Liang-Yu Shyu

Using wavelet transform and fuzzy neural network for VPC detection from the holter ECG

A novel method for detecting ventricular premature contraction (VPC) from the Holter system is proposed using wavelet transform (WT) and fuzzy neural network (FNN). The basic ideal and major advantage of this method is to reuse information that is used during QRS detection, a necessary step for most ECG classification algorithm, for VPC detection. To reduce the influence of different artifacts, the filter bank property of quadratic spline WT is explored. The QRS duration in scale three and the area under the QRS complex in scale four are selected as the characteristic features. It is found that the R wave amplitude has a marked influence on the computation of proposed characteristic features. Thus, it is necessary to normalize these features. This normalization process can reduce the effect of alternating R wave amplitude and achieve reliable VPC detection. After normalization and excluding the left bundle branch block beats, the accuracies for VPC classification using FNN is 99.79%. Features that are extracted using quadratic spline wavelet were used successfully by previous investigators for QRS detection. In this study, using the same wavelet, it is demonstrated that the proposed feature extraction method from different WT scales can effectively eliminate the influence of high and low-frequency noise and achieve reliable VPC classification. The two primary advantages of using same wavelet for QRS detection and VPC classification are less computation and less complexity during actual implementation.

Prolonged fractionation of paced right atrial electrograms in patients with atrial flutter and fibrillation.

OBJECTIVES This study investigated the extent of fractionation of paced right atrial electrograms in patients with and without paroxysmal atrial flutter (AFL) or atrial fibrillation (AF). BACKGROUND Slow conduction through nonuniform anisotropic atrial muscles, represented by fractionated electrograms, may favor the generation of atrial tachyarrhythmias. METHODS This study included 10 control patients (Group 1), 8 patients with documented paroxysmal AFL (Group 2) and 10 patients with documented paroxysmal AF (Group 3). Five electrode catheters were placed in the different sites of the right atrium and one catheter was positioned at the coronary sinus ostium. Atrial pacing from one site was done by a constant drive train with an extrastimulus inserted every fourth beat while recording at the other five sites was performed. The delay of each fractionated potential in the high-pass filtered atrial electrogram in response to extrastimulation was determined and used to construct conduction curves of delay versus the S1S2 interval. RESULTS The mean increase in electrogram duration between a coupling interval of 350 ms and 10 ms above atrial refractoriness was significantly greater in Groups 2 and 3 compared with that in Group 1 (8.5 +/- 2.5 vs. 11.0 +/- 2.7 vs. 5.9 +/- 2.3 ms, respectively, p < 0.001). The mean S1S2 interval at which delay increased suddenly was also longer in Groups 2 and 3 compared with Group 1 (326 +/- 9 vs. 343 +/- 12 vs. 307 +/- 17 ms, respectively, p < 0.001). CONCLUSIONS Increased delays in the individual potential of the fractionated atrial electrograms may be related to the development of AFL and AF.

Evaluation of Scalp and Auricular Acupuncture on EEG, HRV, and PRV

In this study, the EEG, ECG and blood-pressure-pulse recorder were employed to evaluate heart rate variability, pulse rate variability, and EEG of 10 adults after scalp (experimental test I) at Sishencong scalp acupoint and auricular (experimental test II) acupuncture at Shenmen auricular acupoint for about 10 min. Comparison of the results between the experimental tests and a control with no stimulation test showed that both the heart rate and pulse rate were decreased, and the blood pressure fell. The high and low frequency power of FFT analysis of heart rate was increased and decreased, respectively; indicating that the parasympathetic nerves were activated and the sympathetic nerves were inhibited. The analysis of the power spectrum of EEG showed that the number of low frequency waves was increased after acupuncture stimulation. Therefore, acupuncture on either Sishencong or Shenmen might calm the mind, slow down the heart rate, and activate the parasympathetic nerves.

ECG events detection and classification using wavelet and neural networks

An integrated system for ECG diagnosis that combines the wavelet transform (WT) for feature extraction and artificial neural network (ANN) models for the classification is proposed. By using the dyadic wavelet transform, the limitations of other methods in detecting ECG features such as QRS complex, the onsets and offsets of P and T waves are overcame. The ECG baseline is approximated using discrete least squares approximation. On classification, two paradigms of learning, supervised and unsupervised, for training the ANN modes are investigated. The backpropagation algorithm and the Kohonens self-organizing feature map algorithm were used for supervised and unsupervised learning, respectively. The system is evaluated using the MITBIH database. The result indicates that the accuracy of diagnosing cardiac disease is above 97.77%. ECG signals can be classified, even with noise and baseline drift.

