Empirical Mode Decomposition and Wavelet Transform Based ECG Data Compression Scheme

ObjectiveIn health-care systems, compression is an essential tool to solve the storage and transmission problems. In this regard, this paper reports a new electrocardiogram (ECG) data compression scheme which employs sifting function based empirical mode decomposition (EMD) and discrete wavelet transform.MethodEMD based on sifting function is utilized to get the first intrinsic mode function (IMF). After EMD, the first IMF and four significant sifting functions are combined together. This combination is free from many irrelevant components of the signal. Discrete wavelet transform (DWT) with mother wavelet ‘bior4.4’ is applied to this combination. The transform coefficients obtained after DWT are passed through dead-zone quantization. It discards small transform coefficients lying around zero. Further, integer conversion of coefficients and run-length encoding are utilized to achieve a compressed form of ECG data.ResultsCompression performance of the proposed scheme is evaluated using 48 ECG records of the MIT-BIH arrhythmia database. In the comparison of compression results, it is observed that the proposed method exhibits better performance than many recent ECG compressors. A mean opinion score test is also conducted to evaluate the true quality of the reconstructed ECG signals.ConclusionThe proposed scheme offers better compression performance with preserving the key features of the signal very well.     

脑电信号数据压缩及棘波识别的小波神经网络方法

本文在对小波神经网络及其算法研究的基础上,提出了一种对脑电信号压缩表达和痫样脑电棘波识别的新方法。实验结果显示,小波网络在大量压缩数据的同时,能够较好的恢复原有信号,另外,在脑电信号的时频谱等高线图上,得到了易于自动识别的棘波和棘慢复合波特征,说明此方法在电生理信号处理和时频分析方面有着光明的应用前景。     

ECG Data Compression Using Modified Run Length Encoding of Wavelet Coefficients for Holter Monitoring

ObjectiveIn cardiac patient-care, compression of long-term ECG data is essential to minimize the data storage requirement and transmission cost. Hence, this paper presents a novel electrocardiogram data compression technique which utilizes modified run-length encoding of wavelet coefficients.MethodFirst, wavelet transform is applied to the ECG data which decomposes it and packs maximum energy to less number of transform coefficients. The wavelet transform coefficients are quantized using dead-zone quantization. It discards small valued coefficients lying in the dead-zone interval while other coefficients are kept at the formulated quantized output interval. Among all the quantized coefficients, an average value is assigned to those coefficients for which energy packing efficiency is less than 99.99%. The obtained coefficients are encoded using modified run-length coding. It offers higher compression ratio than conventional run-length coding without any loss of information.ResultsCompression performance of the proposed technique is evaluated using different ECG records taken from the MIT-BIH arrhythmia database. The average compression performance in terms of compression ratio, percent root mean square difference, normalized percent mean square difference, and signal to noise ratio are 17.18, 3.92, 6.36, and 28.27 dB respectively for 48 ECG records.ConclusionThe compression results obtained by the proposed technique is better than techniques recently introduced by others. The proposed technique can be utilized for compression of ECG records of Holter monitoring.     

基于小波的心电信号有效性检测方法

目的：检测采集到的信号是否为有效心电信号,提高后续心电诊断和分析的准确率。方法：将采集到的信号进行预处理,即去噪处理,主要抑制基线漂移,50Hz工频及其谐波干扰和肌电干扰;取滑动窗长度为4s,检测该段内信号是否有效。为了验证算法的准确率及对不同心电波形是否具有普遍适用性,对MIT-BIH Arrhythmia Database中48个记录,CU及MIT-BIH Noise Stress Test Database中部分记录进行了仿真、验证。结果：仿真实验证明该方法能正确区分有效和无效信号,错检率较低,实现简单,适合实时处理。结论：本方法准确率高,能减少后续心电诊断和分析的计算量并提高准确率,特别是对室颤检测,符合心电分析的要求。     

基于小波特征分析的手指动作识别研究

目的：本文利用表面肌电（sEMG）信号来研究多种手指组合动作的识别问题。方法：在对采集的四个通道sEMG信号进行降噪预处理的基础上,采用移动加窗处理方法来提取关于手指运动状态的信号活动段,再分析各个信号活动段的小波系数统计特征,进而利用多类支持向量机（SVM分类算法来实现手指组合动作的识别。结果：动作识别率最高达到100％。结论：所采用方法能够有效地识别多种手势动作,并为后续基于肌电信号的实时人机接口系统的研究奠定了理论基础。     

基于小波特征分析的手指动作识别研究

目的:本文利用表面肌电(sEMG)信号来研究多种手指组合动作的识别问题。方法:在对采集的四个通道sEMG信号进行降噪预处理的基础上,采用移动加窗处理方法来提取关于手指运动状态的信号活动段,再分析各个信号活动段的小波系数统计特征,进而利用多类支持向量机(SVM)分类算法来实现手指组合动作的识别。结果:动作识别率最高达到100%。结论:所采用方法能够有效地识别多种手势动作,并为后续基于肌电信号的实时人机接口系统的研究奠定了理论基础。     

