ECG Analysis: A Brief Review

2019 ◽  
Vol 12 ◽  
Author(s):  
Saumendra Kumar Mohapatra ◽  
Mihir Narayan Mohanty
Keyword(s):  
Technology Development ◽  
Accurate Result ◽  
Early Stage ◽  
Heart Diseases ◽  
Short Review ◽  
Disease Diagnosis ◽  
Accurate Analysis ◽  
Ecg Analysis ◽  
Proper Analysis ◽  
Living Being

Background: In recent years cardiac problems found proportional to technology development. Cardiac signal (Electrocardiogram) relates to the electrical activity of the heart of a living being and it is an important tool for diagnosis of heart diseases. Method: Accurate analysis of ECG signal can provide support for detection, classification, and diagnosis. Physicians can detect the disease and start the diagnosis at an early stage. Apart from cardiac disease diagnosis ECG can be used for emotion recognition, heart rate detection, and biometric identification. Objective: The objective of this paper is to provide a short review of earlier techniques used for ECG analysis. It can provide support to the researchers in a new direction. The review is based on preprocessing, feature extraction, classification, and different measuring parameters for accuracy proof. Also, different data sources for getting the cardiac signal is presented and various application area of the ECG analysis is presented. It explains the work from 2008 to 2018. Conclusion: Proper analysis of the cardiac signal is essential for better diagnosis. In automated ECG analysis, it is essential to get an accurate result. Numerous techniques were addressed by the researchers for the analysis of ECG. It is important to know different steps related to ECG analysis. A review is done based on different stages of ECG analysis and its applications in society.

scholarly journals Short Review On Varicose Vein And Its Management

2021 ◽  
Vol 12 (1) ◽  
pp. 832-836
Author(s):  
Pranav N ◽  
Anila K N ◽  
Riju.R.Menon
Keyword(s):  
Quality Of Life ◽  
Varicose Vein ◽  
Inflammatory Responses ◽  
Early Stage ◽  
Treatment Strategies ◽  
Short Review ◽  
Disease Diagnosis ◽  
Treated Group ◽  
Severe Condition

A varicose vein is a condition which affects a large number of people in Western countries and India especially, the northern areas. For curing this proper disease diagnosis, sufficient care for patient and treatment strategies are required, to control the symptoms and signs of varicose vein, the flavonoid group of drugs have been widely used for many years. Under this group, Daflon is the most potent and efficient drug which can be used. This enhances the bioavailability and absorption from the gastrointestinal area. Improved quality of patient's life and efficacy makes this drug therapy more potent and significant. Some of the clinical studies have shown its better action for increased venous tone, lymphatic drainage, decreases cosmetic disfigurement, inflammatory responses occur in microcirculation, protection from free radicals and improved quality of life and efficacy. When compared with other available drugs like Polidocanol, Sotradecol, Asclera, Varithena, Sodium tetradecyl sulfate etc. .clinical benefits of Daflon is more. This drug is useful in the early stage and can be used in severe condition along with sclerotherapy, compression treatment and surgery. Increased patient’s quality of life and increased efficacy were observed in Daflon treated group. Thus it is efficacious as a standard therapy alone and also in combination with other conservative treatment.

scholarly journals Recent Trends in Exhaled Breath Diagnosis Using an Artificial Olfactory System

Biosensors ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 337
Author(s):  
Chuntae Kim ◽  
Iruthayapandi Selestin Raja ◽  
Jong-Min Lee ◽  
Jong Ho Lee ◽  
Moon Sung Kang ◽  
...  
Keyword(s):  
Real Time ◽  
Technology Development ◽  
Early Stage ◽  
Development Trend ◽  
Disease Diagnosis ◽  
Health Conditions ◽  
Exhaled Breath ◽  
Human Breath ◽  
Gas Sensor Array ◽  
Olfactory Systems

