基于局部场电位固有模态分量的响应调谐特性研究

局部场电位(LFP)反映了视觉刺激下大脑皮层局部区域神经元集群的响应.LFP响应特征的准确提取,对分析视觉信息的处理机制具有重要意义.本研究针对LFP的非平稳特性,采用具有自适应特征的希尔伯特黄变换,分解LFP固有模态分量,据此研究了大鼠Vl区对刺激光栅空间频率的响应调谐特性,并与多神经元锋电位(MUA)和小波分解提取的Gamma频带进行了对比.结果表明:LFP第二阶固有模态分量对刺激光栅空间频率的调谐特性最强,调谐指数的均值(0.795 1)高于MUA调谐指数(0.631 3)和小波分解调谐指数(0.6646),而且与MUA响应一致率达68.75％.所提出的方法在LFP响应频带特征提取上更有优势.     

Research of fetal ECG extraction using wavelet analysis and adaptive filtering

Extracting clean fetal electrocardiogram (ECG) signals is very important in fetal monitoring. In this paper, we proposed a new method for fetal ECG extraction based on wavelet analysis, the least mean square (LMS) adaptive filtering algorithm, and the spatially selective noise filtration (SSNF) algorithm. First, abdominal signals and thoracic signals were processed by stationary wavelet transform (SWT), and the wavelet coefficients at each scale were obtained. For each scale, the detail coefficients were processed by the LMS algorithm. The coefficient of the abdominal signal was taken as the original input of the LMS adaptive filtering system, and the coefficient of the thoracic signal as the reference input. Then, correlations of the processed wavelet coefficients were computed. The threshold was set and noise components were removed with the SSNF algorithm. Finally, the processed wavelet coefficients were reconstructed by inverse SWT to obtain fetal ECG. Twenty cases of simulated data and 12 cases of clinical data were used. Experimental results showed that the proposed method outperforms the LMS algorithm: (1) it shows improvement in case of superposition R-peaks of fetal ECG and maternal ECG; (2) noise disturbance is eliminated by incorporating the SSNF algorithm and the extracted waveform is more stable; and (3) the performance is proven quantitatively by SNR calculation. The results indicated that the proposed algorithm can be used for extracting fetal ECG from abdominal signals.     

Multi-level basis selection of wavelet packet decomposition tree for heart sound classification

Wavelet packet transform decomposes a signal into a set of orthonormal bases (nodes) and provides opportunities to select an appropriate set of these bases for feature extraction. In this paper, multi-level basis selection (MLBS) is proposed to preserve the most informative bases of a wavelet packet decomposition tree through removing less informative bases by applying three exclusion criteria: frequency range, noise frequency, and energy threshold. MLBS achieved an accuracy of 97.56% for classifying normal heart sound, aortic stenosis, mitral regurgitation, and aortic regurgitation. MLBS is a promising basis selection to be suggested for signals with a small range of frequencies.     

Time-frequency characterization of atrial fibrillation from surface ECG based on Hilbert-Huang transform

In this paper, based on Hilbert-Huang transform (HHT), we develop a new non-invasive time-frequency analysis method to characterize the dynamic behaviour of atrial fibrillation (AF) from surface ECG. We first extract f waves from single-lead ECG records of AF patients using PCA analysis. To capture the non-stationary behaviours of AF signals at different time scales, we use HHT to find the Hilbert spectrum and instantaneous frequency (IF) distribution of residual signals from principal component analysis. Two important feature variables, namely mean IF (mIF) and index of frequency stability over time (IS), are derived from the IF distribution, and in combination will be able to effectively discriminate two different AF types: self-terminating and non-terminating termination. The proposed AF signal decomposition and analysis method will help us efficiently differentiate individual AF patients, advance our understanding of AF mechanisms, and provide useful guidelines for improving administration of AF patients, especially paroxysmal AF.     

