Early detection of heart diseases using a low-cost compact ECG sensor

2021 ◽  
Author(s):  
Shivam Dixit ◽  
Rahul Kala
Keyword(s):  
Early Detection ◽  
Heart Diseases ◽  
Low Cost

scholarly journals Right use of Screening Pulse Oximetry test for early detection of Critical Congenital Heart Diseases

2018 ◽  
Vol 1 (5) ◽  
pp. 7-11
Author(s):  
Andreas Petropoulos
Keyword(s):  
Early Detection ◽  
Pulse Oximetry ◽  
Low Income ◽  
Screening Test ◽  
Congenital Heart ◽  
Heart Diseases ◽  
Low Cost ◽  
Health Care Systems ◽  
Low Income Countries ◽  
High Morbidity

Introduction: Preventive medicine is the ideal way in dealing with frequent and fatal diseases. Congenital heart disease (CHD) is responsible for the largest proportion of mortality caused by birth defects in the first year of life. Actual numbers and mortality from CHD is increasing. In the developed world the treatment of CHD has escalating costs for health care systems and private covered patients, while in low-income countries the resources are minimal. Prevention/early detection is urgently needed to tackle the increasing needs. Aim: To justify why pulse oximetry (pox) is the best available, early detecting postnatal screening test currently. Conclusion: Although CHD’s are both frequent and carry a high morbidity and mortality, we still lack a single, easy to apply, non-invasive and low-cost screening test, worldwide. The most advantageous method for minimizing CHD deaths worldwide seems to be currently, the combination of clinical assessment with pox. Original publication: https://crimsonpublishers.com/ojchd/pdf/OJCHD.000510.pdf Open Journal of Cardiology and Heart Diseases.

scholarly journals Software System Development to Diagnose Heart Diseases

2019 ◽  
Author(s):  
Renan Yuji Koga Ferreira ◽  
Guilherme Camargo Fabricio De Melloy ◽  
Fabio Sakurayz ◽  
Wesley Attrot
Keyword(s):  
Feature Extraction ◽  
Early Detection ◽  
Embedded System ◽  
Wavelet Transforms ◽  
System Development ◽  
Heart Diseases ◽  
Low Cost ◽  
Computational Cost ◽  
Extraction Algorithm ◽  
Low Computational Cost

Many deaths are caused from heart diseases and several of them could be prevented with early detection. Many people do not have conditions to seek for a doctor or sometimes there are not enough physicians to attend them. In order to detect heart diseases we are developing an electrocardiogram feature extraction algorithm using wavelet transforms prioritizing a low computational cost. This algorithm will be integrated in an embedded system that is under development. This system is going to be accessible, portable and have low cost, because we intend to assist people, mostly those who live in precarious regions, that do not have a physician to attend them. To execute tests on our algorithm we will use the ECG records from MITBIH database and after that we will classify the heartbeats in order to detect anomalies on them.

scholarly journals Right use of Screening Pulse Oximetry test for early detection of Critical Congenital Heart Diseases

2021 ◽  
Vol 1 (4) ◽  
pp. 7-11
Author(s):  
Andreas Petropoulos ◽  
Rustam Huseynov
Keyword(s):  
Early Detection ◽  
Pulse Oximetry ◽  
Low Income ◽  
Screening Test ◽  
Congenital Heart ◽  
Heart Diseases ◽  
Low Cost ◽  
Health Care Systems ◽  
Low Income Countries ◽  
High Morbidity

Introduction: Preventive medicine is the ideal way in dealing with frequent and fatal diseases. Congenital heart disease (CHD) is responsible for the largest proportion of mortality caused by birth defects in the first year of life. Actual numbers and mortality from CHD is increasing. In the developed world the treatment of CHD has escalating costs for health care systems and private covered patients, while in low-income countries the resources are minimal. Prevention/early detection is urgently needed to tackle the increasing needs. Aim: To justify why pulse oximetry (pox) is the best available, early detecting postnatal screening test currently. Conclusion: Although CHD’s are both frequent and carry a high morbidity and mortality, we still lack a single, easy to apply, non-invasive and low-cost screening test, worldwide. The most advantageous method for minimizing CHD deaths worldwide seems to be currently, the combination of clinical assessment with pox. Original publication: https://crimsonpublishers.com/ojchd/pdf/OJCHD.000510.pdf Open Journal of Cardiology and Heart Diseases.

