Bag-of-words representation for biomedical time series classification

Automatic analysis of biomedical time series such as electroencephalogram (EEG) and electrocardiographic (ECG) signals has attracted great interest in the community of biomedical engineering due to its important applications in medicine. In this work, a simple yet effective bag-of-words representation that is originally developed for text document analysis is extended for biomedical time series representation. In particular, similar to the bag-of-words model used in text document domain, the proposed method treats a time series as a text document and extracts local segments from the time series as words. The biomedical time series is then represented as a histogram of codewords, each entry of which is the count of a codeword appeared in the time series. Although the temporal order of the local segments is ignored, the bag-of-words representation is able to capture high-level structural information because both local and global structural information are well utilized. The performance of the bag-of-words model is validated on three datasets extracted from real EEG and ECG signals. The experimental results demonstrate that the proposed method is not only insensitive to parameters of the bag-of-words model such as local segment length and codebook size, but also robust to noise.     

Electrocardiogram Data Compression Techniques for Cardiac Healthcare Systems: A Methodological Review

Objective: Globally, cardiovascular diseases (CVDs) are one of the most leading causes of death. In medical screening and diagnostic procedures of CVDs, electrocardiogram (ECG) signals are widely used. Early detection of CVDs requires acquisition of longer ECG signals. It has triggered the development of personal healthcare systems which can be used by cardio-patients to manage the disease. These healthcare systems continuously record, store, and transmit the ECG data via wired/wireless communication channels. There are many issues with these systems such as data storage limitation, bandwidth limitation and limited battery life. Involvement of ECG data compression techniques can resolve all these issues.Method: In the past, numerous ECG data compression techniques have been proposed. This paper presents a methodological review of different ECG data compression techniques based on their experimental performance on ECG records of the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database.Results: It is observed that experimental performance of different compression techniques depends on several parameters. The existing compression techniques are validated using different distortion measures.Conclusion: This study elaborates advantages and disadvantages of different ECG data compression techniques. It also includes different validation methods of ECG compression techniques. Although compression techniques have been developed very widely but the validation of compression methods is still a prospective research area to accomplish an efficient and reliable performance.     

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.     

二维心室建模和Brugada综合症仿真

本文以Tusscher提出的人体心室单细胞计算模型为基础,用计算机建模仿真的方法,构建一个心室壁组织的二维网格模型。通过修改细胞的离子通道参数,仿真了正常生理条件下和Brugada症状下三类心室细胞的动作电位和心电图波形。结果显示:Brugada症状下的心电图波形有明显的J波出现,ST-段抬高甚至T波倒置。这与临床医学上的报道基本符合,本研究为用计算机仿真建模研究Brugada综合症打下了基础。     

Mutation in collagen gene induces cardiomyopathy in transgenic mice

In many remodeling tissues, such as the heart, collagen degradation to provide new integrin-binding sites is required for survival. However, complete loss of integrin signaling due to disconnection from extracellular matrix (ECM) leads to apoptosis and dilatation. To test the hypothesis that a mutation in type I collagen gene induces cardiomyopathy, we employed a metalloproteinase-resistant collagen mutant homozygous transgenic male (B6,129-Colla-1) and compared with age-sex matched wildtype C57BL/J6 control mice. At the age of 38-42 weeks, aortic and left ventricle (LV) pressure were measured. The LV wall thickness and diameter were measured by a digital micrometer. The levels of matrix metalloproteinase-2 (MMP-2) activity and cardiospecific tissue inhibitor of metalloproteinase-4 (TIMP-4) were measured by zymography and Western blot analyses, respectively. The levels of collagenolysis were measured by Western blot using anti-collagen antibody. In transgenic and wildtype mice, end-diastolic pressure (EDP) was 8.3 +/- 1.7 and 6.5 +/- 1.1 mmHg; LV diameter was 3.43 +/- 0.07 and 2.94 +/- 0.05 mm; wall thickness was 1.18 +/- 0.03 and 1.28 +/- 0.04 mm; end-diastolic wall stress was 600 +/- 158 and 347 +/- 49 dynes/cm(2), respectively. The increase in LV wall stress was associated with increased MMP-2 activity, increased collagenolysis, and decreased levels of TIMP-4. This leads to reduced elastic compliance in collagen mutant transgenic mice. The occurrence of cardiomyopathy in adult Colla-1 mice may be a significant confounding factor as it may be indicative of increased basal levels of ECM disruption. This phenotype is what would be expected if collagen degradation normally supplies integrin ligands during cardiac muscle remodeling.     

