Modified forward-backward overdetermined Prony method and itsapplication in modelling heart sounds

Prony's method is found to be a very effective method for the analysis-synthesis of transient data. However, straightforward application of this method can lead to poor performance, especially for short and noisy data records. The authors present a new over-determined forward-backward Prony method (MFBPM) and its application to the analysis of the first and second heart sounds. The accuracy of the method is measured using both cross-correlation and the normalised-mean-square-error (NMRSE) between a real signal and a synthetic one. Results from more than 80 different subjects show that the MFBPM is highly stable and gives very good performance with an average cross-correlation coefficient of 99.62%. Comparison of the results based on the NMRSE criterion show that the MFBPM is more precise than the modified backward Prony method (MBPM) with an accuracy improvement of upto 10%, and upto 20%, when compared with the conventional forward-backward Prony method (FBPM). Furthermore, a new method for dynamic estimation of model order is proposed for the case of heart sounds based on a subset of synthesised heart sounds which best approximates the observed data using NMRSE     

Time-frequency and time-scale techniques for the classification ofnative and bioprosthetic heart valve sounds

The determination of diagnostic features in recorded heart sounds was investigated with Carpentier-Edwards (CE) bioprosthetic valves. Morphological features, extracted using the Choi-Williams distribution, achieved between 96 and 61% correct classification. The time-scale wavelet-transform feature set achieved 100% correct classification with native valve populations, and 87% with the CE replacements     

Detection of coronary occlusions using autoregressive modeling ofdiastolic heart sounds

Previous studies have indicated that diastolic heart sounds may contain information useful in the detection of occluded coronary arteries. In this study, recordings of diastolic heart sound segments were modeled by autoregressive (AR) methods including the adaptive recursive least-square lattice (RLSL) and the gradient lattice predictor (GAL). Application of the Akaike criterion demonstrated that between 5 and 15 AR coefficients are required to completely describe a diastolic segment. The reflection coefficients, prediction coefficients, zeros of the polynomial of the inverse filter, and the AR spectrum were determined over a number (N = 20-30) of diastolic segments. Preliminary results indicate that the averaged AR spectrum and the zeros of the inverse filter polynomial can be used to distinguish between normal patients and those with coronary artery disease.     

Real-time separation of discontinuous adventitious sounds fromvesicular sounds using a fuzzy rule-based filter

The separation of pathological discontinuous adventitious sounds (DAS) from vesicular sounds (VS) is of great importance to the analysis of lung sounds since DAS are related to certain pulmonary pathologies. An automated way of revealing the diagnostic character of DAS, by isolating them from VS, based on their nonstationarity, is presented. The proposed algorithm uses two adaptive network-based fuzzy inference systems to compose a generalized fuzzy rule-based stationary-nonstationary filter (GFST-NST). The training procedure of the fuzzy inference systems involves the outputs of the wavelet transform-based stationary-nonstationary filter (WTST-NST), proposed by Hadjileontiadis and Panas (1997). The basic idea of the GFST-NST was initially proposed by the authors with the introduction of the fuzzy rule-based stationary-nonstationary filter (FST-NST) (1997), tested with the separation of crackles from VS. The main contribution of this paper is the modification of the structure of the FST-NST filter to a serial-type fuzzy filter that, unlike the parallel operation of the FST-NST filter, sends a predicted stationary signal (VS) into the predictor of the nonstationary (DAS). Applying the GFST-NST filter to fine-coarse crackles and squawks, selected from three lung sound databases, the coherent structure of DAS is revealed and they are separated from VS. The separation performance of the GFST-NST filter was evaluated through quantitative and qualitative indexes that proved its efficiency and superiority against the FST-NST filter. When compared to the WTST-NST filter, the GFST-NST filter performed similarly in accuracy and objectiveness, but in a faster way. Thus, the GFST-NST filter combines the separation accuracy of the WTST-NST filter with the real-time implementation of the FST-NST filter, so it can easily be used in clinical medicine as a module of an integrated intelligent patient evaluation system     

