Alexander fractional differential window filter for ECG denoising

The electrocardiogram (ECG) non-invasively monitors the electrical activities of the heart. During the process of recording and transmission, ECG signals are often corrupted by various types of noises. Minimizations of these noises facilitate accurate detection of various anomalies. In the present paper, Alexander fractional differential window (AFDW) filter is proposed for ECG signal denoising. The designed filter is based on the concept of generalized Alexander polynomial and the R–L differential equation of fractional calculus. This concept is utilized to formulate a window that acts as a forward filter. Thereafter, the backward filter is constructed by reversing the coefficients of the forward filter. The proposed AFDW filter is then obtained by averaging of the forward and backward filter coefficients. The performance of the designed AFDW filter is validated by adding the various type of noise to the original ECG signal obtained from MIT-BIH arrhythmia database. The two non-diagnostic measure, i.e., SNR, MSE, and one diagnostic measure, i.e., wavelet energy based diagnostic distortion (WEDD) have been employed for the quantitative evaluation of the designed filter. Extensive experimentations on all the 48-records of MIT-BIH arrhythmia database resulted in average SNR of 22.014?±?3.806365, 14.703?±?3.790275, 13.3183?±?3.748230; average MSE of 0.001458?±?0.00028, 0.0078?±?0.000319, 0.01061?±?0.000472; and average WEDD value of 0.020169?±?0.01306, 0.1207?±?0.061272, 0.1432?±?0.073588, for ECG signal contaminated by the power line, random, and the white Gaussian noise respectively. A new metric named as morphological power preservation measure (MPPM) is also proposed that account for the power preservance (as indicated by PSD plots) and the QRS morphology. The proposed AFDW filter retained much of the original (clean) signal power without any significant morphological distortion as validated by MPPM measure that were 0.0126, 0.08493, and 0.10336 for the ECG signal corrupted by the different type of noises. The versatility of the proposed AFDW filter is also validated by its application on the ECG signal from MIT-BIH database corrupted by the combination of the noises as well as on the real noisy ECG signals are taken from MIT-BIH ID database. Furthermore, the comparative study has also been done between the proposed AFDW filter and existing state of the art denoising algorithms. The results clearly prove the supremacy of our proposed AFDW filter.     

基于小波变换系数的心电信号基线漂移噪声去除方法

目的：心电信号（ECG）是临床诊断心血管疾病的重要依据,但由于基线漂移等噪声的存在影响了其诊断的准确性,因此在心血管诊断中必须先对ECG信号中的基线漂移进行矫正。方法：利用DB3小波对心电信号进行分解,根据分解的特点,将低频小波系数置零,然后重构形成新的ECG信号。结果：将该方法用于MIT-BIH的ECG记录,结果显示能够较好地滤除ECG信号中的基线漂移噪声。结论：该方法可以准确地去除基线漂移分量,并保留ECG的波形变化,为后续的ECG自动检测奠定了基础。     

Urgency of comparative spectral analysis of noises in sanitary inspection

Spectrum (presentation, an image) is a set of all values of any that characterizes, for example, sound-wave propagation. In exact sciences, the expansion of oscillatory function in terms of harmonics, by calculating the Fourier coefficients denotes a spectral analysis. The paper discusses how to further improve the existing sanitary document regulating the order of noise measurement in the area of an apartment block and in residential and public buildings. The author proposes to supplement the document with a procedure for the comparative analysis of the spectral contents of noises.     

论心电信号检测中的噪声与干扰及其消除方法

目的：认识心电信号是从体表检测到的心脏电生理信号,它对心脏疾病的诊断意义重大。方法：强调在心电信号检测过程中,很容易受到噪声（干扰）的影响,如随机噪声、工频干扰、检测系统的内部噪声等。结果：分析了心电检测中各种噪声和干扰产生的原因及消除和减小噪声（干扰）的方法。结论：为了尽可能地消除噪声（干扰）,又不使检测到的心电信号失真,这就需要改进采集电路、滤波电路,运用新的运算方法。     

对接触高温噪声的轧钢工人心电图分析

[目的]了解高温噪声对作业工人心电图的影响.[方法]选择接触高温噪声的轧钢工人546名和低噪声常温作业的机械修理工、电工512名为对照组,进行心电图检查,其数据进行统计学处理分析.[结果]轧钢工心电图异常率为33.7%,对照组组为20.5%两组差异有非常显著性(x2=23.16,P＜0.01);轧钢工人心电图异常发生率与工龄呈正相关(r=0.97).[结论]应降低轧钢工作环境的噪声和加强防暑降温以减少对作业工人的职业危害.     