Artificial olfactory systems are needed in various fields that require real-time monitoring, such as healthcare. This review introduces cases of detection of specific volatile organic compounds (VOCs) in a patient’s exhaled breath and discusses trends in disease diagnosis technology development using artificial olfactory technology that analyzes exhaled human breath. We briefly introduce algorithms that classify patterns of odors (VOC profiles) and describe artificial olfactory systems based on nanosensors. On the basis of recently published research results, we describe the development trend of artificial olfactory systems based on the pattern-recognition gas sensor array technology and the prospects of application of this technology to disease diagnostic devices. Medical technologies that enable early monitoring of health conditions and early diagnosis of diseases are crucial in modern healthcare. By regularly monitoring health status, diseases can be prevented or treated at an early stage, thus increasing the human survival rate and reducing the overall treatment costs. This review introduces several promising technical fields with the aim of developing technologies that can monitor health conditions and diagnose diseases early by analyzing exhaled human breath in real time.

A Proof for the Possibility of Ce-Oxide from CMP Residuals in Si-Wafers by Analytical TEM

2012 ◽  
Author(s):  
Wayne Zhao ◽  
Liem Do Thanh ◽  
Michael Gribelyuk ◽  
Mary-Ann Zaitz ◽  
Wing Lai
Keyword(s):  
Technology Development ◽  
Early Stage ◽  
Chemical Mechanical Planarization ◽  
Particle Cluster ◽  
Limited Region ◽  
Physical Evidence ◽  
Analytical Tem ◽  
Transmission Electron ◽  
Oxide Particles

Abstract Inclusion of cerium (Ce) oxide particles as an abrasive into chemical mechanical planarization (CMP) slurries has become popular for wafer fabs below the 45nm technology node due to better polishing quality and improved CMP selectivity. Transmission electron microscopy (TEM) has difficulties finding and identifying Ce-oxide residuals due to the limited region of analysis unless dedicated efforts to search for them are employed. This article presents a case study that proved the concept in which physical evidence of Ce-rich particles was directly identified by analytical TEM during a CMP tool qualification in the early stage of 20nm node technology development. This justifies the need to setup in-fab monitoring for trace amounts of CMP residuals in Si-based wafer foundries. The fact that Cr resided right above the Ce-O particle cluster, further proved that the Ce-O particles were from the wafer and not introduced during the sample preparation.

scholarly journals Photonic Crystal Nanobeam Cavities for Nanoscale Optical Sensing: A Review

Micromachines ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 72 ◽  
Author(s):  
Da-Quan Yang ◽  
Bing Duan ◽  
Xiao Liu ◽  
Ai-Qiang Wang ◽  
Xiao-Gang Li ◽  
...  
Keyword(s):  
Photonic Crystal ◽  
Optical Waveguides ◽  
Optical Sensing ◽  
Early Stage ◽  
Disease Diagnosis ◽  
Label Free ◽  
Quality Factors ◽  
Integrated Sensor ◽  
Early Stage Disease ◽  
Wide Range

The ability to detect nanoscale objects is particular crucial for a wide range of applications, such as environmental protection, early-stage disease diagnosis and drug discovery. Photonic crystal nanobeam cavity (PCNC) sensors have attracted great attention due to high-quality factors and small-mode volumes (Q/V) and good on-chip integrability with optical waveguides/circuits. In this review, we focus on nanoscale optical sensing based on PCNC sensors, including ultrahigh figure of merit (FOM) sensing, single nanoparticle trapping, label-free molecule detection and an integrated sensor array for multiplexed sensing. We believe that the PCNC sensors featuring ultracompact footprint, high monolithic integration capability, fast response and ultrahigh sensitivity sensing ability, etc., will provide a promising platform for further developing lab-on-a-chip devices for biosensing and other functionalities.

scholarly journals Holistic Metabolomic Laboratory-Developed Test (LDT): Development and Use for the Diagnosis of Early-Stage Parkinson’s Disease

Metabolites ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 14
Author(s):  
Petr G. Lokhov ◽  
Dmitry L. Maslov ◽  
Steven Lichtenberg ◽  
Oxana P. Trifonova ◽  
Elena E. Balashova
Keyword(s):  
Parkinson’S Disease ◽  
Molecular Weight ◽  
Parkinson's Disease ◽  
High Resolution Mass Spectrometry ◽  
Early Stage ◽  
Disease Diagnosis ◽  
The Body ◽  
Low Molecular Weight ◽  
Low Molecular Weight Compounds

