Chapter 1 - Introduction to biomedical signal processing and artificial intelligence

Abstract

This chapter provides an overall review of biomedical signal processing using artificial intelligence focusing on various organs of the body. The biosignals are analyzed using different assessment methods, such as, electrocardiogram (ECG/EKG) and electroencephalogram (EEG). The signals are small and reach the sensors attenuated and with noise; hence, there is a need for amplifiers that are used to amplify the signals and can be used for human computer interaction. Since the biosignals are weak in level, they are easily distorted by noise. The most common noise types, thermal noise and flicker noise, are discussed further in this chapter. Later in this chapter, mitigation techniques such as finite impulse response (FIR) filters and Butterworth filters are applied to reduce noise in ECG signal. The objective of computer-aided diagnosis (CAD) is addressed to decrease the rate of false diagnosis by assisting physicians with a second opinion.