Physical activity energy expenditure predicts changes in body composition in middle-aged healthy whites: effect modification by age

BACKGROUND: It is unclear whether physical activity energy expenditure (PAEE) predicts changes in body composition. OBJECTIVE: The objective was to describe the independent associations between PAEE and changes in body composition in a population-based cohort. DESIGN: This was a prospective population-based study conducted in 739 (311 men and 428 women) healthy middle-aged (median age: 53.8 y) whites. The median follow-up was 5.6 y. PAEE (MJ/d) was assessed by heart rate monitoring, individually calibrated by using the FLEX heart rate method. Fat mass (FM) and fat-free mass (FFM) were assessed by bioimpedance. RESULTS: Body weight (BW) at follow-up was significantly related to baseline PAEE (P < 0.05) after adjustment for sex, baseline age, FM, FFM, and follow-up time. A significant interaction between PAEE and age (P = 0.023) was observed. After the subjects were stratified (above and below the median for age), BW increased by a mean (+/-SD) of 1.7 +/- 5.9 kg (P < 0.0001) in the younger cohort. In this group, follow-up FM was significantly associated with baseline PAEE (P = 0.036) after adjustment for confounders. In the older cohort, BW did not change between baseline and follow-up. In this group, in contrast with the younger population, follow-up BW, FM, and FFM were all significantly and positively associated with baseline PAEE (P < 0.01 for all). CONCLUSIONS: Baseline PAEE predicts a change in FM in younger adults, who as a group gained weight in this study. In contrast, baseline PAEE in older adults--who were on average weight stable--is associated with a gain in BW, which was explained by an increase in FM and FFM.     

ECG记录图纸数字化过程中的幅值定标方法及其后处理

讨论ECG记录图纸数字化过程中基于自相关的定标方法,并对定标后的心电数据进行数据平滑,50Hz滤波以及基线漂移后处理的.结果表明,自相关定标算法效果非常好,而数据的后处理对于提高ECG记录图纸数字化的精度是至关重要的.     

The impact of varying diagnostic thresholds on affected sib pair linkage analysis

For Mendelian disorders, it is usually simple to classify individuals as either affected or unaffected. By contrast, for “complex” phenotypes, the diagnostic boundary of the disorder is often uncertain. This paper explores the following question: to most efficiently detect linkage in such a complex phenotype by the affected sib pair method, where should the diagnostic threshold be drawn? The model assumes that the disorder is due to a generalized two-allele single major locus (SML) where liability in each genotype is normally distributed. Evidence for linkage between the marker and disease loci is highly dependent on the location of the threshold. The relationship between the placement of the threshold and population linkage information (PLI) is Gaussian-like. At high thresholds, linkage efficiency (LE) (or the amount of linkage information per affected sib pair) is high but PLI is low because the number of affected sib pairs is very small. At low thresholds, the number of affected sib pairs is high, but PLI is low because LE is very low. The model is applied to published SML parameters for schizophrenia, and maximal PLI is achieved at thresholds broader than those for schizophrenia alone.     

Variational mode decomposition based ECG denoising using non-local means and wavelet domain filtering

This paper presents a novel electrocardiogram (ECG) denoising approach based on variational mode decomposition (VMD). This work also incorporates the efficacy of the non-local means (NLM) estimation and the discrete wavelet transform (DWT) filtering technique. Current ECG denoising methods fail to remove noise from the entire frequency range of the ECG signal. To achieve the effective ECG denoising goal, the noisy ECG signal is decomposed into narrow-band variational mode functions (VMFs) using VMD method. The idea is to filter out noise from these narrow-band VMFs. To achieve that, the center frequency information associated with each VMFs is used to exclusively divide them into lower- and higher-frequency signal groups. The higher frequency VMFs were filtered out using DWT-thresholding technique. The lower frequency VMFs are denoised through NLM estimation technique. The non-recursive nature of VMD enables the parallel processing of NLM estimation and DWT filtering. The traditional DWT-based approaches need large decomposition levels to filter low frequency noises and at the same time NLM technique suffers from the rare-patch effect in high-frequency region. On the contrary, in the proposed framework both NLM and DWT approaches complement each other to overcome their individual ill-effects. The signal reconstruction is performed using the denoised high frequency and low frequency VMFs. The simulation performed on the MIT-BIH Arrhythmia database shows that the proposed method outperforms the existing state-of-the-art ECG denoising techniques.     