A laboratory-developed test (LDT) is a type of in vitro diagnostic test that is developed and used within a single laboratory. The holistic metabolomic LDT integrating the currently available data on human metabolic pathways, changes in the concentrations of low-molecular-weight compounds in the human blood during diseases and other conditions, and their prevalent location in the body was developed. That is, the LDT uses all of the accumulated metabolic data relevant for disease diagnosis and high-resolution mass spectrometry with data processing by in-house software. In this study, the LDT was applied to diagnose early-stage Parkinson’s disease (PD), which currently lacks available laboratory tests. The use of the LDT for blood plasma samples confirmed its ability for such diagnostics with 73% accuracy. The diagnosis was based on relevant data, such as the detection of overrepresented metabolite sets associated with PD and other neurodegenerative diseases. Additionally, the ability of the LDT to detect normal composition of low-molecular-weight compounds in blood was demonstrated, thus providing a definition of healthy at the molecular level. This LDT approach as a screening tool can be used for the further widespread testing for other diseases, since ‘omics’ tests, to which the metabolomic LDT belongs, cover a variety of them.

Understanding the Technology Development Process at the Early Standardization Stage

2014 ◽  
Vol 12 (2) ◽  
pp. 1-20 ◽  
Author(s):  
Vladislav V. Fomin ◽  
Hanah Zoo ◽  
Heejin Lee
Keyword(s):  
Content Analysis ◽  
Software Defined Radio ◽  
Development Process ◽  
Technology Development ◽  
Weak Link ◽  
Early Stage ◽  
Radio Spectrum ◽  
Theoretical Frameworks ◽  
Development Framework ◽  
Practical Usefulness

This research is aimed at developing a document content analysis method to be applied in studies of standardization and technology development. The proposed method integrates two theoretical frameworks: the co-evolutionary technology development framework and the “D-N-S” (Design, Negotiation, Sense-making) framework for anticipatory standardizing. At the backdrop of complex and diversified landscape of science and R&D efforts in the technology domain, and the repeated criticism of the weak link between R&D initiatives and standardization, it is argued that the method offered in this work helps to better understand the internal dynamics of the technology development process at the early stage of standardization or pre-standardization, which, in turn, can help mobilize and direct the R&D initiatives. To demonstrate the practical usefulness of the proposed method, this paper conducts a content analysis of the research contributions presented in the COST Action IC0905 “Techno-Economic Regulatory Framework for Radio Spectrum Access for Cognitive Radio/ Software Defined Radio” (COST-TERRA).

Virus induced hepatocellular carcinoma (HCC) and protein biomarkers

2021 ◽  
Author(s):  
Hamza Abbas Jaffari ◽  
Sumaira Mazhar
Keyword(s):  
Hepatocellular Carcinoma ◽  
Early Stage ◽  
Imaging Techniques ◽  
Disease Diagnosis ◽  
Protein Biomarkers ◽  
Early Disease ◽  
Detection Systems ◽  
Non Invasive ◽  
Viral Hepatitis B ◽  
Current Article

Hepatocellular carcinoma (HCC) is a standout amongst the most widely recognized cancers around the world, and just as the alcoholic liver disease it is also progressed by extreme viral hepatitis B or C. At the early stage of the disease, numerous patients are asymptomatic consequently late diagnosis of HCC occurs resulting in expensive surgical resection or transplantation. On the basis of the alpha fetoprotein (AFP) estimation, combined with the ultrasound and other sensitive imaging techniques used, the non-invasive detection systems are available. For early disease diagnosis and its use in the effective treatment of HCC patients, the identification of HCC biomarkers has provided a breakthrough utilizing the molecular genetics and proteomics. In the current article, most recent reports on the protein biomarkers of HBV or HCV-related HCC and their co-evolutionary association with liver cancer are reviewed.

