Chien-Sheng Liu

Cardiac tamponade in an infant : a rare complication of central venous catheterisation

A 2994g infant suffered cardiac tamponade from an infusion of total parenteral nutrition through an indwelling central venous catheter. The infant survived as a result of early diagnosis and aggressive therapeutic intervention. Cardiac tamponade secondary to central venous catheterisation is rare, but potentially lethal. Possible mechanisms are direct puncture by the catheter tip, or osmotic injury from the use of hypertonic solutions. To avoid this complication, the catheter tip should be prevented from entering the right atrium and its position should be checked periodically by chest X ray. Cardiac tamponade should be considered in any patient with a central venous catheter whose clinical condition deteriorates suddenly. Diagnostic or therapeutic pericardiocentesis should be employed as the first measure and time should not be wasted on other diagnostic procedures.

The differential method of phase space matrix for AF/VF discrimination application

The advances in electrocardiographic (ECG) technology have facilitated the development of numerous successful clinical applications and commercial monitoring products for diagnosing disease and monitoring health. All of these demand the development of smart algorithms and computational resources for the real-time, early indication of critical cardiac conditions. This study presents the development of a Complex Phase Space Difference (CPSD) algorithm with differential method to analyze spatial and temporal changes in reconstructed phase space matrix, and derives an index for real-time monitoring. We used total of 5306 data segments from MIT-BIH, CU, and SCDH databases and clinical trial data to determine the optimal working parameters and verified the classification capability by using a quantitative index of this algorithm. With threshold values set to 2.0 and 6.0, this method can successfully differentiate normal sinus rhythm (NSR) signals (1.48+/-0.21), low risk of atrial fibrillation (AF) signals (3.71+/-0.99) and high risk of ventricular fibrillation (VF) signals (9.38+/-2.22). It is the first real-time algorithm that reports the best performance to distinguish AF and VF with sensitivity of 97.9% and specificity of 98.4%. With self-normalization, the algorithm is not subjected to the inter-variability or sampling size effects. Its computational scheme only requires matrices addition and subtraction, and thus significantly reduces the complexity for real-time implementation. It will be able to adopt in different scenarios of tele-healthcare and implantable applications.

Analysis and design of on-sensor ECG processors for realtime detection of VF, VT, and PVC

Cardiovascular disease remains the main cause of death, and great efforts are spent on the design of ECG body sensors these years. Essential components such as analog frontend and wireless transceivers have been integrated on a compact IC with micro-Watt power consumption. To provide timely warning against the fatal vascular signs, based on the Chaotic Phase Space Differential (CPSD) algorithm, on-sensor processors are implemented to detect the abnormal ECG for VF, VT and PVC. The on-sensor processing reduces 98.0% power of wireless data transmission for raw ECG signals. The application specific processor is designed to accelerate CPSD algorithm with 1.7μW power while the OpenRISC is integrated to provide the system flexibility. The architecture is realized on the FPGA platform to physically demonstrate the detection of the abnormal ECG signals in a real time.

Analysis and Design of On-sensor ECG Processors for Realtime Detection of Cardiac Anomalies Including VF, VT, and PVC

Cardiovascular disease remains the main cause of death, and great efforts are spent on the design of ECG (electrocardiogram) body sensors these years. Essential components such as analog frontend and wireless transceivers have been integrated on a compact IC with micro-Watt power consumption. To provide timely warning against the fatal vascular signs, based on the Chaotic Phase Space Differential (CPSD) algorithm, heterogeneous VLSI processors are implemented and integrated to extract the abnormal ECG characteristics for VF (Ventricular Fibrillation), VT (Ventricular Tachycardia) and PVC (Premature Ventricular Contraction). The on-sensor processing reduces 98.0% power of wireless data transmission for raw ECG signals. The application specific processor is designed to accelerate CPSD algorithm with 1.7μW power while the OpenRISC is integrated to provide the system flexibility. The architecture is realized on the FPGA platform to demonstrate the detection of the abnormal ECG signals in realtime.

The development and evaluation of the citizen telehealth care service system: Case study in taipei

Because of the rapid aging population in Taiwan and the trend of fewer children, people are looking into technical solutions for continuous/intermittent monitoring of vital signs in the home setting environment and the interactions between family members. In this study we developed a smart medical services system for managing chronic disease, called Citizen Telemedical Care service System (CTCS). The system integrates biosignal measurement, hypertension risk estimation expert system, clinic appointment service, video communication service, medical assistance referral, health frequency program record, and health/hygiene education. The demo version CTCS is exhibited in the center of INSIGHT opened for visit and trial use. In order to verify the demand and acceptability of the system and services, we have interviewed 251 volunteers with a questionnaire survey with the help from Taipei City Government. The results showed that people have positive expectation about the service program for health care and the capability of home devices. They also expressed high motivation on learning to use the system and to participate in the program. According to the evaluation results, the system is processing a small user test led by Taipei City Government, in order to further verify the acceptability and satisfaction of the system.

