunyi Tang, Zhaoqin Liu, Wenxi Chen, Kei-ichiro Kitamura, and Tetsu Nemoto. Automatic Sleep Monitoring System for Home Healthcare. In Proc. of the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2012), pages 894-897, Hong Kong and Shenzhen, China, August 31-Sept. 4 2011.
In this paper, we present an automatic and realtime sleep monitoring system for home healthcare. The basic system consists of sensor boards, bedside boxes and a group of servers with various functions for analyzing sleep data and reporting sleep qualities of users. The sensor board is installed beneath a pillow to measure pressure change signal during sleep. The bedside box digitizes and transmits the signal to the servers. The system is different from conventional sleep monitoring devices used in a hospital, whose sensor is nonintrusive and easy-to-use that any person can use it at home. Furthermore, it provides a web-based interactive platform for users to analyze, manage and visualize their sleep data. These functions are evaluated by dozens of persons at different age groups over three months, and they are confirmed useful not only for a doctor who is responsible for checking his/her patient’s daily sleep pattern, but also useful for self-care. It is of great application potential in home healthcare.
Hsien Che Hung, Daming Wei, and Wenxi Chen. A CMOS Analog Front End Design in Multi-Lead ECG System for Ubiquitous Healthcare. In Proc. of the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2012), pages 281-284, Hong Kong and Shenzhen, China, 2011. CDROM.
This paper presents design considerations for implementation of synthesized 12-lead ECG. The Analog Front End (AFE) chip has designed in a 0.35 μ m 2P3M Global Foundries CMOS technology, dissipating under 1 mW from a 3.3V single end supply. The chip is a build-in implementation that applies a Wilson Central Terminal (WCT) and Driven Right Leg (DRL). An extendible design is proposed to make it easy that implementation from 2-lead ECG circuit to 4-lead or even 12-lead ECG. The circuit is achieved the chip die size, with good performance for multi-lead ECG systems.
Xin Zhu, Wenxi Chen, Kei-ichiro Kitamura, and Tetsu Nemoto. Comparison of Pulse Rate Variability Indices Estimated from Pressure Signal and Photoplethysmogram. In Proc. of the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2012), pages 867-870, Hong Kong and Shenzhen, China, August 31Sept. 4 2011.
In this research, we proposed a method to estimate the time- and frequencydomain indices of pulse rate variability by using pulse waveforms separated from pressure signals measured during sleep. The pulse waveform is extracted from pressure signals based on wavelet transform, and heart beats are detected by an adaptive pulse template method. Through an evaluation based on 13 healthy subjects’pressure and photoplethysmography signals measured simultaneously during sleep, we found that the time- and frequency-domain indices of pulse rate variability estimated from pressure signals have a high correlation with those estimated from photoplethysmography signals. It suggests that pressure signals may serve as a convenient and low-cost tool to estimate pulse rate variability during sleep.
Xin Zhu, Wenxi Chen, Tetsu Nemoto, and Kei-ichiro Kitamura. Adaptive Pulse Template Method for Accurate Heart Beat Detection from Pressure Signals Measured during Sleep. In Proc. of iCAST 2011: 3rd International Conference on Awareness Science and Technology, pp. Technology, pp. ?-?, page CDROM, Dalian, China, Sept 27-30 2011.
We proposed an adaptive pulse template method for accurate detection of heart beat from pressure signals measured during sleep. 13 subjects' pressure and photoplethysmography signals were measured during sleep for evaluation. Compared with our previous heart beat detection method based on differential filtering, the adaptive pulse template method has a higher positive predictivity 94.46% and a satisfying sensitivity 94.08% for the detection of heart beat in the pulse waveform extracted from pressure signals. The accurate detection of heart beat can improve the estimation accuracy of pulse rate variability analysis.
Wenxi Chen, Hiroo Watanabe, Xin Zhu, Kei-ichiro Kitamura, and Tetsu Nemoto. Detection of daily lifestyle change from pulse rate measured during sleep. In Proc. of the International Conference on Health Informatics (HealthInf2012), pages 358-361, Vilamoura, Algarve, Portugal, Feb 1-4 2012.