Comparison of pattern recognition methods for computer-assistedclassification of spectra of heart sounds in patients with a porcinebioprosthetic valve implanted in the mitral position

The diagnostic performance of two pattern recognition methods (or classifiers) to detect valvular degeneration was evaluated in 48 patients with a porcine bioprosthetic heart valve inserted in the mitral position. Twenty patients had a normal porcine bioprosthetic valve and 28 patients had a degenerated bioprosthetic valve. One method was based on the Gaussian-Bayes model and the second on the "nearest neighbor" algorithm using three distance measurements. Eighteen diagnostic features were extracted from the sound spectrum of each patient and, for each method, a two-class supervised learning approach was used to determine the most discriminant diagnostic patterns composed of 6 features or less. The probability of error of the classifiers was estimated with the leave-one-out approach. The performance of each method to discriminate between normal and degenerated bioprosthetic valves was verified by clinical evaluation of the valves. The best performance in evaluation of the sound spectrum (98% correct classifications) was obtained with the Bayes classifier and two patterns of six features each. The percentage of false positive classifications of valve degeneration was 0% and the percentage of false negative classifications was 4%. Sensitivity for the detection of valve degeneration was 96%, specificity was 100%, positive predictive value was 100%, and negative predictive value was 95%. The best performance of the nearest neighbor method (94% correct classifications) was obtained by using the Mahalanobis distance and five patterns composed of three, four, five, or six diagnostic features. Using a pattern composed of only three features, the percentage of false positive classifications for degeneration was 10% and the percentage of false negative classifications was 4%.(ABSTRACT TRUNCATED AT 250 WORDS)     

Separation of discontinuous adventitious sounds from vesicularsounds using a wavelet-based filter

The separation of pathological discontinuous adventitious sounds (DAS) from vesicular sounds (VS) is of great importance to the analysis of lung sounds, since DAS are related to certain pulmonary pathologies. An automated way of revealing the diagnostic character of DAS by isolating them from VS, based on their nonstationarity, is presented in this paper. The proposed algorithm combines multiresolution analysis with hard thresholding in order to compose a wavelet transform-based stationary-nonstationary filter (WTST-NST). Applying the WTST-NST filter to fine/coarse crackles and squawks, selected from three lung sound databases, the coherent structure of DAS is revealed and they are separated from VS. When compared to other separation tools, the WTST-NST filter performed more accurately, objectively, and with lower computational cost. Due to its simple implementation it can easily be used in clinical medicine     

基于蓝牙的心肺音采集系统

心脏疾病目前已经成为致死率第一的疾病。学者们正在致力于研究各种治疗方式,以从心脏病手中挽救人们的生命。而目前我国的心血管发病率在逐年增加,心血管课题也成为一个重要课题,心血管疾病也越来越受到人们的重视。本文研究了心肺音采集系统的适配电路,阐述了可分离心、肺音的多功能无线可视化电子听诊器的应用前景。针对可分离心、肺音的多功能无线可视化电子听诊器工作原理确定了适配电路的选择方案。详细介绍了各部分电路的功能,构成低功耗、低成本的硬件平台,实现基于蓝牙的心肺音采集系统。     

冠心病患者支架植入术后氯吡格雷与不同质子泵抑制剂联合治疗的疗效比较

目的探讨不同质子泵抑制剂对氯吡格雷抗血小板作用的影响。方法286例在我院实施冠状动脉支架植入术的患者随机分为奥美拉唑40mg/d+氯吡格雷75mg/d组(146例)和泮托拉唑40mg/d+氯吡格雷75mg/d组(140例),连续用药30d,观察主要不良心脑血管事件。结果奥美拉唑组心性死亡、非致死性急性心肌梗死、紧急靶血管血运重建、脑卒中发生率分别为1.37%、2.05%、3.42%、0.68%;泮托拉唑组分别为0.71%、2.85%、2.85%、0.71%,两组无统计学差异(P>0.05)。奥美拉唑组主要不良心脑血管事件、急性亚急性血栓形成发生率分别为7.53%、1.37%,泮托拉唑组分别为7.14%、0.71%,两组亦无统计学差异(P>0.05)。两组出血事件发生率分别为9(6.16%)和9(6.42%),差异无统计学意义(P=0.926)。结论冠心病患者支架植入术后采用氯吡格雷联合奥美拉唑或泮托拉唑治疗的近期疗效相近。     

