Analisis Aplikasi Filter FIR dan Filter IIR dalam Pra-pemrosesan Sinyal Elektroensefalografi

Abstract

– Electroencephalography (EEG) is a method used to analyze brain activities, detect abnormalities in brain, and diagnose brain-related disease. To extract information from EEG signal, preprocessing steps such as Fast Fourier Transform (FFT), filter, and wavelet decomposition will be needed. This paper primarily focuses on implementation of Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filter design in EEG signal preprocessing in MATLAB software. The result of the simulation indicates that each filter design implemented in EEG preprocessing has different performance and side effect toward signal processing parameters such as phase distortion, amplitude ratio, and processing time. Filter design type implementation also affect power and entropy calculation result.
 Keywords – EEG, FIR filter digital, IIR filter digital, Wavelet Decomposition, GUI-MATLAB

Comparison of FIR and IIR Filters for Audio Signal Noise Reduction

“…Moreover, digital filters are commonly used in digital signal processing, control systems, and communications [16][17] [18]. Digital filters can be implemented as Finite Impulse Response (FIR) filters or Infinite Impulse Response (IIR) filters [3]. The difference between FIR and IIR is presented in Table 1.…”

“…Noise disturbance from the environment is sometimes difficult to predict because there are various types of noise, such as motor vehicles with large cylinder volumes passing by, which cause low-frequency noise; the sound of aircraft jet engines which cause high-frequency noise; or even thunder. Not only found in audio signals, noise can be found in ECG (Electrocardiogram) signals from heart's electrical activity [1], EMG (Electromyography) from muscle's electrical activity [2], and EEG (Electroencephalography) from brain wave [3] [4]. Although information can sometimes be received, it will disrupt the receiver.…”