A Study of Electrical Conductance of Meridian in the Obese During Weight Reduction

This study was designed to investigate the electrical conductance of meridian in the obese during weight reduction. Ten obese including overweight (Body Mass Index, BMI > 26) and 30 healthy (non-overweight) people were recruited from Chung Yuan Christian University. The obese subjects were instructed to follow a weight reduction program that included diet control, exercise and oral intake of Prozac. A device, the design of which is based on the Ryodoraku theorem, was used to measure the electrical conductance of 12 meridians on both sides of the subjects. The results showed that: (1) the average coefficient of variation of the electrical conductances in 24 meridians of the obese group was statistically different from that of the healthy group (p < 0.05); (2) the average coefficient of variation of electrical conductance in the obese after weight reduction was significantly decreased than before the weight reduction program (p < 0.05); (3) the BMI and the electrical conductance of meridian was correlated in the obese (r = -0.77, p < 0.001) as well as in the healthy group (r = -0.92, p < 0.001). These findings suggest that electrical conductance of meridians can be a parameter to monitor weight, especially for obese people.

Portable impedance cardiography system for real-time noninvasive cardiac output measurement

A portable impedance cardiography (ICG) system has been developed. It is battery powered, small size, and in-expensive. Only one 9.6 V Ni/Cd battery is needed to operate the system for one and half hours, continuously. In addition, a digital signal processing (DSP) chip (TMS320C50, National Instrumentation Co.) is used for real-time signal processing, event detection, and stroke volume (SV) calculation. Information such as SV, cardiac output (CO), heart rate (HR) and left ventricular ejection time (LVET) are displayed on a 128*64 dot matrix LCD and updated after each heart beat. This system is also capable of storing the above information in the internal SRAM that can be transmitted to the personal computer through an RS232 interface for further analysis, after monitoring.

The detection of impedance cardiogram characteristic points using wavelet transform

A novel impedance cardiograph event detection method using wavelet transform is proposed. When compared to the C and E points in the pressure-volume loop, the wavelet method performs significantly better than the traditional method (P < 0.05) in the B and X points detection even after the addition of 20% artificial noise into the test signal. Nevertheless, the SVs estimated by ICG are poorly correlated with values measured by the conductance catheter.

The effect of data reduction by independent component analysis and principal component analysis in hand motion identification

Both independent component analysis (ICA) and principal component analysis (PCA) were used in this study to evaluate their effects in data reduction in the hand motion identification using surface electromyogram (SEMG) and stationary wavelet transformation. The results indicate that both methods increase the number of training epochs of the artificial neural network. The unsupervised fast ICA reduces the number of SEMG channels from 7 to 4. However the hand motion identification rate using the reduced channels is significantly lower (p < 0.05). On the other hand, the PCA reduces the size of neural network by more than 70%. Moreover, the results of discrimination rate and neural network training epochs show no significant difference as compared to the results before PCA reduction. The result of this study demonstrates that using wavelet and PCA are effective pre-processing for surface EMG analysis. It can efficiently reduce the size of neural network and increase the discrimination rate for different hand motions.

Assessment of left atrial function using multi-slice CT images

The function of left atrium can be accurately estimated non-invasively using 4D CT cardiac images. A self-developed image analysis program will first reconstruct 3D volume of heart. Then, one may re-sample images for accurately deleting the 4 pulmonary veins from the atrium and set the boundary. With the prior processed information, the active contour methodology and seed regional growth methodology were implemented to delineate the atrial contour. With a calibration standard of 500 ml saline with contrast medium in bag, both methods were able to estimate volume within 5% of error. Thirty sets of patientpsilas CT cardiac images that were acquired at 30% and 90% of RR interval. The dimension of pulmonary veins and the left atrial volume was evaluated. The contractility of pulmonary vein and the ejection fraction (EF) of atrium was calculated. The result shows that the left atrium with a larger volume will have a poor ejection fraction.

Two-Cuff Noninvasive Blood Pressure Waveform Monitoring System for Dynamic Blood Vessel Characteristic Study

This study proposes and constructs a two-cuff non-invasive blood pressure waveform monitor system. The proposed system uses dynamic feedback to maintain constant low cuff pressure at 40 mmHg. Thus, long term continuous blood pressure waveform monitoring is possible. Additionally, the two blood pressure waveforms can be used to compute the system function, frequency response and impulse response of vessel system for system dynamic studies. Ten normal young males were recruited for this study. Continuous blood pressure signals from upper arm and wrist were obtained by the proposed system. During steady state, correlation coefficients of systolic pressure and diastolic pressure, between upper arm and wrist, are 0.83plusmn0.15 and 0.81plusmn0.14, respectively. During cold pressor, correlations decrease slightly. Additionally, the blood vessel system model was evaluated using autoregressive exogenous model (ARX) model. The dynamic changes of blood vessel system during task can be seen from the 3D time-varying impulse responses. In order to assist the observation of the dynamic characteristic change of blood vessel system during different physiological conditions, the 90% energy curve was proposed and used. Before the end of cold pressor, the 90% energy curve reviewed that system energy accumulates faster than steady state indicating the vessel system shifted to higher frequency. On the other hand, the system shifted to slower system during Valsalva maneuver