Electrical and surface composition properties of phosphorus implantation in Mg-doped GaN

Changes in electrical as well as surface composition such as chemical and electronic properties of Mg-doped p-type GaN by phosphorus implanting are systematically investigated using Hall effect and X-ray photoelectron spectroscopy (XPS) measurements. It is shown that p-type conductivity of Mg-doped GaN can be improved by implanting P atoms after a proper post-implantation annealing treatment, probably due to the reduction of self-compensation by P atoms substitution on N vacancy sites. XPS analysis is further found that the decrease of surface oxides and the shift of the surface Fermi level toward the valence band edge through P atoms introduced. These experimental results indicate that the P implantation is an effective method to improve p-type conductivity of Mg-doped GaN and reducing the surface barrier height, which can lead to a lower metal contact resistivity to p-type GaN.     

小儿先心病心脏手术前后血清神经元特异性烯醇化酶水平的动态观察

目的 :血清神经元特异性烯醇化酶 (s-NSE)是一个能够反映脑损伤的指标 ,本文通过对体外循环开放式心脏不停跳、停跳两种手术患儿 ,手术前后s-NSE的动态观察 ,以了解在脑保护方面何种手术方式更好。方法 :采用ELESA法测定体外循环开放式心脏不停跳、停跳手术先心病患儿各 2 0例 ,术前 2 4小时、术后 2h、术后 7天的s-NSE水平 ,并以 2 0例健康儿童作为对照组。结果 :1.手术组术前s-NSE水平低且组间无差异 (P >0 .0 5 )。 2 .手术组在术后 2h测定显示s -NSE水平显著增高 ,平均值为 8.3± 2 .3 μg/L(心脏不停跳组 )和 16.3± 6.2 μg/L (心脏停跳组 ) ,与术前比较差异非常显著 (P <0 .0 0 1) ;术后 7天s-NSE水平分别为 6.1± 2 μg/L(心脏不停跳组 )和 10 .8± 2 .3 μg/L (心脏停跳组 ) ,与术前比较差异显著 (P <0 .0 5 ;0 .0 1)。 3 .术后 2hs-NSE水平停跳组明显高于不停跳组 (P <0 .0 0 1) ,且术后 7ds-NSE水平两组比较亦有显著差异 (P <0 .0 5 )。结论 :1.先心病患儿术前s-NSE处于正常水平。 2 .体外循环开放式心脏手术先心病患儿的s-NSE水平短期内尚不能完全恢复。 3 .心脏不停跳手术较心停跳手术术后的s-NSE水平低且恢复较快。提示就脑保护而言 ,心脏不停跳术式可能较好。     

改进型遗传算法在加载天线设计中的运用

遗传算法是一种全新的优化搜索方法，可以用来解决各种复杂的实际问题。针对简单型遗传算法的一些不足之处，介绍了一种改进型的遗传算法，并阐述了其在短波宽带集总加载天线优化设计中的运用。     

The fabrication of a broad-spectrum light-emitting diode using high-energy ion implantation

High-energy ion implantation is used to spatially modify the bandgap of a 1.5-/spl mu/m laser structure to fabricate a broad spectrum light emitting diode (LED). An increase in the emission full width half maximum (FWHM) from 28 nm to 90 nm is observed. An absorbing section at one end of the device is used to suppress lasing operation and remove Fabry-Perot noise.     