Effects of chronic fluorosis on electrocardiogram in sheep

This study was carried out to evaluate the effects of chronic fluorosis by means of the electrocardiograms in sheep. Ten sheep with fluorosis living around a volcanic mountain (Tendürek Mount) in East Anatolia in Turkey and 10 healthy sheep were used. Leads I, II, III, aVR, aVL, aVF, V₂, V₄, and V₁₀ were recorded in the electrocardiographs of the sheep. All waves were seen in all derivations. The P-Q interval was significantly (p<0.05) prolonged and sinus bradycardia was observed in the sheep with fluorosis. As a result of this, the number of heart beats was decreased significantly (p<0.05); that is, the number of heart beats was 110±15 in the control group and 75±10 in sheep with fluorosis.     

Effect of 50 Hz, 0.2 mT magnetic fields on RBC properties and heart functions of albino rats

In this work the effect of sinusoidal 50 Hz, 0.2 mT magnetic fields on the red blood cells (RBCs) and heart functions of Albino rats were investigated. Twenty-four male Albino rats were equally divided into four groups, A, B, C, and D. Animals from groups B were continuously exposed to the magnetic field for 15 days; and groups C and D, for 30 days. Group A was used as control. Animals from group D were kept after exposure to the magnetic field for a period of 45 days for delayed effect studies. The osmotic fragility and shape of RBCs' membrane and hemoglobin (Hb) structure tests were carried out for all groups. The dielectric relaxation of Hb molecules was measured in the frequency range of 0.1-10 MHz and the dielectric increment (Deltaepsilon), relaxation time (tau), molecular radius (r), and Cole-Cole parameter (alpha) were calculated for all groups. The ECG was measured for all animals before and after exposure to the magnetic field. The results indicated that exposure of the animals to 50 Hz, 0.2 mT magnetic fields resulted in the decrease of RBCs membrane elasticity and permeability and changes in the molecular structure of Hb. The ECG of the exposed animals was considerably altered. The data also indicated that there was no sign of repair in the newly generated RBCs structure and the ECG after removing the animals from the magnetic field, which indicates that the blood generating system was severely injured. The injuries in the heart of the animals were attributed to the loss of some physiological functions of the RBCs as a result of exposures of the rats to the magnetic field.     

织物电极的皮肤-电极接触阻抗测量方法分析

随着可穿戴式健康监测技术的发展,新型心电传感器-织物电极成为人们关注的热点,本文对织物电极的皮肤-电极接触阻抗测量方法进行了综述。首先介绍了织物电极的概念,分析了织物电极的皮肤-电极电化学界面、皮肤-电极电化学界面的等效电路和简化电路模型,得出了皮肤-电极接触阻抗的计算公式;其次,将皮肤-电极接触阻抗的测量方法归纳为直接测量法、参比测量法和模拟皮肤测量法三类,讨论了它们的测量原理和优缺点。本文认为需将模拟皮肤测量法和真实皮肤测量法有机结合,才能有效评价织物电极的阻抗特性,为织物电极的性能评价和心电信号采集电路的设计提供重要依据。最后,本文对织物电极待解决的问题进行了分析讨论。     

A lead dependent ischemic episodes detection strategy using Hermite functions

In this work a new strategy for automatic detection of ischemic episodes is proposed. A new measure for ST deviation based on the time–frequency analysis of the ECG and the use of a reduced set of Hermite basis functions for T wave and QRS complex morphology characterization, are the key points of the proposed methodology.Usually, ischemia manifests itself in the ECG signal by ST segment deviation or by QRS complex and T wave changes in morphology. These effects might occur simultaneously. Time–frequency methods are especially adequate for the detection of small transient characteristics hidden in the ECG, such as ST segment alterations. A Wigner–Ville transform-based approach is proposed to estimate the ST shift. To characterize the alterations in the T wave and the QRS morphologies, each cardiac beat is described by expansions in Hermite functions. These demonstrated to be suitable to capture the most relevant morphologic characteristics of the signal. A lead dependent neural network classifier considers, as inputs, the ST segment deviation and the Hermite expansion coefficients. The ability of the proposed method in ischemia episodes detection is evaluated using the European Society of Cardiology ST–T database. A sensitivity of 96.7% and a positive predictivity of 96.2% reveal the capacity of the proposed strategy to perform ischemic episodes identification.