Chaotic Phase Space Differential (CPSD) Algorithm for Real-Time Detection of VF, VT, and PVC ECG Signals

The continuous evolution of electrocardiography (ECG) recording has enabled the successful development of many significant applications of this vital signal for clinical diagnosis and monitoring. Recent trends in device miniaturization and wireless transmission have extended the uses of such a signal modality to telemedicine for home cares. However, it has posted new technical challenges for the scenarios of home users and associated business models. Among them, a smart algorithm for real time or early indication of critical cardiac conditions, e.g. ventricular fibrillation (VF), Ventricular Tachycardia (VT), are extremely important for sharing the work loads of remote side for proper responses and delivery of health care. It would be also rather critical to fit such a computation task into the wearable or mobile device for the requirement of low power consumption. In this paper, we report the development of a novel analysis algorithm based on Time-Delayed Phase Space Reconstruction (PSR) method to differentiate abnormal ECG segments from entire records. We used BIHMIT arrhythmia database and CU database to verify our original ideas. According to our test results, this algorithm successfully identified the three heart diseases of PVC (Premature Ventricular Contraction), VF (Ventricular Fibrillation) and VT (Ventricular Tachycardia) immediately. We calculated the statistic parameters to estimate the efficiency: the average of sensitivity is 98.7% and the specificity reaches 96.2%. We also implemented this algorithm for wearable applications in a single-chip micro controller (MSP430, TI) for arrhythmia ECG data. The total code size is about a few hundred bytes and the execute time meets the order of sub-second. This new algorithm provides a powerful real-time index for clinical diagnosis and long-term home-care applications.

Modified maternal ECG cancellation for portable fetal heart rate monitor

Abstract This letter presents an efficient algorithm to detect fetal heart rates based on linear template subtraction (TS) for portable fetal heart rate monitors. After pre-processing, the covariance function windowing is used to eliminate maternal P-waves, maternal T-waves, baseline wander, and to enhance maternal R-waves and fetal R-waves. Next, fetal ECG is extracted by the modified mECG cancellation method which forms a mECG template by projecting an average maternal R-wave as a basis into exponential domains. Finally, fetal R-peaks are detected using a 2-D phase space matrix. The results show that the true positive rate, false discovery rate, and false negative rate of the proposed method are 86.80%, 5.78%, 13.20% respectively, which are better than those of other single-channel fetal ECG template extraction methods. It turns out that the modified template subtraction method has three main advantages. First, the covariance function windowing easily removes baseline wander, maternal P waves and maternal T waves. Second, the modified mECG cancellation model can extract overlapping signals without causing large waveform distortions. Last, both covariance function windowing and the modified mECG cancellation model are efficient and can operate in real time.

Phonon-assisted transient electroluminescence in Si

The phonon-replica infrared emission is observed at room temperature from indirect band gap Si light-emitting diode under forward bias. With increasing injection current density, the broadened electroluminescence spectrum and band gap reduction are observed due to joule heating. The spectral-resolved temporal response of electroluminescence reveals the competitiveness between single (TO) and dual (TO + TA) phonon-assisted indirect band gap transitions. As compared to infrared emission with TO phonon-replica, the retarder of radiative recombination at long wavelength region (∼1.2 μm) indicates lower transition probability of dual phonon-replica before thermal equivalent.

ARTIFICIAL NEURAL NETWORKS FOR ESTIMATING GLOMERULAR FILTRATION RATE BY URINARY DIPSTICK FOR TYPE 2 DIABETIC PATIENTS

Background: The result of a standard urinary dipstick from a patient with diabetes mellitus type 2 can be used to predict the estimated glomerular filtration rate (eGFR). We designed a multilayer perceptron (MLP) to investigate the possibility and optimal number of variables for the prediction. Methods: A total of 299 volunteers with diabetes mellitus type 2 were included. The blood and urine samples from volunteers were analyzed for blood sugar, glycated hemoglobin, serum creatinine, and urine chemistry. The urine chemistry was examined by a standard urinary dipstick. Volunteer age and gender and six test items of the dipstick were set as eight variables for this study. The eight variables were grouped and examined for the optimal combination. The eight variables from 232 of 299 volunteers were used to train an MLP for the optimal variables. The performance of trained MLP was validated by the data from 69 of 232 volunteers. Results: The optimal combination for variables was the six test items of the dipstick and volunteer age. The area under the curve (0.928), accuracy (0.879), sensitivity (0.83), and specificity (0.88) of the trained MLP were examined. Conclusions: The results demonstrate the eGFR prediction potential of the results of a urinary dipstick using this method.

Chaotic phase space differential algorithm for real-time detection of ventricular arrhythmias: Application in animal model

Life-threatening ventricular arrhythmias remain the main cause of death among patients with cardiovascular diseases. Efforts have been spent on early detection of such fatal cardiac signs. We have previously reported a novel chaotic phase space differential (CPSD) algorithm in discriminating VPC, VT, and VF from normal sinus rhythm with both good sensitivity and specificity. In this article, we apply this algorithm on the rat model of calcium induced ventricular tachycardia. Peaked CPSD values can be observed along with the occurrence of ventricular tachycardia. In addition, minor ECG changes such as new onset S wave or sinus arrhythmia can also be noted on CPSD tracing. We believe that the CPSD algorithm not only is capable of detecting lethal ventricular arrhythmias, but also is potentially a good tool for long-term monitoring the change of ECG signals.