This study aims at detecting changes in daily lifestyle by using pulse rate measured during sleep. A convenient system for pulse rate measurement during sleep and an algorithm for detection of lifestyle changes were developed in this study. The data collection system consists of a home unit and a database server. The home unit includes a Bluetooth-enabled SpO2 sensor and a relay station. The sensor measures pulse rate (PR) and SpO2 beat-by-beat. The relay station receives the measured PR and SpO2 data via Bluetooth connection with the sensor, and then transmits these data to the database server through Internet automatically. The database server manages the data and performs data analysis. Daily PR data were preprocessed to suppress spike-like noise and movement artefact. Changes in daily lifestyle were detected by a dynamic time warping (DTW) algorithm. Vital data were collected from a healthy college student during daily sleep time over one year, and were used to examine the prototype system. The results showed that unusual or irregular events, such as too much alcohol drink, physical illness and mental stress, could be identified successfully. The system seems promising in application of health care and management under daily life environment.
Ying Chen and Wenxi Chen. Nonlinear Analysis of Long-term Pulse Rate Variability Using Noise Titration Method. In Proc. of the 50th Annual Conference of Japanese Society for Medical and Biological Engineering, page CDROM, Tokyo, Japan, Apr 29-May 1 2011.
This study analyzes seasonal features of pulse rate chaos in both healthy and unhealthy subjects. Analytical methods, such as numerical titration, sample entropy and spectral analysis, were used to detect and estimate the seasonal fluctuations in chaotic attributes, complexity and nonlinearity of pulse rate. Chaotic feature analyses are based on pulse rate data collected over one year from a healthy male and a male patient after coronary stenting. The results show that the mean level of pulse rate chaos in the healthy subject is lowest in winter (values of NL, DR, and SampEn are 8.1 ± 0.30.02, separately) and highest in summer (corresponding values are 9.9 ± 0.6postoperative individual has a relatively lower mean chaotic dynamics that is least active in autumn (7.1 ± 0.5active in winter (7.7 ± 0.4(9.1 ± 0.7distinct seasonal autonomic and cardiac activities in both good health and disease. These findings may also pave the way for developing new approaches to monitoring long-term HRV and interpreting HRV chaotic features.
Ming Huang, Wenxi Chen, Kei-ichiro Kitamura, and Tetsu Nemoto. Spatial Covariance-Based Inverse Modeling for Heat Conduction in Human Abdominal Phantom. In Proc. of the 50th Annual Conference of Japanese Society for Medical and Biological Engineering, page CDROM, Tokyo, Japan, Apr 29-May 1 2011.
This study aims to evaluate the feasibility theoretically in monitoring the deep body temperature distribution using inverse modeling method. In this study, a two dimensional inverse model of human abdominal phantom was built by integrating the biophysical and geometric information. We could estimate the temperature values of the different parts inside the model from the temperature values of the skin surface. The statistical a priori information of the temperature spatial covariance is assumed to be known, and is used in the regularization of the inverse problem. The quasi linearity is invoked to search for the most suitable solutions iteratively. A fast and stable convergence for the best solution could be acquired. The absolute error of the solution is kept within an acceptable level. Through this inverse model, a physiology based study about the inverse solution of deep body temperature can be conducted.
Ying Chen and Wenxi Chen. Detection of Circaseptan Rhythm and the "Monday Effect" from Long-term Pulse Rate Dynamics. In Proc. of the 33rd Annual International Conference of the IEEE Engineering in Medicine and BiologySociety (EMBC11), pages 3780-3783, Boston, USA, August 30-Sept. 3 2011.
