Electropulsegraph and Wave Classification Framework

Electropulsegraph 및 파형분류 프레임워크

Electropulsegraphy is a medical device that was invented by an orient medical physician and a few engineers to help the physicians to diagnose patients in more systematic way by analyzing waveforms generated from the device. Data generated form the device has been collected for over several decades, and undergoes functional upgrades today. The device generates 33 waveforms that reflect the states of patients. As one of those upgrading efforts, we strive to develop an intelligent algorithm that makes the diagnostic process automatically, which was previously done manually for a long period of time. The logistic regression algorithm is used for our classification problems, which is one of those well-known algorithms for various classification problems such as character recognition systems. Out of the 33 waveforms, we only use 5 waveform data (Type1 toType5) as training data sets to estimate the parameters of the logistic regression. And the parameters are used to classify waveform inputs chosen at random.