Wavelet threshold based ECG compression using USZZQ and Huffman coding of DSM

In this paper, a new Wavelet threshold based ECG signal compression technique using uniform scalar zero zone quantizer (USZZQ) and Huffman coding on differencing significance map (DSM) is proposed. Wavelet coefficients are selected based on the energy packing efficiency of each sub-band. Significant Wavelet coefficients are quantized with uniform scalar zero zone quantizer. Significance map is created to store the indices of the significant coefficients. This map is encoded efficiently with less number of bits by applying Huffman coding on the differences between indices in the significance map. ECG records from the MIT-BIH arrhythmia database are selected as test data. For the record 117, the proposed technique achieves a compression ratio of 18.7:1 with lower percentage root mean square difference (PRD) compared to other threshold based methods. The proposed technique is tested for MIT-BIH arrhythmia record 119 and a compression ratio of 21.81:1 is achieved with a PRD value of 3.716% which is much lower compared to the reported PRD value of 5.0 and 5.5% of set partitioning in hierarchical tress (SPIHT) and analysis by synthesis ECG compressor (ASEC), respectively. The noise eliminating capability of the proposed technique is also demonstrated in this work. The proposed technique achieves the required compression ratio with less reconstruction error for GSM-based cellular telemedicine system.     

Computationally Efficient Cosine Modulated Filter Bank Design for ECG Signal Compression

In this work, computationally efficient and reliable cosine modulated filter banks (CMFBs) are designed for Electrocardiogram (ECG) data compression. First of all, CMFBs (uniform and non-uniform) are designed using interpolated finite impulse response (IFIR) prototype filter to reduce the computational complexity. To reduce the reconstruction error, linear iteration technique is applied to optimize the prototype filter. Then after, non-uniform CMFB is used for ECG data compression by decomposing ECG signal into various frequency bands. Subsequently, thresholding is applied for truncating the insignificant coefficients. The estimation of the threshold value is done by examining the significant energy of each band. Further, Run-length encoding (RLE) is utilized for improving the compression performance. The method is applied to MIT-BIH arrhythmia database for performance analysis of the proposed work. The experimental observations demonstrate that the proposed method has accomplished high compression ratio with the admirable quality of signal reconstruction. The proposed work provides the average values of compression ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), quality score (QS), correlation coefficient (CC), maximum error (ME), mean square error (MSE), and signal to noise ratio (SNR) are 23.86, 1.405, 2.55, 19.08, 0.999, 0.12, 0.054 and 37.611 dB, respectively. The proposed 8-channel uniform filter bank is used to detect the R-peak locations of the ECG signal. The comparative analysis shows that beats (locations and amplitudes) of both signals (original and reconstructed signals) are same.     

Wavelet weighted blood vessel distortion measure for retinal images

In this paper, a novel wavelet transform based blood vessel distortion measure (WBVDM) is proposed to assess the image quality of blood vessels in the processed retinal images. The wavelet analysis of retinal image shows that different wavelet subbands carry different information about the blood vessels. The WBVDM is defined as the sum of wavelet weighted root of the normalized mean square error of subbands expressed in percentage. The proposed WBVDM is compared with other wavelet based distortion measures such as wavelet mean square error(WMSE), Relative WMSE(Rel WMSE) and root of the normalized WMSE(RNWMSE). The results show that WBVDM performs better in capturing the blood vessel distortion. For distortion in clinically nonsignificant regions, the proposed WBVDM shows a low value of 1.1676 compared to a large mean square error value of 7.9909. The evaluation of correlation using Pearson linear correlation coefficient (PLCC) and Spearman rank order correlation coefficient (SROCC) shows a higher value for the correlation between WBVDM and subjective score. The experimental observations show that WBVDM is able to capture the distortion in blood vessels more effectively and responds weakly to the distortion inherent in the other retinal features.     

ECG signal denoising using higher order statistics in Wavelet subbands

In this work, we propose a novel denoising method based on evaluation of higher-order statistics at different Wavelet bands for an electrocardiogram (ECG) signal. Higher-order statistics at different Wavelet bands provides significant information about the statistical nature of the data in time and frequency. The fourth order cumulant, Kurtosis, and the Energy Contribution Efficiency (ECE) of signal in a Wavelet subband are combined to assess the noise content in the signal. Accordingly, four denoising factors are proposed. Performance of the denoising factors is evaluated and compared with the soft thresholding method. The filtered signal quality is assessed using Percentage Root Mean Square Difference (PRD), Wavelet Weighted Percentage Root Mean Square Difference (WWPRD), and Wavelet Energy-based Diagnostic Distortion (WEDD) measures. It is observed that the proposed denoising scheme not only filters the signal effectively but also helps retain the diagnostic information.     