This study proposes a methodology to detect circaseptan (CS) rhythm in pulse rate (PR) data and to investigate the "Monday effect" in CS rhythm. Daily PR was collected from a middle-aged healthy working woman over one year. PR, SDNN index and sample entropy (SampEn) were chosen as the indexes of PR dynamics. In order to avoid interference from other biorhythms, ensemble empirical mode decomposition (EEMD) method was used to decompose the original PR series into multiple components. And the single cosinor method was applied to fit the detrended component signal. An optimal 7-day period was found in all indexes (P = 0.0103, P = 0.0133, P = 0.0122 for PR, SDNN index and SampEn, separately) that demonstrated an underlying CS rhythm. In the following study, a statistical Monday decrease in PR dynamics was observed especially significant in the detrended signal. The results suggested a direct relationship between the “ Monday effect ” and the CS variation, and also indicated a cardiac susceptibility to the social activities. The findings in CS periodicity and the “ Monday effect ” may help understand the human's biorhythm, provide evidence for preventive and optimized timing treatment, and also serve to daily health management.
Zhaoqin Liu, Linlin Jiang, Wenxi Chen, Kei-ichiro Kitamura, and Tetsu Nemoto. Characterization of body movement in a female before and after parturition. In Proc. of the 50th Annual Conference of Japanese Society for Medical and Biological Engineering, page CDROM, Tokyo, Japan, Apr 29-May 1 2011.
The purpose of this study was to characterize the different features of body movements for females before and after parturition. Body movement signal was measured by a piezoelectric sensor board which was deployed on the abdominal position beneath a mattress during sleep to monitor pressure changes around abdominal area. Body movement epochs were detected by an innovative algorithm based on Hilbert transform. Data were collected from two healthy pregnant females during sleep for 7 weeks before parturition and 6 weeks after parturition. The pressure signal was used to determine the duration and time interval of maternal movements. Characteristics of the detected body movements before and after parturition were investigated through their proportion. The results showed that before and after parturition, the body movement which features as 0 1 min in interval and 0 6 sec in duration has significant difference statistically. It is considered that these differences are highly correlated with the prenatal activities.
Zhaoqin Liu, Linlin Jiang, Wenxi Chen, and Kei-ichiro Kitamura amd Tetsu Nemoto. Characterization of Maternal Body Movement During Sleep Before and After Parturition. In Proc. of the 33rd Annual International Conference of the IEEE Engineering in Medicine and BiologySociety (EMBC11), pages 1503-1506, Boston, USA, August 30-Sept. 3 2011.
The purpose of this study was to characterize the different features of body movements for females before and after parturition. Body movement signal was measured by a piezoelectric sensor board which was deployed on the abdominal position beneath a mattress during sleep to monitor pressure changes around abdominal area. Body movement epochs were detected by an innovative algorithm based on Hilbert transform. Data were collected from two healthy pregnant females during sleep for 7 weeks before parturition and 6 weeks after parturition. The pressure signal was used to determine the duration and time interval of maternal movements. Characteristics of the detected body movements before and after parturition were investigated through their proportion. The results showed that before and after parturition, the body movement which features as 0 1 min in interval and 0 6 sec in duration has significant difference statistically. It is considered that these differences are highly correlated with the prenatal activities.
Ming Huang and Wenxi Chen. Inverse Modeling for Heat Conduction Problem in Human Abdominal Phantom. In Proc. of the 33rd Annual International Conference of the IEEE Engineering in Medicine and BiologySociety (EMBC11), pages 1367-1370, Boston, USA, August 30-Sept. 3 2011.
Noninvasive methods for deep body temperature measurement are based on the principle of heat equilibrium between the thermal sensor and the target location theoretically. However, the measurement position is not able to be definitely determined. In this study, a 2-dimensional mathematical model was built based upon some assumptions for the physiological condition of the human abdomen phantom. We evaluated the feasibility in estimating the internal organs temperature distribution from the readings of the temperature sensors arranged on the skin surface. It is a typical inverse heat conduction problem (IHCP), and is usually mathematically ill-posed. In this study, by integrating some physical and physiological a-priori information, we invoked the quasi-linear (QL) method to reconstruct the internal temperature distribution. The solutions of this method were improved by increasing the accuracy of the sensors and adjusting their arrangement on the outer surface, and eventually reached the state of converging at the best state accurately. This study suggests that QL method is able to reconstruct the internal temperature distribution in this phantom and might be worthy of a further study in an anatomical based model.
