Recent Studies on Applications Using Biomedical Signal Processing: A Review

Abstract

The intend of this article is to review the various studies on utilizations of biomedical signal processing moreover present a comprehensive view. Different approaches to biomedical signal processing such as using ECG, EEG, EMG, PCG and Neurological/Cardiological signal processing methods are examined. Various databases, signal processing methods used, features extracted, classifiers employed and the performance evaluation results obtained are reviewed here, along with different filters used for diverse biomedical Applications. Major classifiers such as SVM, BPNN, CNN, PNN, RNN, LSTM, ANN and Fuzzy neural networks (FNN) linked with AI are reviewed, along with AI based biomedical signal processing. Comparative analyses of different parameters of signal processing methods, feature extraction techniques, and classifiers used in different biomedical signal processing applications are presented, in tabulated and text forms. This study should be helpful to different researchers and biomedical engineers, as well as medical practitioners working in biomedical signal processing domains.