Wavelet threshold based TDL and TDR algorithms for real-time ECG signal compression

In this paper, two novel and simple, target distortion level (TDL) and target data rate (TDR), Wavelet threshold based ECG compression algorithms are proposed for real-time applications. The issues on the use of objective error measures, such as percentage root mean square difference (PRD) and root mean square error (RMSE) as a quality measures, in quality controlled/guranteed algorithm are investigated with different sets of experiments. For the proposed TDL and TDR algorithm, data rate variability and reconstructed signal quality is evaluated under different ECG signal test conditions. Experimental results show that the TDR algorithm achieves the required compression data rate to meet the demands of wire/wireless link while the TDL algorithm does not. The compression performance is assessed in terms of number of iterations required to achieve convergence and accuracy, reconstructed signal quality and coding delay. The reconstructed signal quality is evaluated by correct diagnosis (CD) test through visual inspection. Three sets of ECG data from three different databases, the MIT-BIH Arrhythmia (mita) (F_s=360 Hz, 11 b/sample), the Creighton University Ventricular Tachyarrhythmia (cuvt) (F_s=250 Hz, 12 b/sample) and the MIT-BIH Supraventricular Arrhythmia (mitsva) (F_s=128 Hz, 10 b/sample), are used for this work. For each set of ECG data, the compression ratio (CR) range is defined. The CD value of 100% is achieved for CR ≤12, CR ≤ 8 and CR ≤ 4 for data from mita, cuvt and mitsva databases, respectively. The experimental results demonstrate that the proposed TDR algorithm is suitable for real-time applications.     

Analysis of ECG signal denoising method based on S-transform

Electrocardiogram (ECG), a noninvasive technique which is used generally as a primary diagnostic tool for cardiovascular diseases. A cleaned ECG signal provides necessary information about the electrophysiology of the heart diseases and ischemic changes that may occur. However in real situation, noise is often embedded with ECG signal during acquisition. In this paper, a novel ECG signal denoising technique is proposed using Stockwell transform (S-transform). This method is evaluated on several normal and abnormal ECG signals of MIT/BIH arrhythmia database, by artificially adding white Gaussian noises to visually inspected clean ECG recordings. The experimental results demonstrate that the proposed method shows the better signal to noise ratio (SNR), lower root mean square error (RMSE) and percent root mean square difference (PRD) compared to generally used ECG denoising method like wavelet transform.     

Influence of the scale function on wavelet transformation of the surface electromyographic signal

The scale function in wavelet transformation (WT) determines wavelet dilation and optimises the processing of a given signal. Here, the objective was to determine the influence of the scale function on the WT of 160 surface electromyograms using second-degree polynomial (WT(poly)) and exponential (WT(exp)) scale functions. For each WT, a mean frequency (MNF) was calculated from the original wavelet spectrum and from the cubic spline interpolated wavelet spectrum, and these were compared with the MNF obtained from a fast Fourier transform (FFT). The total intensity (Tp) for each WT was compared with the root mean square (RMS). The MNFs computed from the original wavelet spectra were significantly (P < 0.05) lower and higher when computed from the reconstructed wavelet spectra than those from the FFT. The Tp computed from WT(poly) showed significantly higher agreement with the RMS than the Tp from WT(exp). Finally, the WT(poly) may serve as a reference in electromyography.     

