Yue-Der Lin

Power-Line Interference Detection and Suppression in ECG Signal Processing

A novel power-line interference (PLI) detection and suppression algorithm is presented to preprocess the electrocardiogram (ECG) signals. A distinct feature of this proposed algorithm is its ability to detect the presence of PLI in the ECG signal before applying the PLI suppression algorithm. No PLI suppression operation will be performed if PLI is not detected. We propose a PLI detector that employs an optimal linear discriminant analysis (LDA) algorithm to make a decision for the PLI presence. An efficient recursive least-squares (RLS) adaptive notch filter is also developed to serve the purpose of PLI suppression. Experimental results demonstrate superior performance of this proposed algorithm.

An EEG spike detection algorithm using artificial neural network with multi-channel correlation

An automatic spike detection algorithm for classification of multi-channel EEG signals based on artificial neural network is presented. Radial basis function (RBF) neural network was chosen for single channel recognition, with model optimization using receiver operating characteristics analysis. Waveform simplification was employed for high noise immunity. Feature extraction with as few as three parameters was used as preparation for the inputs to the neural network. Identification of multi-channel geometric correlation was performed to further lower the false-positive rate by using an incidence matrix. Threshold value for spike classification was chosen for simultaneous maximization of detection sensitivity and selectivity. Evaluation with visual analysis in this preliminary study showed a 83% sensitivity using 16-channel continuous EEG records of four patients, while a high false positive rate was found, which was believed to arise from the extensive and exhaustive visual analysis process. The computation time required for spike detection was significantly less than that needed for online display of the signals on the monitor. We believe that the algorithm proposed in this study is robust and that the simple structure of RBF neural network yields high potential for real-time implementation.

Aminoguanidine prevents arterial stiffening and cardiac hypertrophy in streptozotocin-induced diabetes in rats

The formation of advanced glycation endproducts (AGEs) on collagen within the arterial wall may be responsible for the development of diabetic vascular injury. This study was to examine the role of aminoguanidine (AG), an inhibitor of AGEs formation, in the prevention of arterial stiffening and cardiac hypertrophy in streptozotocin (STZ) induced diabetes in rats. Diabetes was induced in animals by a single tail vein injection with 65 mg kg−1 STZ. After confirmation of the development of hyperglycemia (2 days later), rats were treated for 8 weeks with AG (daily peritoneal injections of 50 mg kg−1) and compared with the age‐matched untreated diabetic controls. After exposure to AG, the STZ‐diabetic rats showed no alterations in cardiac output, aortic pressure profiles, total peripheral resistance, and aortic characteristic impedance. By contrast, treatment of this experimental diabetes with AG resulted in a significant increase in wave transit time (τ), from 20.4±0.6 to 24.7±0.5 ms (P<0.05) and a decrease in wave reflection factor (Rf), from 0.78±0.04 to 0.53±0.02 (P<0.05). The decreased Rf associated with the increased τ suggest that AG may retard the diabetes‐induced augmentation in systolic load of the left ventricle coupled to its arterial system. Meanwhile, the diminished ratio of left ventricular weight to body weight suggests that prevention of the diabetes‐related cardiac hypertrophy by AG may correspond to the drug‐induced decline in aortic stiffening. Glycation‐derived modification on aortic collagen was also found to be enhanced in rats with diabetes (+65.3%, P<0.05) and the advanced glycation process was retarded by AG treatment. We conclude that long‐term administration of AG to the STZ‐treated rats imparts significant protection against the diabetes‐derived deterioration in vascular dynamics, at least partly through inhibition of the AGEs accumulation on collagen in the arterial wall.

Aminoguanidine prevents the impairment of cardiac pumping mechanics in rats with streptozotocin and nicotinamide‐induced type 2 diabetes

Aminoguanidine (AG), an inhibitor of advanced glycation endproducts, has been shown to prevent arterial stiffening and cardiac hypertrophy in streptozotocin (STZ) and nicotinamide (NA)‐induced type 2 diabetes in rats. Our aims were to examine whether AG produced benefits on cardiac pumping mechanics in the STZ and NA‐treated animals in terms of maximal systolic elastance (Emax) and theoretical maximum flow (Qmax).

