A Low-Power Neuromorphic Bandpass Filter for ... - IEEE Xplore

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The University of Alabama at Birmingham ... In an attempt to reduce the power consumption of ... romorphic low-power bandpass filter with excellent figure-of.
A Low-Power Neuromorphic Bandpass Filter for Biosignal Processing Qingyun Ma, Yang-Guo Li, and Mohammad Rafiqul Haider

Yehia Massoud

Department of Electrical and Computer Engineering The University of Alabama at Birmingham Birmingham, Alabama 35294-4551 Email: {maq, yangguo, mrhaider}@uab.edu

Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester, MA 01609 Email: [email protected]

Abstract-Various types of biosignals originating from the human body are being extensively used for diagnostics as well as therapeutic interventions. Low-power biological signal process­ ing necessitates energy-efficient filter blocks for time-frequency analysis. In an attempt to reduce the power consumption of an implantable biosignal processor, this paper presents a neu­ romorphic low-power bandpass filter with excellent figure-of­ merit. The charging and discharging profiles of different ionic channels of a Si neuron are utilized to achieve the bandpass filter characteristics. The entire filter structure constitutes 5 transistors working in the weak-inversion saturation regions. Designed in a

standard O.13-Mm CMOS process, the proposed bandpass filter consumes only 5

nW

with a 0.5 V supply for a center frequency

of 200 Hz. The center frequency can be tuned from 150 Hz to 1.5 KHz. The Monte Carlo simulation reveals 58 MVrms input­

referred noise and 1 % THD for 7 mVp_p of input signal. The proposed architecture also demonstrates excellent figure-of-merit.

I.

INTRODUCTION

Human body is the source of various kinds of biological signals and the interactions of these biosignals maintain the rhythmic control of different biological events. Among the various kinds of biosignals, Electroencephalography (E EG), Electrocardiography (ECG), Electromyography (EMG), etc. are the most common signals with frequency ranges 0.01 Hz 100 Hz, 0.01 Hz - 300 Hz, and 50 Hz - 3000 Hz, respectively. Power spectrum analysis of the signals helps extracting signal features for compression and feature vector analysis. Unlike digital processor, analog processing unit facilitates low-power, low-noise and less area consumption. In a hearing aid device, an analog signal processor manifests a bank of bandpass filters to identify different frequency channels and helps precise gain or compression control along with further processing in the subsequent stages. To control the gain of the automatic gain control (AGC) amplifiers for a reduced dynamic range hearing problem, a bank of bandpass filters are utilized to identify different channels [1]. The reported bandpass filter in [1] consumes 1.32 fLW power for a center frequency of 1.18 KHz with a dynamic range of 65 dB. Several topologies of implementing the bandpass filters have been reported in the literature. Unlike power hungry operational transconductance amplifiers (OTA) and switched operational amplifiers, gm-C and the switched-capacitor [2] - [4] structures have been considered to meet the stringent requirement of the system power budget. Spoilt current sources

and log-domain topologies [5], [6] have also been investigated. However, they either exhibit large crossover distortion or use non-standard floating gate MOS devices. The performance of a bandpass filter is described by the figure-of-merit (FoM) of the corresponding filter [2]. The lower the value of FoM the better is the system performance. In this paper, we present a neuromorphic low-power bandpass filter with excellent figure-of-merit. The simplified Hodgkin Huxley neuron model is used in this bandpass filter design. Two current mirror based log-domain blocks working as sodium and potassium channels create the current sourcing and sinking profile. The center frequency can be tuned by the bias current. The proposed bandpass filter consumes only 5 nW with a 0.5 V supply for a center frequency of 200 Hz. The Monte Carlo simulation reveals 58 fL Vrms input-referred noise and 1% THD for 7 m Vp_p of input signal. Our proposed structure achieves 41 dB dynamic range and 0.78 x 10-13 FoM. II. T HE

PROPOSED NEUROMORPHIC BANDPASS FILTER ARCHITECTURE

A. Circuit Architecture

The proposed neuromorphic band pass filter architecture is inspired by the ionic mechanism of the biological neuron. A single ion channel in the silicon neuron has three major blocks - sigmoid function block, log-domain block, and linear

I Fig. 1.

Block diagram of a neuron inspired bandpass filter.

978-1-4673-5537-7/13/$31.00 ©2013

IEEE

M2) based log-domain filter. The capacitor in this block brings a pole into INa. The frequency response of the output current from the top section is, INa -

r--Ci���- -: : gain block : I

: I

v;:-l

I I I I !... ________ J I I I

s+

"'h CNa ·UT

(2)

"'h CNa ·UT

where h is the drain current flowing through MI. Similarly, the discharging current IK can be expressed as

I

�M3:

Iref .

Jref

IK=

t