Evaluation of the kinetic energy of the torso by magneto-inertial measurement unit during the sit-to-stand movement

Sit-to-stand tests are used in geriatrics as a qualitative issue in order to evaluate motor control and stability. In terms of measured indicators, it is traditionally the duration of the task that is reported, however it appears that the use of the kinetic energy as a new quantitative criterion allows getting a better understanding of musculoskeletal deficits of elderly subjects. The aim of this study was to determine the feasibility to obtain the measure of kinetic energy using magneto-inertial measurement units (MIMU) during sit-to-stand movements at various paces. 26 healthy subjects contributed to this investigation. Measured results were compared to a marker-based motion capture using the correlation coefficient and the normalized root mean square error (nRMSE). nRMSE were below 10% and correlation coefficients were over 0.97. In addition, errors on the mean kinetic energy were also investigated using Bland-Altman 95% limits of agreement (0.63 J–0.77 J), RMSE (0.29 J–0.38 J) and correlation coefficient (0.96–0.98). The results obtained highlighted that the method based on MIMU data could be an alternative to optoelectronic data acquisition to assess the kinetic energy of the torso during the sit-to-stand test, suggesting this method as being a promising alternative to determine kinetic energy during the sit-to-stand movement.     

A Novel Weighted Total Difference Based Image Reconstruction Algorithm for Few-View Computed Tomography

In practical applications of computed tomography (CT) imaging, due to the risk of high radiation dose imposed on the patients, it is desired that high quality CT images can be accurately reconstructed from limited projection data. While with limited projections, the images reconstructed often suffer severe artifacts and the edges of the objects are blurred. In recent years, the compressed sensing based reconstruction algorithm has attracted major attention for CT reconstruction from a limited number of projections. In this paper, to eliminate the streak artifacts and preserve the edge structure information of the object, we present a novel iterative reconstruction algorithm based on weighted total difference (WTD) minimization, and demonstrate the superior performance of this algorithm. The WTD measure enforces both the sparsity and the directional continuity in the gradient domain, while the conventional total difference (TD) measure simply enforces the gradient sparsity horizontally and vertically. To solve our WTD-based few-view CT reconstruction model, we use the soft-threshold filtering approach. Numerical experiments are performed to validate the efficiency and the feasibility of our algorithm. For a typical slice of FORBILD head phantom, using 40 projections in the experiments, our algorithm outperforms the TD-based algorithm with more than 60% gains in terms of the root-mean-square error (RMSE), normalized root mean square distance (NRMSD) and normalized mean absolute distance (NMAD) measures and with more than 10% gains in terms of the peak signal-to-noise ratio (PSNR) measure. While for the experiments of noisy projections, our algorithm outperforms the TD-based algorithm with more than 15% gains in terms of the RMSE, NRMSD and NMAD measures and with more than 4% gains in terms of the PSNR measure. The experimental results indicate that our algorithm achieves better performance in terms of suppressing streak artifacts and preserving the edge structure information of the object.     

A least-squares identification algorithm for estimating squat exercise mechanics using a single inertial measurement unit

This study investigated the possibility of estimating lower-limb joint kinematics during a squat exercise performed in the sagittal plane based on data collected from a single inertial measurement unit located on the lower trunk. The human body was modeled as a three-degrees-of-freedom planar chain and the relevant joint angles (ankle, knee, and hip) are represented by Fourier series. A least-squares approach based on the minimization of the difference between the measured and estimated linear accelerations and the angular velocity of the lower trunk was used to solve the related analytical problem. The approach was validated on ten healthy young volunteers (ten trials each) using a force plate and a stereophotogrammetric system to collect reference data. The root mean square differences between the estimated joint angles and those reconstructed with the stereophotogrammetric system were lower than 4° with correlation coefficients higher than 0.99. The ankle joint resultant vertical force component was estimated with an accuracy of about 3% and a high correlation coefficient of r=0.95, whereas much lower percentage accuracies were found for the horizontal force and couple components. The latter accuracies were similar to those affecting these force and couple components as estimated through inverse dynamics and the stereophotogrammetric data in conjunction with the same mechanical model, which suggests that only minor errors were introduced by the proposed algorithm and measurement tools.     

蛋白质-蛋白质对接中打分函数的研究

通过分析蛋白质－蛋白质间的静电、疏水作用和熵效应与相对于晶体结构的蛋白质主链原子的均方根偏差（RMSD）的相关性,定量地考查了它们在蛋白质－蛋白质对接中作为打分函数评价近天然构象的能力。对7个蛋白质复合物体系的分析表明,就水化能而言,原子接触势模型（ACE）优于原子水化参数模型（ASP）,且修正的ACE模型具有更好的评价近天然构象的能力;水化能与静电能结合对评价能力有进一步的提高。最后,我们将静电和修正的ACE水化能结合作为打分函数用于36个蛋白质复合物体系的对接研究,进一步证实了这两种能量项的组合能有效地将近天然结构从分子对接模式中区分出来。     

Quantitative characterization of a biological membrane by means of its spatial autocovariance.