ECG feature extraction and disease diagnosis

An important factor to consider when using findings on electrocardiograms for clinical decision making is that the waveforms are influenced by normal physiological and technical factors as well as by pathophysiological factors. In this paper, we propose a method for the feature extraction and heart disease diagnosis using wavelet transform (WT) technique and LabVIEW (Laboratory Virtual Instrument Engineering workbench). LabVIEW signal processing tools are used to denoise the signal before applying the developed algorithm for feature extraction. First, we have developed an algorithm for R-peak detection using Haar wavelet. After 4th level decomposition of the ECG signal, the detailed coefficient is squared and the standard deviation of the squared detailed coefficient is used as the threshold for detection of R-peaks. Second, we have used daubechies (db6) wavelet for the low resolution signals. After cross checking the R-peak location in 4th level, low resolution signal of daubechies wavelet P waves and T waves are detected. Other features of diagnostic importance, mainly heart rate, R-wave width, Q-wave width, T-wave amplitude and duration, ST segment and frontal plane axis are also extracted and scoring pattern is applied for the purpose of heart disease diagnosis. In this study, detection of tachycardia, bradycardia, left ventricular hypertrophy, right ventricular hypertrophy and myocardial infarction have been considered. In this work, CSE ECG data base which contains 5000 samples recorded at a sampling frequency of 500 Hz and the ECG data base created by the S.G.G.S. Institute of Engineering and Technology, Nanded (Maharashtra) have been used.     

Selection of pulse oximetry equipment for ambulatory monitoring

Primary objective : This communication describes the initial stage of a research project concerning the monitoring of SpO₂ in infants prone to periods of spontaneous oxygen desaturation whilst freely moving around their home environment. The primary aim was to determine an appropriate probe type and site together with an assessment of the suitability of two commercially available oximeter units. Research design : The study comprised 19 comparative tests, totalling 162 hours of recordings at resolution one sample every four seconds. Comparisons are drawn between probes, probe sites and pulse oximeters. Main outcomes/ results : The bias and precision is presented with respect to the probe and measurement site. Also, correlation between the trial and reference recordings is considered. Conclusions : It is concluded that ambulatory recording of SpO₂ in infants utilizing equipment suitable for home monitoring can produce diagnostic data equivalent to that of the Ohmeda 3700 biox, but that an indication of movement artefact may be required for confirmation of accuracy. It became apparent that 'wrap around' probes, used on the index finger or big toe are the most suitable.     

Physical activities recognition from ambulatory ECG signals using neuro-fuzzy classifiers and support vector machines

Abstract

The use of wearable recorders for long-term monitoring of physiological parameters has increased in the last few years. The ambulatory electrocardiogram (A-ECG) signals of five healthy subjects with four body movements or physical activities (PA)—left arm up down, right arm up down, waist twisting and walking—have been recorded using a wearable ECG recorder. The classification of these four PAs has been performed using neuro-fuzzy classifier (NFC) and support vector machines (SVM). The PA classification is based on the distinct, time-frequency features of the extracted motion artifacts contained in recorded A-ECG signals. The motion artifacts in A-ECG signals have been separated first by the discrete wavelet transform (DWT) and the time–frequency features of these motion artifacts have then been extracted using the Gabor transform. The Gabor energy feature vectors have been fed to the NFC and SVM classifiers. Both the classifiers have achieved a PA classification accuracy of over 95% for all subjects.     

Reaction Kinetics and Thermodynamic Aspects of Thermoreversibly Cross‐Linked Polymer Networks

The Diels–Alder reaction of furan and maleimide is used to prepare reversibly cross‐linking polymer gels consisting of furan‐bearing polymer chains and bismaleimides. The roles of chain length, stoichiometry, and concentration on gelation kinetics and other properties are evaluated. Additionally, kinetics of the Diels–Alder reactions in the gelling system are compared with the kinetics of small molecule systems. By combining spectroscopic and rheological techniques, a mechanochemical analysis is performed.