ECG denoising and compression using a modified extended Kalman filter structure

This paper presents efficient denoising and lossy compression schemes for electrocardiogram (ECG) signals based on a modified extended Kalman filter (EKF) structure. We have used a previously introduced two-dimensional EKF structure and modified its governing equations to be extended to a 17-dimensional case. The new EKF structure is used not only for denoising, but also for compression, since it provides estimation for each of the new 15 model parameters. Using these specific parameters, the signal is reconstructed with regard to the dynamical equations of the model. The performances of the proposed method are evaluated using standard denoising and compression efficiency measures. For denosing, the SNR improvement criterion is used, while for compression, we have considered the compression ratio (CR), the percentage area difference (PAD), and the weighted diagnostic distortion (WDD) measure. Several Massachusetts Institute of Technology–Beth Israel Deaconess Medical Center (MIT–BIH) ECG databases are used for performance evaluation. Simulation results illustrate that both applications can contribute to and enhance the clinical ECG data denoising and compression performance. For denoising, an average SNR improvement of 10.16 dB was achieved, which is 1.8 dB more than the next benchmark methods such as MABWT or EKF2. For compression, the algorithm was extended to include more than five Gaussian kernels. Results show a typical average CR of 11.37:1 with WDD ≪ 1.73%. Consequently, the proposed framework is suitable for a hybrid system that integrates these algorithmic approaches for clean ECG data storage or transmission scenarios with high output SNRs, high CRs, and low distortions.      

Wavelet-based enhancement of lung and bowel sounds using fractal dimension thresholding--Part I: methodology

An efficient method for the enhancement of lung sounds (LS) and bowel sounds (BS), based on wavelet transform (WT), and fractal dimension (FD) analysis is presented in this paper. The proposed method combines multiresolution analysis with FD-based thresholding to compose a WT-FD filter, for enhanced separation of explosive LS (ELS) and BS (EBS) from the background noise. In particular, the WT-FD filter incorporates the WT-based multiresolution decomposition to initially decompose the recorded bioacoustic signal into approximation and detail space in the WT domain. Next, the FD of the derived WT coefficients is estimated within a sliding window and used to infer where the thresholding of the WT coefficients has to happen. This is achieved through a self-adjusted procedure that iteratively "peels" the estimated FD signal and isolates its peaks produced by the WT coefficients corresponding to ELS or EBS. In this way, two new signals are constructed containing the useful and the undesired WT coefficients, respectively. By applying WT-based multiresolution reconstruction to these two signals, a first version of the desired signal and the background noise is provided, accordingly. This procedure is repeated until a stopping criterion is met, finally resulting in efficient separation of the ELS or EBS from the background noise. The proposed WT-FD filter introduces an alternative way to the enhancement of bioacoustic signals, applicable to any separation problem involving nonstationary transient signals mixed with uncorrelated stationary background noise. The results from the application of the WT-FD filter to real bioacoustic data are presented and discussed in an accompanying paper.     

Time-domain electromagnetic computations using a modified EFIE kernel and field-source equilibrium relations

A form for the electric-field dyadic Green's function for free space is derived that allows explicit time evolution of the modified electric-field integral equation (EFIE) applied to surface scattering. The modified EFIE kernel, here called a "source function," has an integrable singularity in the source region, and is shown to be equivalent, in the frequency domain, to the standard dyadic Green's function. With definitions of "local" and "non-local" fields at a conductor surface, both electric and magnetic versions of the relations between non-local fields and equilibrium surface sources (currents and charges) are derived. These field-source equilibrium (FSE) relations are exact if all the non-local fields are included: the interaction fields, as well as the usual incident fields from distant sources. When the interaction fields are neglected, the magnetic-field version of the FSE relations becomes the usual physical optics approximation. Source functions and the FSE relations were used in two three-dimensional, time-domain numerical simulations to compute radiation patterns from a conical helical antenna driven at a fixed frequency, and scattering of a CW plane wave by a perfectly conducting sphere. This surface-scattering simulation was explicit but remained stable. Excellent agreement between the computed and known results validated the approach.     

Simulation-based analog and RF circuit synthesis using a modified evolutionary strategies algorithm

This paper presents a simulation-based analog circuit synthesis methodology. Simulation-based approach is preferred so that the synthesizer, SACSES, is topology independent and requires minimal user effort. We argue that both the simulator and the search algorithm have to be optimized for analog circuit synthesis. In this regard, instead of using a commercially available simulator, an accelerated simulator, SPASE, is implemented. Various acceleration mechanisms for DC, AC and noise simulation are discussed. For example, it is shown that taking the previous DC solution as the starting point of the next DC analysis more than halves the number of iteration required for convergence. A modified version of self-adaptive evolutionary strategies, which incorporates the Metropolis criterion in the selection mechanism, is used as the search algorithm. Smooth penalty mechanisms for biasing constraints are proposed and embedded in the algorithm. Usefulness of the tool is validated by three synthesis examples.     