Profiles for the exoplasmic face (EF) of the freeze-fractured plasma membrane from the root storage tissue of red beets are reconstructed by microdensitometry of micrographs of surface-shadowed-platinum carbon replicas. Autocovariance functions (ACFs) are computed from those profiles. The initial portions of the ACFs have a Gaussian form whose parameters (root mean square surface roughness and autocovariance length) are estimated. The parameter estimates are used to show that the pits on the EF faces are in good complementarity with the intramembrane particles seen on the complementary protoplasmic fracture faces.     

ParDOCK: an all atom energy based Monte Carlo docking protocol for protein-ligand complexes

We report here an all-atom energy based Monte Carlo docking procedure tested on a dataset of 226 protein-ligand complexes. Average root mean square deviation (RMSD) from crystal conformation was observed to be approximately 0.53 A. The correlation coefficient (r(2)) for the predicted binding free energies calculated using the docked structures against experimental binding affinities was 0.72. The docking protocol is web-enabled as a free software at www.scfbio-iitd.res.in/dock.     

Abscisic acid signalling when soil moisture is heterogeneous: decreased photoperiod sap flow from drying roots limits abscisic acid export to the shoots

To investigate the contribution of different parts of the root system to total sap flow and leaf xylem abscisic acid (ABA) concentration ([X-ABA]_leaf), individual sunflower ( Helianthus annuus L.) shoots were grafted onto the root systems of two plants grown in separate pots and sap flow through each hypocotyl measured below the graft union. During deficit irrigation (DI), both pots received the same irrigation volumes, while during partial root zone drying (PRD) one pot ('wet') was watered and another ('dry') was not. During PRD, once soil water content ( θ ) decreased below a threshold, the fraction of sap flow from drying roots declined. As θ declined, root xylem ABA concentration increased in both irrigation treatments, and [X-ABA]_leaf increased in DI plants, but [X-ABA]_leaf of PRD plants actually decreased within a certain θ range. A simple model that weighted ABA contributions of wet and dry root systems to [X-ABA]_leaf according to the sap flow from each, better predicted [X-ABA]_leaf of PRD plants than either [X-ABA]_dry, [X-ABA]_wet or their mean. Model simulations revealed that [X-ABA]_leaf during PRD exceeded that of DI with moderate soil drying, but continued soil drying (such that sap flow from roots in drying soil ceased) resulted in the opposite effect.     

Deriving protein dynamical properties from weighted protein contact number

It has recently been shown that in proteins the atomic mean-square displacement (or B-factor) can be related to the number of the neighboring atoms (or protein contact number), and that this relationship allows one to compute the B-factor profiles directly from protein contact number. This method, referred to as the protein contact model, is appealing, since it requires neither trajectory integration nor matrix diagonalization. As a result, the protein contact model can be applied to very large proteins and can be implemented as a high-throughput computational tool to compute atomic fluctuations in proteins. Here, we show that this relationship can be further refined to that between the atomic mean-square displacement and the weighted protein contact-number, the weight being the square of the reciprocal distance between the contacting pair. In addition, we show that this relationship can be utilized to compute the cross-correlation of atomic motion (the B-factor is essentially the auto-correlation of atomic motion). For a nonhomologous dataset comprising 972 high-resolution X-ray protein structures (resolution <2.0 A and sequence identity <25%), the mean correlation coefficient between the X-ray and computed B-factors based on the weighted protein contact-number model is 0.61, which is better than those of the original contact-number model (0.51) and other methods. We also show that the computed correlation maps based on the weighted contact-number model are globally similar to those computed through normal model analysis for some selected cases. Our results underscore the relationship between protein dynamics and protein packing. We believe that our method will be useful in the study of the protein structure-dynamics relationship.     

Universal similarity measure for comparing protein structures

We introduce a new variant of the root mean square distance (RMSD) for comparing protein structures whose range of values is independent of protein size. This new dimensionless measure (relative RMSD, or RRMSD) is zero between identical structures and one between structures that are as globally dissimilar as an average pair of random polypeptides of respective sizes. The RRMSD probability distribution between random polypeptides converges to a universal curve as the chain length increases. The correlation coefficients between aligned random structures are computed as a function of polypeptide size showing two characteristic lengths of 4.7 and 37 residues. These lengths mark the separation between phases of different structural order between native protein fragments. The implications for threading are discussed.     

