Electrocardiogram (ECG) Signal Processing

Sörnmo, Leif; Laguna, Pablo

doi:10.1002/9780471740360.ebs1482

Cited by 114 publications

(70 citation statements)

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“…In order to detect abnormal electrical activity of muscle that can occur in many diseases and conditions such as amyotrophic lateral sclerosis (ALS, Lou Gehrig's disease), carpal tunnel syndrome, muscular dystrophy, neuropathy, sciatic nerve dysfunction, inflammation of muscles, an EMG scan is used to record the electrical activity of muscles [13]. For detecting different types of heart problems such as heart attack, coronary heart diseases and stroke, ECG is used to record the heart's electrical activity to understand how the heart works [14]. To detect blockage or narrowing of the vessels, arteriogram is used to have an X-ray of the arteries and veins.…”

Section: Current Medical Technologies For Medical Data Collections Anmentioning

confidence: 99%

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

2016

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Section: Current Medical Technologies For Medical Data Collections Anmentioning

confidence: 99%

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

2016

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“…This is detected as tiny rises and falls in the voltage between two electrodes placed either side of the heart, which is displayed as a wavy line either on a screen or on paper [7] [8]. This display indicates the overall rhythm of the heart and weaknesses in different parts of the heart muscle [9]. …”

Section: Methodologyand Principle Of Ecgmentioning

confidence: 99%

A Review Paper on Analysis of Electrocardiograph (ECG) Signal for the Detection of Arrhythmia Abnormalities

Joshi¹,

Tomar²,

Tomar³

2014

IJAREEIE

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-ECG conveys information regarding the electrical function of the heart, by altering the shape of its constituent waves, namely the P, QRS, and T waves. ECG Feature Extraction plays a significant role in diagnosing most of the cardiac diseases. One cardiac cycle in an ECG signal consists of the P-QRS-T waves. This feature extraction scheme determines the amplitudes and interval in the ECG signal for subsequent analysis. The amplitude and interval of P-QRS-T segment determine the function of heart. Cardiac Arrhythmia shows a condition of abnormal electrical activity in the heart which is a threat to humans. The aim of this paper presents analyses cardiac disease in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia using analysis of resulting ECG normal & abnormal wave forms. This paper presents a method to analyze electrocardiogram (ECG) signal, extract the features, for the classification of heart beats according to different arrhythmia. Cardiac arrhythmia which are found are Tachycardia, Bradycardia, Supra ventricular Tachycardia, Incomplete Bundle Branch Block, Bundle Branch Block, Ventricular Tachycardia, hence abnormalities of heart may cause sudden cardiac arrest or cause damage of heart. The early detection of arrhythmia is very important for the cardiac patients. Electrocardiogram (ECG) feature extraction system has been developed and evaluated based on the multi-resolution wavelet transform.

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“…Unfortunately, all ECG recordings are contaminated by different types of noise and artifacts sources (Sörnmo & Laguna, 2006) as it is illustrated in Figure 2. These noise sources are: a) Baseline wander is a low-frequency component in the ECG (see Fig.…”

Section: Ecg Filteringmentioning

confidence: 99%