Wavelet-based enhancement of lung and bowel sounds using fractal dimension thresholding--Part II: application results

The application of the wavelet transform-fractal dimension-based (WT-FD) filter of Part I of this paper to real bioacoustic data, which include explosive lung sounds (ELS) and explosive bowel sounds (EBS) recorded from patients with pulmonary or gastrointestinal dysfunction, respectively, is presented in this paper. The objective of the latter is the evaluation of the performance of the WT-FD filter on different types of bioacoustic signals, varying not only in their structural morphology but also in the degree of their noise contamination. As it is thoroughly described in Part I of this paper, the WT-FD filter uses the fractal dimension to form an efficient way of thresholding the WT coefficients at different resolution scales, keeping, thus, only those that can contribute to the accurate reconstruction of the ELS and EBS signals. Quantitative and qualitative analysis of the experimental results show an efficient performance of the WT-FD filter to circumvent the noise presence (100% detectability rate, 100% sensitivity, 100% specificity) by faithfully extracting the authentic structure of ELS and EBS from the background noise. The WT-FD filter does not require any noise reference signal or noise reference templates. The results from a noise stress test (mean cross-correlation index of the original and the estimated signal converging to 100%; mean normalized maximum amplitude error converging to 0.7%) prove its robustness to various noise levels (0-20 dB), enabling its potential use in similar noise cases met in everyday clinical medicine. Furthermore, the efficient performance of the WT-FD filter facilitates the physician to better interpret the auscultation findings. Due to its simplicity and low computational cost, the WT-FD filter can possibly be implemented in a real-time context to serve as a tool for the continuous ELS and EBS screening.     

Structural Learning of Bayesian Networks using a modified MDL score metric

Bayesian networks are tools as they represent probability distributions as graphs. They work with uncertainties of real systems. Since last decade there is a special interest in learning network structures from data. However learning the best network structure is a NP-Hard problem, so many heuristics algorithms to generate network structures from data were created. Many of these algorithms use score metrics to generate the network model. This paper address learn the structure of ALARM pattern benchmark using K-2 algorithm and a modified MDL as score metric. Results shown that score metrics with parameters that strength the tendency to select simpler network structures are better than score metrics with weaker tendency to select simpler network structures and that modified MDL gives better results than original MDL.     

Characterization of semiconductor interfaces using a modified mixed mode bending apparatus

This research deals with the experimental assessment of the strength of bi-material interfaces as a function of mode mixity, focusing on two dimensional problems. A modified mixed mode bending apparatus is designed and tested, which can be used to measure small forces involved in the delamination of semiconductor packaging materials. Using this setup, it is possible to measure interface strength over nearly the full range of mode mixities using a single specimen design. A finite element model is used to determine interface strength and mode mixity. As an example, the combined numerical-experimental procedure is applied to the interface between copper lead frame (LF) and epoxy molding compound (MCE). A remarkable result is that a double cantilever beam (DCB) test of this interface does not yield the lowest possible interface strength, meaning that it can not be used as a worst case test.     

Planar integration of a resonant-tunneling diode with pHEMT using anovel proton implantation technique

A novel technique of integrating resonant-tunneling diodes (RTDs) with pseudomorphic high-electron-mobility transistors (pHEMTs) is demonstrated. A proton was implanted through the pHEMT layers to convert the RTD structure underneath to a high-resistivity buffer without degrading the performance of the pHEMT. The cutoff frequency is 16 GHz for a 1.5-μm-gate-length pHEMT on such an implanted buffer. Substituting the conventional deep mesa etch with ion implantation maintains a highly planar surface. Such a monolithically integrated RTD/pHEMT oscillator is described