Xin Zhu, Osamu Okazaki, and Daming Wei. Body Surface Potential Mapping and Conduction Abnormalities at Right Ventricular Outflow Tract in Brugada Syndrome : a Simulation Study. In Proceedings of JHRS JSE APHRS 2011, page CDROM, 2011.
We proposed computer simulation of body surface potential mapping (BSPM) based on the Wei-Harumi models of normal heart, Brugada syndrome (BrS), and RBBB. The BrS cell models with action potential (AP) dome and prolonged action potential duration (APD) were set at the epicardium of the right ventricular outflow tract (RVOT) in BrS heart models. Type 1 BrS ECGs were reproduced at the right precordial leads both in the standard and higher intercostal spaces (BrS-1SH) or only in the higher intercostal spaces (BrS-1H) through adjusting the locations of BrS model cells. Simulated BSPM of both BrS-1SH and BrS-1H demonstrated an electrical dipole at RVOT and a dipole related to ventricular depolarization at the end of QRS complex, while an electrical dipole with an opposite direction at RVOT and another dipole related to ventricular repolarization were observed during the T wave. Similar dipole patterns at RVOT were not found in the BSPM simulated with normal and RBBB heart models. This simulation research suggests that BSPM may reveal conduction abnormalities at RVOT for the diagnosis of BrS as found by Guillem et al. based on clinical BSPM data.
Wenxi Chen, Xin Zhu, and Tetsu Nemoto. Respiratory Rhythm and Pulse rate monitor device, November 2011.
Naoyuki Takiguchi. Web GUI Design and Implementation for Sleep Monitoring System. Graduation thesis, School of Computer Science and Engineering, 2012.
Thesis Adviser: W. Chen
Tsuyuki Sato. Effects of Ambient Light on Heart Rate and Respiration Rate during Sleep. Graduation thesis, School of Computer Science and Engineering, 2012.
Thesis Adviser: W. Chen
Kazuya Matsuda. Optimization of a PID Control System for an Abdominal Phantom in Deep Body. Graduation thesis, School of Computer Science and Engineering, 2012.
Thesis Adviser: W. Chen
Linlin Jiang. Development of a Web-based System for Home Health Care. Master thesis, Graduate School of Computer Science and Engineering, 2012.
Thesis Adviser: W. Chen
Xun Gong. Full Automatic Home Health Monitoring System Using Bluetooth Pulse Oximeter. Master thesis, Graduate School of Computer Science and Engineering, 2011.
Thesis Adviser: C. Chen
Zhaogin Liu. Characterization of body movement during sleep and its physiological significance. Master thesis, Graduate School of Computer Science and Engineering, 2011.
Thesis Adviser: W. Chen
Weijia Lu. Studies on Atrial Fibrillation - Algorithms for Epicardial Mapping and Computer Modeling. Ph.d. thesis, Graduate School of Computer Science and Engineering, 2011.
Thesis Adviser: W. Chen
Shizhong Yuan. Web-based information sharing for electrocardiograms. Ph.d. thesis, Graduate School of Computer Science and Engineering, 2011.
Thesis Adviser: W. Chen
Kenta Yuuki. Morphological Filtering for Removing Baseline Wander in Electrocardiogram. Graduation thesis, School of Computer Science and Engineering, March 2012.
Kousuke Takano. Study of Analysis of T-wave Alternans Using Derived Vectorcardiogram. Master thesis, Graduate School of Computer Science and Engineering, March 2012.
Hiroyoshi Furukawa. Heart Rate Variability Analysis after Bathing in Hot Spring. Bachelor's thesis, School of Computer Science and Engineering, March 2012.
Yusuke Konishi. Monitor of Systolic Blood Pressure using Pulse Arrival Time during Rest. Bachelor's thesis, School of Computer Science and Engineering, March 2012.
Misato Kikawa. Study on Heart Rate Variability after Drinking Alcohol. Bachelor's thesis, School of Computer Science and Engineering, March 2012.
Yukari Tsunoda. Study on Improvement of Electrocardiogram Authentication Accuracy After Ingestion of Alcohol. Master's thesis, Graduate School of Computer Science and Engineering, March 2012.
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