scholarly journals Amalgamation of Clustering and Meta-heuristic Optimization Techniques for Automated MR Brain Analysis

2019 ◽  
Vol 9 (2S2) ◽  
pp. 642-647
Keyword(s):  
Computation Time ◽  
Medical Practitioner ◽  
Automated Analysis ◽  
Disease Diagnosis ◽  
Tumor Location ◽  
Optimization Techniques ◽  
Heuristic Optimization ◽  
Computer Assisted ◽  
Accurate Analysis ◽  
Tumor Region

Interest in computer-assisted image analysis in increasing among the radiologist as it provides them the additional information to take decision and also for better disease diagnosis. Traditionally, MR image is manually examined by medical practitioner through naked eye for the detection and diagnosis of tumor location, size, and intensity; these are difficult and not sufficient for accurate analysis and treatment. For this purpose, there is need for additional automated analysis system for accurate detection of normal and abnormal tumor region. This paper introduces the new semi-automated image processing method to identify the brain tumor region in Magnetic Resonance Image (MRI) using c means clustering technique along with meta-heuristic optimization, based on Jaya optimization algorithm. The resultant performance of the proposed algorithm (FCM +JA) is examined with the help of key analyzing parameters, MSE-Mean Square Error, PSNR-Peak Signal to Noise Ratio, DOI-Dice Overlap Index and CPU memory utilization. The experimental results of this method show better and enhanced tumor region display in reduced computation time.

scholarly journals A Novel Computational Framework for Precision Diagnosis and Subtype Discovery of Plant With Lesion

2022 ◽  
Vol 12 ◽  
Author(s):  
Fei Xia ◽  
Xiaojun Xie ◽  
Zongqin Wang ◽  
Shichao Jin ◽  
Ke Yan ◽  
...  
Keyword(s):  
Plant Disease ◽  
Early Stage ◽  
Disease Diagnosis ◽  
Image Clustering ◽  
Economic Losses ◽  
Computational Framework ◽  
Great Opportunity ◽  
Deep Embedding ◽  
Food Shortages ◽  
Public Datasets

Plants are often attacked by various pathogens during their growth, which may cause environmental pollution, food shortages, or economic losses in a certain area. Integration of high throughput phenomics data and computer vision (CV) provides a great opportunity to realize plant disease diagnosis in the early stage and uncover the subtype or stage patterns in the disease progression. In this study, we proposed a novel computational framework for plant disease identification and subtype discovery through a deep-embedding image-clustering strategy, Weighted Distance Metric and the t-stochastic neighbor embedding algorithm (WDM-tSNE). To verify the effectiveness, we applied our method on four public datasets of images. The results demonstrated that the newly developed tool is capable of identifying the plant disease and further uncover the underlying subtypes associated with pathogenic resistance. In summary, the current framework provides great clustering performance for the root or leave images of diseased plants with pronounced disease spots or symptoms.

scholarly journals Recent Advances in Non‐nucleophilic Mg Electrolytes

2021 ◽  
Vol 7 ◽  
Author(s):  
Qijie Wu ◽  
Kewei Shu ◽  
Lili Sun ◽  
Haihua Wang
Keyword(s):  
High Performance ◽  
Early Stage ◽  
Oxidation Stability ◽  
Short Review ◽  
High Reactivity ◽  
Inherent Safety ◽  
Practical Application ◽  
Safety Issues ◽  
Ion Structure ◽  
Recent Advances

High-performance electrolyte is still a roadblock for the development of rechargeable magnesium (Mg) batteries. Grignard-type electrolytes were once the only choice in the early stage of rechargeable Mg batteries research. However, due to their nucleophilic nature and high reactivity, Grignard-type electrolytes have inherent safety issues and low oxidation stability, which restrict the development of rechargeable Mg batteries in terms of practical application. Recently, emerging novel Mg battery systems such as Mg-S, Mg-O2/air batteries also require non‐nucleophilic electrolytes with high oxidation stability. This short review summarizes recent advances in non‐nucleophilic Mg electrolytes and aims to provide insights into electrochemical properties and active Mg ion structure of such electrolytes.

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