基于小波变换的心电信号去噪算法

目的:去除在心电信号采集过程中混入的肌电干扰、工频干扰、基线漂移等噪声信号,避免噪声对心电信号特征点的识别和提取造成误判和漏判。方法:首先利用coif4小波对心电信号按Mallat算法进行分解,然后采用软、硬阈值折衷与小波重构的算法进行去噪。结果:采用MIT/BIH Arrhythmia Database中的心电信号进行仿真、验证,有效去除了三种常见的噪声信号。结论:本方法实时性好,为临床分析与诊断奠定了基础。     

广州市公园对比评价研究——基于社交媒体数据的文本分析

传统公园评价的研究大多集中在单个公园使用满意度方面,存在问卷样本量小、采集时间较集中等缺陷。大数据相关研究的快速发展为公园系统评价提供了新的契机。基于对社交媒体数据的文本分析,研究对比广州市 50 个公园的评价结果,同时探究公园评价与人口统计学特征、地理区位、评价时间以及公园属性之间的关系。研究发现, 1）公园正面评价主要集中在免费设施、环境和特色等方面,而负面评价多集中于公园卫生、交通成本、停车等管理服务方面,广州公园的管理服务水平亟待提升。 2）女性较男性更关注公园能否满足其对社交场所的需求,本地游客较外地游客更关注公园本身的服务质量而非公园的外部属性。 3）基干公园应更侧重其可达性和基本的服务功能,承担大众日常活动;特色公园应更注重满足特定人群的需求及特色打造;自然公园应更关注公园生态质量并能够承担需要较大场地的活动。 4） 2010—2018 年,人们越来越关注公园特色的打造,在公园中的活动类型也越来越多样,现代公园建设更应着力于文化服务质量的提升。研究突破传统公园研究方法的局限,将大数据的手段运用到多个公园的整体评价当中,有助于建立更普适、更有针对性的公园评价指标体系,具有较高的实践价值。     

基于免疫组化和癌症基因组图谱数据分析的脾酪氨酸激酶在宫颈癌中的表达研究

摘要 目的：探讨Syk 在宫颈癌中的表达及其临床意义。方法：应用免疫组化检测Syk在宫颈癌、癌前病变(CIN)和相应的正常宫颈组织中的表达。借助R2生物信息平台挖掘Syk在TCGA数据库305例宫颈鳞癌中的mRNA表达及其与预后的关系。结果：免疫组化结果显示,Syk在宫颈癌巢分化较好的中心区表达较强,在分化较低的癌巢周边区表达较弱。Syk 染色主要定位在宫颈癌和正常宫颈组织的细胞质和细胞膜,正常宫颈组织基底细胞无 Syk 表达,8例CIN组织细胞核中可见Syk表达, 但宫颈癌组织细胞核中未见Syk表达。Syk在宫颈癌、CIN和正常宫颈组织中的阳性率分别是76%、54%、40%,三组间的表达差异具有统计学意义（P=0.001）。Syk 在深度浸润和淋巴结转移中表达较强。数据挖掘结果显示,Syk mRNA在305例不同临床分期的宫颈癌中均表达,Syk mRNA高表达组219例,Syk mRNA低表达组73例,其中13例生存数据缺失,Syk高表达组的患者预后较差。结论：Syk在宫颈癌中的表达提示Syk在宫颈癌中具有致癌蛋白的作用,Syk在某些CIN中的核表达可能与更好的预后相关。     

槭树科植物广义形态学性状分支分析

通过45个广义的形态学性状对槭树科(Aceraceae)尤其是槭属(Acer L.)的主要类群做了分支分析,结果显示：1)槭属内由于各类群分布着较多的同塑性状状态,而难以为属下组间关系的解决提供更多有价值的信息;通过对具体的性状状态分布分析显示,对于象槭属这样在形态上分化较大的类群,由于多数分类性状在不同类群间经历了平行和逆转演化,因而在较低分类阶元水平很难选择合适的性状来通过分支分析构建其系统发育;2)鸡爪槭组(section Palmata)作为整个槭属的基部类群,虽然支持率较低,但与其它类群相比在槭属内维持了较多的原始性状;3)金钱槭属(Dipteronia Oliv.)的两个种作为单系得到了100％的靴带支持,且和槭属作为姐妹群也得到了较好的支持。     

Analysis of Longitudinal Data of Epileptic Seizure Counts – A Two‐State Hidden Markov Regression Approach

