Fig. 2 | Scientific Reports

Fig. 2

From: Ensemble learning for biomedical signal classification: a high-accuracy framework using spectrograms from percussion and palpation

Fig. 2

An Ensemble Learning-Based Method for Classifying Biomedical Signals into Eight Anatomical Regions. Percussion and palpation signals are collected at the start of the procedure. After being processed with Short-Time Fourier Transform (STFT) and normalization procedures to produce spectrogram images, these signals are fed into an ensemble of Convolutional Neural Network (CNN), Support Vector Machine (SVM), and Random Forest (RF) classifiers. Predictions are then generated from the ensemble model.

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