A novel approach to the extraction of fetal electrocardiogram based on empirical mode decomposition and correlation analysis

Fetal heart rate monitoring is the process of checking the condition of the fetus during pregnancy and it would allow doctors and nurses to detect early signs of trouble during labor and delivery. The fetal ECG (FECG) signal is so weak and also is corrupted by other signals and noises, mainly by maternal ECG signal. It is so hard to acquire a noise-free, precise and reliable FECG using the conventional methods. In this study, a combination of empirical mode decomposition (EMD) algorithms, correlation and match filtering is used for extracting FECG from maternal abdominal ECG signals. The proposed method benefits from match filtering ability to detect fetal signal and QRS complex to detect weak QRS peaks. The combined method, has been applied successfully on different signal qualities, even for signals that their analysis was hard and complicated for other methods. This method is able to detect R-R intervals with high accuracy. It was proved that the complete ensemble empirical mode decomposition method provides a better frequency resolution of modes and also requires less iterations that leads to a considerably less computational cost than EMD and ensemble empirical mode decomposition and can reconstruct the FECG completely from the calculated modes. We believe that this method opens a new field in non-invasive maternal abdominal signal processing so the FECG signal could be extracted with high speed and accuracy.     

System for automatic heart rate calculation in epileptic seizures

This article presents a comprehensive system for automatic heart rate (HR) detection. The system is robust and resistant to disturbances (noise, interferences, artifacts) occurring mainly during epileptic seizures. ECG signal filtration (IIR) and normalization due to skewness and standard deviation were used as preprocessing steps. A key element of the system is a reference QRS complex pattern calculated individually for each ECG recording. Next, a cross-correlation of the reference QRS pattern with short, normalized ECG windows is calculated and the maxima of the correlation are found (R-wave locations). Determination of the RR intervals makes possible calculation of heart rate changes and also heart rate variability (HRV). The algorithm was tested using a simulation in which a noise of an amplitude several times higher than ECG standard deviation levels was added. The proposed algorithm is characterized by high QRS detection accuracy, and high sensitivity and specificity. The algorithm proved to be useful in clinical practice, where it was used to automatically determine HR for ECG signals recorded before and during 58 focal seizures in 56 adult patients with intractable temporal lobe epilepsy.     

消除心电信号工频干扰的新型IIR自适应陷波器设计

目的：设计和实现一种用于消除ECG信号中50Hz工频干扰的新型IIR自适应陷波器。方法：利用Steiglitz—McBride Method（SMM）方法跟踪工频频率，设计基于零极点分布的陷波器，应用最小平方逼近方法得到对称、可控的通带增益。结果：仿真显示设计的新型自适应陷波器能够正确地估计和实时地跟踪工频频率．陷波器的通带增益也可以通过改进的算法得到控制。结论：该陷波器能够有效地跟踪和消除心电信号中的工频干扰。     

Research on electrocardiogram baseline wandering correction based on wavelet transform,QRS barycenter fitting,and regional method

Baseline wandering in electrocardiogram (ECG) is one of the biggest interferences in visualization and computerized detection of waveforms (especially ST-segment) based on threshold decision. A new method based on wavelet transform, QRS barycenter fitting and regional method was proposed in this paper. Firstly, wavelet transform as a coarse correction was used to remove the baseline wandering, whose frequency bands were non-overlapping with that of ST-segment. Secondly, QRS barycenter fitting was applied as a detailed correction. The third, the regional method was used to transfer baseline to zero. Finally, the method in this paper was proved to perform better than filtering and function fitting methods in baseline wandering correction after the long-term ST database (LTST) verification. In addition, the proposed method is simple and easy to carry out, and in current use.     