This paper discusses a two‐state hidden Markov Poisson regression (MPR) model for analyzing longitudinal data of epileptic seizure counts, which allows for the rate of the Poisson process to depend on covariates through an exponential link function and to change according to the states of a two‐state Markov chain with its transition probabilities associated with covariates through a logit link function. This paper also considers a two‐state hidden Markov negative binomial regression (MNBR) model, as an alternative, by using the negative binomial instead of Poisson distribution in the proposed MPR model when there exists extra‐Poisson variation conditional on the states of the Markov chain. The two proposed models in this paper relax the stationary requirement of the Markov chain, allow for overdispersion relative to the usual Poisson regression model and for correlation between repeated observations. The proposed methodology provides a plausible analysis for the longitudinal data of epileptic seizure counts, and the MNBR model fits the data much better than the MPR model. Maximum likelihood estimation using the EM and quasi‐Newton algorithms is discussed. A Monte Carlo study for the proposed MPR model investigates the reliability of the estimation method, the choice of probabilities for the initial states of the Markov chain, and some finite sample behaviors of the maximum likelihood estimates, suggesting that (1) the estimation method is accurate and reliable as long as the total number of observations is reasonably large, and (2) the choice of probabilities for the initial states of the Markov process has little impact on the parameter estimates.     

基于nrDNA ITS 序列数据的兰属系统发育关系的初步分析

现存的兰属分类系统是基于宏观形态学性状、尤其是花粉块的数目以及唇瓣与蕊柱的愈合程度而建立的.兰属因此而划分为3个亚属:兰亚属 (subgenus Cymbidium),大花亚属(subgenus Cyperorchis) 和建兰亚属 (subgenus Jensoa).本文运用PCR扩增和直接测序的方法分析兰属 (Cymbidium) 27种、3个栽培品种以及3个外类群的核DNA ITS 区段序列.通过最简约性分析产生的ITS系统发育树表明,兰属的3个亚属均可能为不自然的类群.大花亚属表现为一复系群,兰亚属的冬凤兰 (C.dayanum) 隐藏于其中;建兰亚属为一并系群,它的成员之一兔耳兰 (C.lancifolium) 偏离出去而成为兰属一最基部的分支;兰亚属为一复系群,它分为几支而分别与另两个亚属组合在一起.由于兰属ITS序列位点变异率较低,最简约性分析产生的几支主要分支均得不到Bootstrap分析的高度支持,各亚属内组之间的关系也不明确.研究兰属的系统发育关系还需要新的数据.     

A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry

The introduced protocol provides a tool for the analysis of multiprotein complexes in the thylakoid membrane, by revealing insights into complex composition under different conditions. In this protocol the approach is demonstrated by comparing the composition of the protein complex responsible for cyclic electron flow (CEF) in Chlamydomonas reinhardtii, isolated from genetically different strains. The procedure comprises the isolation of thylakoid membranes, followed by their separation into multiprotein complexes by sucrose density gradient centrifugation, SDS-PAGE, immunodetection and comparative, quantitative mass spectrometry (MS) based on differential metabolic labeling (¹⁴N/¹⁵N) of the analyzed strains. Detergent solubilized thylakoid membranes are loaded on sucrose density gradients at equal chlorophyll concentration. After ultracentrifugation, the gradients are separated into fractions, which are analyzed by mass-spectrometry based on equal volume. This approach allows the investigation of the composition within the gradient fractions and moreover to analyze the migration behavior of different proteins, especially focusing on ANR1, CAS, and PGRL1. Furthermore, this method is demonstrated by confirming the results with immunoblotting and additionally by supporting the findings from previous studies (the identification and PSI-dependent migration of proteins that were previously described to be part of the CEF-supercomplex such as PGRL1, FNR, and cyt f). Notably, this approach is applicable to address a broad range of questions for which this protocol can be adopted and e.g. used for comparative analyses of multiprotein complex composition isolated from distinct environmental conditions.     

用RAPD技术探讨冬青属苦丁茶的遗传差异、亲缘关系与分类地位

利用随机扩增多态性DNA (RAPD)技术对 2 2份冬青属苦丁茶不同种质材料的遗传变异进行了研究。 4 0个 10 bp的引物用于多态性检测 ,从中筛选出了 2 7个多态性良好的引物。用该 2 7个引物对上述 2 2份种质材料进行PCR扩增 ,共得到 4 45条DNA谱带 ,其中多态性带4 32条 ,占 97 0 8%。根据扩增结果计算了各份材料之间的遗传距离 ,并用UPGMA构建了聚类树状图。分析结果表明 :2 2份供试材料分成 4类 5组 ,第Ⅰ类为Ilexpentagona (分为A、B两组 :A组为新变种var mashanensisG .M .L .;B组为原变种var pentagona) ,第Ⅱ类为I kudingcha,第Ⅲ类为I latifolia ,第Ⅳ类为I cornuta ;第Ⅱ ,Ⅲ ,Ⅳ三类各有一组材料组成。物种的差异、亲缘关系以及同一物种内不同种质材料在起源地域上的差异均可从系统树中反映出来。RAPD分子标记的结果可作为判断冬青属苦丁茶种质资源材料的起源地域、遗传差异、亲缘关系以及种级水平和种下分类鉴定的重要参考依据