Key result
Image processing standardizes ECG waveforms to a uniform ~8 ms sampling interval by resizing.
Why the study?
The MIT-BIH Normal Sinus Rhythm Database is sampled at 128 Hz with data available at 7.8125 ms intervals, whereas analysis techniques such as artificial neural networks and correlation techniques require ECG samples at desired intervals.
Answers are grounded in this paper and cite their sources.
Demonstrates an image processing method to resample MIT-BIH ECG waveforms at custom intervals, facilitating broader application in neural networks and signal analysis.
MIT-BIH Database is the standard ECG database which is used universally for ECG analysis purpose.MIT-BIH database for normal sinus rhythm is sampled at 128 Hz and the data is available at uniform intervals of 7.8125 ms.To use this data for analysis purpose with various techniques like artificial neural networks, correlation techniques etc., it is required to have samples at desired intervals.Hence this paper proposes an image processing method to convert the samples at desired intervals, so that the MIT-BIH database can be used widely and universally.
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Kumar et al. (2012) studied Normal sinus rhythm (n=1). Image processing-based uniform ECG sampling method vs. Original MIT-BIH database sampling at 7.8125 ms intervals (128 Hz) was evaluated on Uniform sampling interval of extracted ECG waveform. Image processing of MIT-BIH Normal Sinus Rhythm ECG waveforms successfully converted the native 7.8125 ms (128 Hz) sampling interval into a uniform 8 ms (125 Hz) interval by resizing to 127 dpi.
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