Augmentation in Healthcare: Augmented Biosignal Using Deep Learning and Tensor Representation

摘要: In healthcare applications, deep learning is a highly valuable tool. It extracts features from raw data to save time and effort for health practitioners. A model capable of extracting the by itself without any external intervention. On other hand, shallow feature extraction techniques depend on user experience in selecting powerful algorithm. this article, we proposed multistage that based spectrogram biosignal. The provides an appropriate representation input biosignal boosts accuracy training testing dataset. next stage, smaller datasets are augmented as larger sets enhance classification datasets. After that, dataset represented TensorFlow more services functionalities, which give flexibility. was compared with different approaches. results show approach better terms accuracy.