scholarly journals Disease Classification and Biomarker Discovery Using ECG Data

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Rong Huang ◽  
Yingchun Zhou
Keyword(s):  
Biomarker Discovery ◽  
Heart Diseases ◽  
Low Cost ◽  
Recent Decade ◽  
Extraction Methods ◽  
Disease Classification ◽  
Stepwise Discriminant Analysis ◽  
Heavy Tailed ◽  
Sensitivity Specificity ◽  
Sample Quantiles

In the recent decade, disease classification and biomarker discovery have become increasingly important in modern biological and medical research. ECGs are comparatively low-cost and noninvasive in screening and diagnosing heart diseases. With the development of personal ECG monitors, large amounts of ECGs are recorded and stored; therefore, fast and efficient algorithms are called for to analyze the data and make diagnosis. In this paper, an efficient and easy-to-interpret procedure of cardiac disease classification is developed through novel feature extraction methods and comparison of classifiers. Motivated by the observation that the distributions of various measures on ECGs of the diseased group are often skewed, heavy-tailed, or multimodal, we characterize the distributions by sample quantiles which outperform sample means. Three classifiers are compared in application both to all features and to dimension-reduced features by PCA: stepwise discriminant analysis (SDA), SVM, and LASSO logistic regression. It is found that SDA applied to dimension-reduced features by PCA is the most stable and effective procedure, with sensitivity, specificity, and accuracy being 89.68%, 84.62%, and 88.52%, respectively.

Use of RNA isolated from feces as a promising tool for the early detection of colorectal cancer

2012 ◽  
Vol 27 (2) ◽  
pp. 82-89 ◽  
Author(s):  
Giuliano Bernal
Keyword(s):  
Colorectal Cancer ◽  
Early Detection ◽  
Low Cost ◽  
Occult Blood ◽  
Detection Methods ◽  
Fecal Occult Blood ◽  
Public Health Services ◽  
Promising Alternative ◽  
Altered Expression ◽  
Fecal Occult

Colorectal cancer is one of the most common forms of cancer worldwide. Early detection would allow patients to be treated surgically and halt the progression of the disease; however, the current methods of early detection are invasive (colonoscopy and sigmoidoscopy) or have low sensitivity (fecal occult blood test). The altered expression of genes in stool samples of patients with colorectal cancer can be determined by RT-PCR. This is a noninvasive and highly sensitive technique for colorectal cancer screening. According to information gathered in this review and our own experience, the use of fecal RNA to determine early alterations in gene expression due to malignancy appears to be a promising alternative to the current detection methods and owing to its low cost could be implemented in public health services.

scholarly journals Cloud based mobile solution for early detection of Skin Cancer using Artificial Intelligence

2021 ◽  
pp. 312-324
Author(s):  
Pawan Sonawane ◽  
Sahel Shardhul ◽  
Raju Mendhe
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Skin Cancer ◽  
Early Detection ◽  
Transfer Learning ◽  
Network Model ◽  
Neural Network Model ◽  
Mobile Application ◽  
Low Cost ◽  
Skin Tumors

The vast majority of skin cancer deaths are from melanoma, with about 1.04 million cases annually. Early detection of the same can be immensely helpful in order to try to cure it. But most of the diagnosis procedures are either extremely expensive or not available to a vast majority, as these centers are concentrated in urban regions only. Thus, there is a need for an application that can perform a quick, efficient, and low-cost diagnosis. Our solution proposes to build a server less mobile application on the AWS cloud that takes the images of potential skin tumors and classifies it as either Malignant or Benign. The classification would be carried out using a trained Convolution Neural Network model and Transfer learning (Inception v3). Several experiments will be performed based on Morphology and Color of the tumor to identify ideal parameters.