The effect of acute fluid consumption on measures of impedance and percent body fat using leg-to-leg bioelectrical impedance analysis

OBJECTIVE: To examine the effect of acute fluid consumption on measures of impedance and percent body fat (%BF) using a common leg-to-leg bioelectrical impedance analyzer system. DESIGN: Cross-sectional design with treatment order determined using a counterbalanced assignment. SETTING: University laboratory. SUBJECTS: In total, 21 recreationally active men (mean age 19.7 +/- 1.0 years; body mass index 24.2 +/- 2.3 kg/m2) volunteered to participate in this study. INTERVENTION: Subjects had their body composition assessed on three separate occasions. After an initial baseline body composition measurement, subjects consumed 591 ml of water (H2O), a carbohydrate/electrolyte drink (CHOE), or received nothing, used as the control (CON). Subjects were reassessed 20, 40, and 60 min after baseline (POST). Urine specific gravity (USG) was recorded at baseline and 60 min POST to assess hydration state. RESULTS: There were no significant changes in impedance or total body water (TBW) for any of the measurement time periods after drinking H2O or a CHOE beverage. Body weight (BW) (P < 0.0001) and %BF (P < 0.02) increased significantly 20 min POST and remained elevated at the 40 and 60 min POST time periods. After drinking, USG significantly decreased (P<0.0001) 60 min POST from baseline. For the CON trial, there were no significant changes in BW, %BF, TBW, or USG over time. CONCLUSIONS: Fluid consumption had no effect on lower-body impedance despite causing significant changes in hydration state. A slight overestimation in %BF (approximately 0.5%) was observed due to increased BW in the H20 and CHOE trials. This finding may have little practical significance when assessing body composition by LBIA.     

Predictors of long-term weight maintenance

OBJECTIVE: The purpose of this study was to evaluate available variables of a long-term weight maintenance study to investigate possible factors predisposing to weight regain after a period of weight loss. RESEARCH METHODS AND PROCEDURES: The Maastricht Weight Maintenance Study is an ongoing longitudinal study of healthy men and women (29 men and 62 women; 18 to 65 years of age; BMI = 30.2 +/- 3.1 kg/m(2)). A variety of parameters were measured before and after a very-low-energy diet and after a follow-up of at least 2 years. RESULTS: Mean weight loss was 7.9 +/- 3.6 kg, and percent weight regain was 113.8 +/- 98.1%. Percent BMI regain was negatively associated with an increase in dietary restraint (r = -0.47, p < 0.05). Percent weight regain was negatively correlated with baseline resting metabolic rate (r = -0.38, p = 0.01) and baseline fat mass (r = -0.24, p = 0.05) and positively correlated with the magnitude of change in body weight (BW) expressed as maximum amplitude of BW (r = 0.21, p < 0.05). In addition, amplitude of BW was positively correlated with the frequency of dieting (r = 0.57, p < 0.01). DISCUSSION: The best predictors for weight maintenance after weight loss were an increase in dietary restraint during weight loss, a high baseline resting metabolic rate, a relatively high baseline fat mass favoring a fat-free mass-sparing effect during weight loss, a rather stable BW, and a low frequency of dieting. Therefore, BW maintenance after BW loss seems to be a multifactorial issue, including mechanisms that regulate an individuals' energy expenditure, body composition, and eating behavior in such a way that energy homeostasis is maintained.     

基于快速傅里叶变换的心电模板匹配算法设计

目的：研究心律失常患者的心电信号特征,设计一种能够准确识别正常与异常信号的心电模板匹配算法,以辅助医师诊断心血管疾病.方法：利用快速傅里叶变换计算待测心电与正常模板之间的归一化相关系数,当系数大于某一预设阈值时,判断信号正常;否则提示可能存在异常,建议患者做进一步检查.结果：利用MIT-BIH数据库的心律失常数据进行算法仿真,以正常心拍作模板信号,对10例待测异常心拍进行检测,其中3例心室融合心跳被误判为正常,其余均能正确检测;对12组正常信号进行检测,肢体Ⅱ导联采集的信号全部判断正确,胸导联V1有3例被误判.结论：该算法对肢体Ⅱ导联信号具有较好的适用性,且对室性早搏的检出率较高.     

