Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 47, Pages: 1-4
Chhatrapal Singh* and Jaspinder Singh
*Author for correspondence
Department of Electronics and Communication systems, Lovely Professional University, Punjab, India; [email protected]
Feature extraction of biomedical signals plays a significant role in diagnosing of diseases or problems. This paper shows some basic features and processing techniques for biomedical signals and also contains the brief description of neural networks. The biomedical signals are related to the body organs which describe electrically working of associated organs. Examples of biomedical signals are EEG, ECG, EMG. For classifying the biomedical signals, we use ANNs because classification is the most growing research and application area of neural network. Neural networks are used in lot of areas of industry like finance, engineering, biology. Here describes the ANN and its importance. For solving the nonlinear classification problem, used BPNN which is multi- layer feed forward neural network.
Keywords: Artificial Neural Networks (Anns), Biomedical Signal, BPPN Algorithm, EEG, ECG, Wavelet Transforms
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