Parallel feedback Active Noise Control of MRI acoustic noise with signal decomposition using hybrid RLS-NLMS adaptive algorithms

Abstract

This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components and residual random components. Periodicity of fMRI acoustic noise is exploited by using linear prediction (LP) filtering to achieve signal decomposition. A hybrid combination of adaptive filters-Recursive Least Squares (RLS) and Normalized Least Mean Squares (NLMS) are then used to effectively control each component separately. Performance of the proposed FANC system is analyzed and Noise attenuation levels (NAL) up to 32.27 dB obtained by simulation are presented which confirm the effectiveness of the proposed FANC method.

Real-time active noise control of multi-tones and MRI acoustic noise in fMRI bore with signal decomposition and parallel hybrid RLS-NLMS adaptive algorithms

“…The simulation results of this algorithm have been presented in our previous paper [5].Here we present the realtime implementation results of proposed FANC on an fMRI test bed. An initialization phase, which includes determination of period and the synthesis of the dominant periodic components of the Input noise signal, over a data length of 1 second, is done offline and the generated signal estimates are stored.…”

“…In [3], a FANC method introduced to reduce the acoustic noise during MRI/fMRI scan in which an error microphone reads the noise signal near the patient's ears and is processed using adaptive NLMS algorithms in order to achieve a quiet zone near the patient's ears inside the MRI bore. In [5], a parallel FANC method was first proposed and simulation results were presented, which utilized AR modelling approach to decompose the noisy error signal and then controlled using a pair of adaptive filters.…”

Improved Parallel Feedback Active noise control using linear prediction for adaptive noise decomposition

“…[2] provides convenient solution to the problem of LP order determination and performed satisfactorily well for different narrowband periodic signals under different SNRs. In [3], similar approach was used, but the ANC used was a hybrid RLS-NLMS algorithm. However, in [1][2][3], the spectral estimates were obtained 'off-line' using 1 second of initialization data.…”

“…In [3], similar approach was used, but the ANC used was a hybrid RLS-NLMS algorithm. However, in [1][2][3], the spectral estimates were obtained 'off-line' using 1 second of initialization data. Thus these methods were not very effective for signals with varying spectral components.…”