Important ECG diagnosis-aiding indices of ventricular septal defect children with or without congestive heart failure

In this paper we perform a statistical study of the conventional RR intervals and two newly defined PR' and RT intervals of ECG data. A quadratic classification rule is applied to extract several important ECG diagnosis-aiding indices among normal children and children with ventricular septal defect (VSD) with or without congestive heart failure (CHF). The results show that certain statistics computed from PR', RR and RT intervals are important diagnosis-aiding indices. Best classification vectors are searched for pairwise classification. Two methods, minimum distance criterion and a two-stage classification procedure, are considered for three-way classification. Furthermore, logistic regression models based on transformations of these important diagnosis-aiding indices are proposed. The receiver operating characteristic curves of the proposed models show better performance than those of linear and quadratic logistic models. In order to proceed with this study, a computer algorithm to automatically detect the three intervals is developed and the related ECG data are collected and analysed. The algorithm is also enhanced with an outlier detection procedure for the automatic measurements of the PR' and RT intervals.     

基于多分辨率分析的心电图QRS波检测

从多分辨率分析出发，构造出一个用于心电图R波检测的滤波器，并在此滤波器的基础上提出了一种新的R波检测算法。本文详细论述了滤波器的构造方法和新的R波检测算法的原理及在实现中采用的一些策略，经MIT-BIH标准心律失常数据库验证，该算法对于各种干扰尤其是肌电干扰具有很强的抑制能力。算法实现简单，计算量小，在ECG信号的脱机和实时处理程序中均可使用。     

Serum insulin and ECG abnormalities suggesting coronary heart disease in the populations of Mauritius and Nauru: Cross-sectional and longitudinal associations

Cross-sectional associations between insulin and ECG abnormalities suggestive of ‘possible’ and ‘probable’ coronary heart disease (CHD) in the populations of Nauru (n = 568) and Mauritius (n = 3280) have been examined in both non-diabetic and diabetic subjects. Additionally, the longitudinal relationship between baseline insulin and incident ECG abnormalities has been explored in non-diabetic Nauruans (n = 177) over 5 years. Age-adjusted mean 2-hour serum insulin was generally higher in subjects with ECG abnormalities than those with a normal ECG, but the difference was significant only for non-diabetic Mauritian men (p < 0.01). There was no clear association between prevalence of ECG abnormalities and quintiles of fasting or 2-hr insulin in Mauritians, and in non-diabetic Nauruans there was a non-significant positive association between prevalence of ECG abnormalities and tertiles of 2-hr insulin. Logistic regression analyses showed a slight positive association between 2-hr insulin and ECG abnormalities in non-diabetic Mauritians (p = 0.06 in males, p = 0.09 in females), and non-diabetic male Nauruans (p = 0.054) independent of possible confounders. Fasting insulin was not associated in any group. In longitudinal analyses in Nauruans there were no significant differences in mean baseline fasting or 2-hr serum insulin between subjects who maintained a normal ECG and those who developed abnormalities consistent with ‘possible CHD’ (there were no changes suggestive of ‘probable CHD’). The incidence of ECG changes suggesting ‘possible CHD’ was slightly higher in the upper tertile of baseline fasting insulin in both sexes and 2-hr insulin in females, but when other factors were accounted for, multiple logistic regression analyses did not support this finding. Data from the populations of Mauritius and Nauru do not support a major role for serum insulin in ECG abnormalities suggestive of CHD.     

A new algorithm for ECG interference removal from single channel EMG recording

This paper presents a new method to remove electrocardiogram (ECG) interference from electromyogram (EMG). This interference occurs during the EMG acquisition from trunk muscles. The proposed algorithm employs progressive image denoising (PID) algorithm and ensembles empirical mode decomposition (EEMD) to remove this type of interference. PID is a very recent method that is being used for denoising digital images mixed with white Gaussian noise. It detects white Gaussian noise by deterministic annealing. To the best of our knowledge, PID has never been used before, in the case of EMG and ECG separation or in other 1D signal denoising applications. We have used it according to this fact that amplitude of the EMG signal can be modeled as white Gaussian noise using a filter with time-variant properties. The proposed algorithm has been compared to the other well-known methods such as HPF, EEMD-ICA, Wavelet-ICA and PID. The results show that the proposed algorithm outperforms the others, on the basis of three evaluation criteria used in this paper: Normalized mean square error, Signal to noise ratio and Pearson correlation.