A Study of Heart Sound and Lung Sound Separation by Independent Component Analysis Technique

In the hospital, using percussion and auscultation are the most common ways for physical examination. Recently, in order to develop tele-medicine and home care system and to assist physician getting better auscultation results; electric stethoscope and computer analysis have become an inevitable trend. However, two important physical signals heart sound and lung sound recorded from chest overlap on spectrum chart. Therefore, in order to reduce human factor (ex. misplace or untrained of using) and minimize correlated effect in computer analysis; its necessary for separated heart sound and lung sound. Independent component analysis can divide these sounds efficiency. In this paper, we use two microphones to collect signals from left and right chest. We have successfully divide heart and lung sounds by fast ICA algorithm. Therefore, it can assist physician examine and also using on tele-medicine and home care by this way

Variations of HRV analysis in different approaches

The analysis of normal-to-normal (NN) intervals acquired from a continuous electrocardiogram (ECG) record is a standard method to evaluate the variations in heart rate. For the advantage of responding to the pumping action of the heart, photoplethysmography (PPG) has also been used extensively in the analysis of heart rate variability (HRV). However, there is little literature available on the variation between the HRV analysis derived from ECG and PPG. In the research described here, experiments of recording short-term (les 5 minutes) ECG and PPG signals simultaneously from healthy subjects (male, N=10) under control were carried out to investigate the possibility of such variation. Automatic computer analysis is provided for the analysis of correlation coefficient and the LF/HF ratio by autoregressive (AR) spectral analysis for evenly resampled sequences. The identical results are highly expected. However, the correlation coefficient between RRI (R-R interval from ECG) and PPI (peak-to-peak interval from PPG) is 0.86plusmn0.15, which should be unity for perfectly matched patterns. In additions, the relative LF/HF ratios are 2.49plusmn1.13 (for ECG) and 2.73plusmn0.82 (for PPG) respectively. Though there is no statistical difference, the worst likelihood ratio (LR) reaches the deviation of 19.04%. From the experimental results, it can be appreciated that there is indeed variation for HRV analysis in two different approaches even for healthy subjects under well-controlled conditions. For abnormal subjects in clinical applications, such variation may be expected to become more apparent. Though the variation is minor, it is suggested to obey the standard measure of HRV proposed by Task Force for consistent conclusions.

Preamplifier with a second-order high-pass filtering characteristic

A new preamplifier for suppressing low-frequency interference is presented. The proposed preamplifier, with its front end being implemented by an instrumentation amplifier, enjoys the following advantages: differential high-pass filtering, high input impedance, high common--mode rejection ratio and low passive sensitivity. This circuit can be realized with commercial operational amplifiers with enough phase margin, or fabricated in a chip for practical measurement of physiological signals.

Autonomic neuropathy precedes cardiovascular dysfunction in rats with diabetes

Background  Our team previously demonstrated arterial stiffening and cardiac hypertrophy in type 2 diabetic rats at 8 but not 4 weeks after being administered streptozotocin (STZ) and nicotinamide (NA). The present study focused on investigating the effects of type 2 diabetes on cardiac autonomic nerve function in the STZ‐ and NA‐treated animals, using modern spectral estimation technique.

Evaluation measures for adaptive PLI filters in ECG signal processing

Many studies have been devoted to the adaptive power-line interference (PLI) filter design for ECG signal processing. However, almost all existing PLI suppression filters are developed for applications in which the presence of PLI noise is assumed a priori. Indiscriminate application of PLI suppression over an ECG signal that is free of PLI noise may deform ECG morphology, and even cause degraded performance of subsequent processing. To date, little work has been done on the possibility of ECG signal degradation by such filtering operation and the impact on further processing. In order to evaluate the difference between the original and the filtered pattern, this study proposes quantitative evaluation measures. The assessments include convergence time, the frequency tracking efficiency, the execution time and the relative statistics in time and frequency domain. Extensive experiments have been done with artificially and practically corrupted ECG signals for four existing PLI adaptive filtering techniques (Ahlstrom and Tompkinspsila, Pei and Tsengpsilas, Sopsilas and Ziarani and Konradpsilas algorithm). The results reveal that ECG signal distortion resulted from these existing adaptive filters. None of the existing algorithms outperform the others in all assessments. The proposed evaluation measures can also be used for the performance evaluation of the other types of artifact suppression, such as the baseline wander and EMG corruption contaminated in ECG, after minor modification. The proposed measures also make the optimal filter design under different constraints possible for ECG signal processing.

Using conductive fabric for capacitive EEG measurements

Abstract Traditional electroencephalogram (EEG) measurements require conductive gel to ensure good conduction between the electrodes and skin (or scalp). But this gel may make patients uncomfortable because of possible skin allergies during long-term measurement. The measurement procedure is also tedious because pasting the electrodes to the patient’s scalp is time consuming. The required lead wires also constrain patient movements. This study uses conductive fabric as the capacitive electrode for EEG measurements. This paper provides the design considerations and the related theoretical analysis for this method. A long-term, null-input experiment was conducted to verify the stability of the proposed system. Experiments were conducted over the hair of patients to verify the feasibility of using the method during EEG monitoring. Various mental task experiments were also conducted. The changes in frequency domain analysis show that the proposed strategy discriminates between different mental tasks.