scholarly journals A Low-cost Biomarker-based SAW-Biosensor Design for Early Detection of Prostate Cancer

2017 ◽  
Vol 27 ◽  
pp. 248-249 ◽  
Author(s):  
Alper Sisman ◽  
Etki Gur ◽  
Sencer Ozturk ◽  
Burak Enez ◽  
Bilal Okur ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Early Detection ◽  
Low Cost

Coorscreen: A Low-Cost, on-Site Mammography Screening Program

1996 ◽  
Vol 10 (5) ◽  
pp. 364-370 ◽  
Author(s):  
Mary Greenwood ◽  
Joanne Henritze
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Malignant Disease ◽  
Screening Program ◽  
Low Cost ◽  
Cost Savings ◽  
Participation Rate ◽  
Program Cost ◽  
Mammography Screening Program ◽  
Screening And Prevention

Setting. Coors Brewing Company is a self-insured corporation of 10,600 employees located in Golden, Colorado. Management has long believed in the value of a healthy workforce and has instituted ongoing health and wellness programming since 1981. Program design. Coorscreen was started in September 1985 to create an ongoing awareness of breast cancer screening and prevention for all female employees, spouses, and retirees and to lower the health care costs for the company through early detection of breast cancer. Program impact. From 1985 through 1993, 12,210 mammograms were completed on 3729 employees, spouses, and retirees. The participation rate was 83%. Forty-seven malignant conditions were confirmed during the first 8 years. Pathology reports confirmed 43 early detections (10 employees) and four late detections (two employees). The 10 cases of malignant disease detected early among employees cost an average of $12,388 in terms of direct medical costs, short-term disability, temporary replacement, and ongoing benefits. The two cases detected late among employees cost an average of $143,398. Among spouses, cases of malignant disease detected late have cost an average of $69,230 more than cases detected early. On the basis of early detection for 10 employees and 26 spouses, the total savings are estimated to be $3,110,000. Discussion. The Coorscreen program cost savings for the first 8 years were $3,110,080 because of the lower cost of early versus late detection. Total screening and procedural costs to the company have equaled $668,690. Thus the company has realized a total cost savings of $2,441,190.

scholarly journals Early Detection of Atrial Fibrillation Based on ECG Signals

2020 ◽  
Vol 7 (1) ◽  
pp. 16
Author(s):  
Nuzhat Ahmed ◽  
Yong Zhu
Keyword(s):  
Atrial Fibrillation ◽  
Early Detection ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Research Work ◽  
Threshold Values ◽  
Heart Health ◽  
Ecg Signals ◽  
Normal Heart Rate

Atrial fibrillation, often called AF is considered to be the most common type of cardiac arrhythmia, which is a major healthcare challenge. Early detection of AF and the appropriate treatment is crucial if the symptoms seem to be consistent and persistent. This research work focused on the development of a heart monitoring system which could be considered as a feasible solution in early detection of potential AF in real time. The objective was to bridge the gap in the market for a low-cost, at home use, noninvasive heart health monitoring system specifically designed to periodically monitor heart health in subjects with AF disorder concerns. The main characteristic of AF disorder is the considerably higher heartbeat and the varying period between observed R waves in electrocardiogram (ECG) signals. This proposed research was conducted to develop a low cost and easy to use device that measures and analyzes the heartbeat variations, varying time period between successive R peaks of the ECG signal and compares the result with the normal heart rate and RR intervals. Upon exceeding the threshold values, this device creates an alert to notify about the possible AF detection. The prototype for this research consisted of a Bitalino ECG sensor and electrodes, an Arduino microcontroller, and a simple circuit. The data was acquired and analyzed using the Arduino software in real time. The prototype was used to analyze healthy ECG data and using the MIT-BIH database the real AF patient data was analyzed, and reasonable threshold values were found, which yielded a reasonable success rate of AF detection.

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