Comparison of three methods for beat-to-beat-interval extraction from continuous blood pressure and electrocardiogram with respect to heart rate variability analysis.

In recent years the analysis of heart rate variability (HRV) has become a suitable method for characterizing autonomous cardiovascular regulation. The aim of this study was to investigate the differences in HRV estimated from continuous blood pressure (BP) measurement by different methods in comparison to electrocardiogram (ECG) signals. The beat-to-beat intervals (BBI) were simultaneously extracted from the ECG and blood pressure of 9 cardiac patients (10 min, Colin system, 1000-Hz sampling frequency). For both data types, slope, peak, and correlation detection algorithms were applied. The short-term variability was calculated using concurrent 10-min BP and ECG segments. The root mean square errors in comparison to ECG slope detection were: 1.74 ms for ECG correlation detection; 5.42 ms for ECG peak detection; 5.45 ms for BP slope detection; 5.75 ms for BP correlation detection; and 11.96 ms for BP peak detection. Our results show that the variability obtained with ECG is the most reliable. Moreover, slope detection is superior to peak detection and slightly superior to correlation detection. In particular, for ECG signals with higher frequency characteristics, peak detection often exhibits more artificial variability. Besides measurement noise, respiratory modulation and pulse transit time play an important role in determining BBI. The slope detection method applied to ECG should be preferred, because it is more robust as regards morphological changes in the signals, as well as physiological properties. As the ECG is not recorded in most animal studies, distal pulse wave measurement in combination with correlation or slope detection may be considered an acceptable alternative.     

A method for compression — Reconstruction of ECG signals

A new method of data compression — reconstruction for ECG signals is presented. The method gives the ability (a) to control the final accuracy of the reconstructed signal before the transmission (or storage) of samples and (b) to control the compression ratio (CR) in order to obtain an optimum use of the channel capacity. The main advantage of the method was found to be the very strong improvement of the local re-construction during the active periods. Indeed, we can obtain CR values between 3 and 10 with local root mean square error (r.m.s.e.) improvement, compared to the total r.m.s.e. value, by 85% during the active period.     

ROSETTALIGAND: protein-small molecule docking with full side-chain flexibility

Protein-small molecule docking algorithms provide a means to model the structure of protein-small molecule complexes in structural detail and play an important role in drug development. In recent years the necessity of simulating protein side-chain flexibility for an accurate prediction of the protein-small molecule interfaces has become apparent, and an increasing number of docking algorithms probe different approaches to include protein flexibility. Here we describe a new method for docking small molecules into protein binding sites employing a Monte Carlo minimization procedure in which the rigid body position and orientation of the small molecule and the protein side-chain conformations are optimized simultaneously. The energy function comprises van der Waals (VDW) interactions, an implicit solvation model, an explicit orientation hydrogen bonding potential, and an electrostatics model. In an evaluation of the scoring function the computed energy correlated with experimental small molecule binding energy with a correlation coefficient of 0.63 across a diverse set of 229 protein- small molecule complexes. The docking method produced lowest energy models with a root mean square deviation (RMSD) smaller than 2 A in 71 out of 100 protein-small molecule crystal structure complexes (self-docking). In cross-docking calculations in which both protein side-chain and small molecule internal degrees of freedom were varied the lowest energy predictions had RMSDs less than 2 A in 14 of 20 test cases.     

五针热脉冲探头在测定树干液流中的应用

准确测量树干液流对研究树木耗水特性、植物生理和生态水文效应等具有重要意义.本文选用一种新型五针热脉冲多功能数字探头(PHPP),运用热脉冲理论,测量小叶杨树干液流,并与热扩散探针(TDP)进行对比分析,探究五针热脉冲探头测量树干液流的适用性和准确性.结果表明: 五针热脉冲探头能够准确揭示小叶杨树干液流昼夜变化规律,并且与热扩散探针测量结果呈显著的线性相关关系,R²达到0.90,均方根误差为2.75,平均相对误差为11%.PHPP探头能较为精确地识别低液流和逆液流,可以快速准确地拟合热参数,直接测得树干液流速率,应用潜力较大.