     

Acoustic properties of fracture of dental restorative materials and endocrown restorations under quasi-static loading

Objectives(1) To investigate the properties of acoustic emission (AE) signals from fracture of dental materials and endocrown restorations during quasi-static compression using the continuous wavelet transform analysis. (2) To determine by the parameters of AE signals in which structural element of tooth-endocrown system the fracture starts.MethodsFive restorative materials (zirconium dioxide (Prettau zirconia), ceramics (IPS e.max Press), metal ceramics (GC Initial MC+Nicrallium N2 BCS), composite resin (Nano Q), luting cement (Relyx™ U200)) were manufactured into discs, 13 mm diameter, 5 mm thick, which were divided into 5 groups (Group B, C, D, E, F, respectively) and included into Type 1. Twenty-five extracted human molars were divided into 5 groups and included into Type 2: Group A (control, no restoration); BE (tooth restored by zirconium dioxide endocrowns); CE (restored by ceramic endocrowns); DE (restored by metal ceramic endocrowns); EE (restored by composite resin endocrowns). An increasing load was applied to the center of the samples with a hard steel ball until a fracture occurred. The loading rate was 0.12 mm/min. Two-channel AE detection system was used to record the AE activity during testing. The parameters including the peak frequency, bandwidth, duration time and energy of AE signals were analyzed.ResultsThe restorative materials (Type 1) differ from each other by acoustic properties such as the peak frequency main bands and energy of AE signals. The detected AE signals correspond to the different fracture types. The dominant fracture mechanism of Group C, E and F specimens was the macrocracking (brittle fracture), and of Group D specimens was the microcracking, which alternated with the plastic deformation and macrocracking. For the number of events corresponding to the brittle fracture, statistically significant differences (p < 0.05) were found between all group pairs. AE signals were not released during compression test of the zirconium dioxide samples, thus the fracture was not detected.All the AE signals detected during compression test of the different endocrown systems (Type 2) had two peak frequency bands. The fracture of Groups A, BE, CE and DE samples characterized by alternating the micro- and macrocracking with plastic deformation, and the brittle fracture was the dominant fracture mechanism. The restorations of Group EE fractured without plastic deformation. For the number of events corresponding to the brittle fracture, statistically insignificant differences (p > 0.05) were found between Groups A vs CE and A vs EE, and statistically significant differences (p < 0.05) were found between Groups A vs BE and A vs DE.SignificanceThe initiation of fracture in the restorations with endocrowns made from different materials begins with the tooth damage. The metal ceramic endocrown restoration showed the highest fracture resistance, what is especially important for clinical use.     

The influence of irrigation solutions in the inorganic and organic radicular dentine composition

The aim of this study was to analyse changes in radicular dentine composition after different irrigation regimes using attenuated total reflectance Fourier‐transform infrared spectroscopy (ATR‐FTIR). Dentine slices from human single‐root teeth were immersed in: (i) 5.25% sodium hypochlorite (NaOCl) for 1, 5 and 20 min; (ii) 17% EDTA for 1 min; and (iii) 5.25% NaOCl for 20 min, and 17% EDTA and 5.25% NaOCl, both for 1 min. Carbonate/mineral, Amide I/mineral and Amide III/CH₂ ratios were determined using ATR‐FTIR before and after immersion in the irrigation solutions tested. Results showed that 5.25% NaOCl significantly decreased carbonate/mineral, Amide I/mineral and Amide III/CH₂ ratios (P < 0.05). Application of 17% EDTA produced no change in carbonate/mineral ratio (P = 0.120), while an increase in Amide I/mineral in apical third (P = 0.002) and Amide III/CH₂ (P < 0.001) was observed. The combination of NaOCl, EDTA and NaOCl increased carbonate/mineral ratio in coronal third (P = 0.037), and Amide I/mineral (P = 0.003) and Amide III/CH₂ (P = 0.001) ratios. In conclusion, irrigation solutions tested significantly affected radicular dentine composition.