Efficient FIR Filter Implementations for Multichannel BCIs Using Xilinx System Generator

6Citations
Citations of this article
25Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background. Brain computer interface (BCI) is a combination of software and hardware communication protocols that allow brain to control external devices. Main purpose of BCI controlled external devices is to provide communication medium for disabled persons. Now these devices are considered as a new way to rehabilitate patients with impunities. There are certain potentials present in electroencephalogram (EEG) that correspond to specific event. Main issue is to detect such event related potentials online in such a low signal to noise ratio (SNR). In this paper we propose a method that will facilitate the concept of online processing by providing an efficient filtering implementation in a hardware friendly environment by switching to finite impulse response (FIR). Main focus of this research is to minimize latency and computational delay of preprocessing related to any BCI application. Four different finite impulse response (FIR) implementations along with large Laplacian filter are implemented in Xilinx System Generator. Efficiency of 25% is achieved in terms of reduced number of coefficients and multiplications which in turn reduce computational delays accordingly.

Figures

  • Figure 1: A comparison of electromagnetic (pink) and neuroimaging techniques (blue) [5].
  • Figure 2: Phases of BCI (focus of study (green), not discussed (grey)).
  • Figure 3: Large Laplacian in XSG to reduce SNR using localization.
  • Figure 4: Flipping coefficients method in XSG to implement zero phase FIR filter.
  • Figure 5: FFT method in XSG to implement zero phase band pass filtering.
  • Figure 6: MAC filter design without symmetry [11].
  • Figure 7: Manual filter implementation 1 in XSG using basic blocks for implementing MAC engine.
  • Figure 8: MAC filter design with symmetry [12].

References Powered by Scopus

BCI2000: A general-purpose brain-computer interface (BCI) system

2324Citations
N/AReaders
Get full text

An EEG-based brain-computer interface for cursor control

881Citations
N/AReaders
Get full text

Brain computer interfacing: Applications and challenges

426Citations
N/AReaders
Get full text

Cited by Powered by Scopus

FPGA implementation of high performance digital down converter for software defined radio

14Citations
N/AReaders
Get full text

Hardware/Software Co-design of an ECG- PPG Preprocessor: A Qualitative & Quantitative Analysis

7Citations
N/AReaders
Get full text

SPECTRA: a tool for enhanced brain wave signal recognition

7Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Ghani, U., Wasim, M., Khan, U. S., Saleem, M. M., Hassan, A., Rashid, N., … Kashif, A. (2018). Efficient FIR Filter Implementations for Multichannel BCIs Using Xilinx System Generator. BioMed Research International, 2018. https://doi.org/10.1155/2018/9861350

Readers over time

‘18‘19‘20‘21‘22‘23‘2402468

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 11

100%

Readers' Discipline

Tooltip

Engineering 7

58%

Nursing and Health Professions 3

25%

Chemistry 1

8%

Social Sciences 1

8%

Save time finding and organizing research with Mendeley

Sign up for free
0