Apparatus, method and computer readable storage medium for predicting blood pressure non-compressively using convolutional neural network and long-short-term memory network

A method for predicting blood pressure non-compressively, the method comprising:

• a first step of converting a sequence image of non-pressurized biosignals into an arrayed image in a sequence folding layer;
• a second step of generating a feature map by performing a convolution operation on an arrayed image in a CNN layer;
• a third step of converting the generated feature map into a sequence image in a sequence unfolding layer;
• a fourth step of converting the converted sequence image into one-dimensional data in a flatten layer;
• a fifth step of extracting feature values from the converted one-dimensional data using weights in a long-short-term memory network layer;
• a sixth step of performing image classification using feature values extracted from the long-short-term memory network layer in a fully connected layer;
• and
• a seventh step of predicting systolic blood pressure (SBP) and diastolic blood pressure (DBP) for the classified images in a regression layer.