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J. Biomedical Science and Engineering, 2009, 2, 177-183

JBiSE

ECG compression and labview implementation
Tatiparti Padma1, M. Madhavi Latha2, Abrar Ahmed3
GRIET, JNTU, Hyderabad, India, Member IETE; 2JNTU, Hyderabad, India, Member IEEE; 3GRIET, Hyderabad, India. Email: tatipartipadma@gmail.com Received 11 February 2009; revised 19 March 2009; accepted 25 March 2009.
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ABSTRACT
It isoften very difficult for the patient to tell the difference between angina symptoms and heart attack symptoms, so it is very important to recognize the signs of heart attack and immediately seek medical attention. A practical case of this type of remote consultation is examined in this paper. To deal with the huge amount of electrocardiogram (ECG) data for analysis, storage and transmission; anefficient ECG compression technique is needed to reduce the amount of data as much as possible while preserving the clinical significant signal for cardiac diagnosis. Here the ECG signal is analyzed for various parameters such as heart rate, QRS-width, etc. Then the various parameters and the compressed signal can be transmitted with less channel capacity. Comparison of various ECG compressiontechniques like TURNING POINT, AZTEC, CORTES, FFT and DCT it was found that DCT is the best suitable compression technique with compression ratio of about 100:1. In addition, different techniques are available for implementation of hardware components for signal pickup the virtual implementation with labview is also used for analysis of various cardiac parameters and to identify the abnormalities likeTachycardia, Bradycardia, AV Block, etc. Both hardware and virtual implementation are also detailed in this context. Keywords: ECG Compression; Labview; Implementation

1. INTRODUCTION
An electrocardiogram (ECG or EKG) is a recording of the electrical activity of the heart over time produced by an electrocardiograph. Electrical impulses in the heart originate in the sinoatrial node and travelthrough the heart muscle where they impart electrical initiation of systole or contraction of the heart. The electrical waves

can be measured at selectively placed electrodes (electrical contacts) on the skin. Electrodes on different sides of the heart measure the activity of different parts of the heart muscle. An ECG displays the voltage between pairs of these electrodes, and the muscleactivity that they measure, from different directions, also understood as vectors. After acquiring the signal, different signal analysis techniques using MATLAB software where various abnormalities can be traced out in ECG of a particular patient. The signal is then transmitted using wireless technology using Blue-Tooth as a transmitting technique. The device operates at a range of 100-150m, a distancethat is ideal for use in a hospital. Digital analysis of electrocardiogram (ECG) signal imposes a practical requirement that digitized data be selectively compressed to minimize analysis efforts and data storage space. Therefore, it is desirable to carry out data reduction or data compression. Data reduction is achieved by discarding digitized samples that are not important for subsequent patternanalysis and rhythm interpretation. Examples of such data reduction algorithms are: AZTEC, turning point (TP). AZTEC retains only the samples for which there is sufficient amplitude change. TP retains points where the signal curves (such as at the QRS peak) and discards every alternate sample. The data reduction algorithms are empirically designed to achieve good reduction without causingsignificant distortion error. Another class of algorithms compresses the data under mathematically rigorous rules, so that digitized samples are compressed and recovered under some reversible mathematical criteria operating under predefined error limits. This approach has the benefit that the original signal can be recovered by with a minimum loss of information. Einthoven named the waves he observed on...