IEEE SENSORS 2006, EXCO, Daegu, Korea / October 22-25, 2006

On-Chip Electrochemical Impedance Spectroscopy for

Biosensor Arrays

Chao Yang, Daniel Rairigh, Andrew MasonDepartment of Electrical & Computer Engineering

Michigan State University, East Lansing, United State{yangchao, rairighd, mason}(egr.msu.edu

Abstract-Electrochemical impedance spectroscopy (EIS) is apowerful tool for characterizing biological materials, includinglipid bilayers and many membrane proteins. However,traditional EIS methods are very slow at low frequencies,where these materials respond in biosensor applications. Toenable dense arrays of biosensors based on tethered bilayerlipid membranes (tBLM), a new approach for EIS has beendeveloped. This paper introduces a methodology and circuitthat can rapidly perform EIS in the lmHz to 100kHzfrequency range. A circuit implementing this new approachhas been realized in 0.5gm CMOS technology with 3.3 voltagepower supply. In the sub-hertz range where membrane proteinbiosensor response is most critical, the circuit can measureimpedance with 8 bit resolution in 20ms, three orders ofmagnitude faster than traditional integrator-based circuits.Though tailored for the low frequency spectrum in biosensorapplications, the EIS circuit can be used to measure impedancein a wide range of sensory materials.

I. INTRODUCTION

Protein modified tethered bilayers lipid membranes(tBLM) [1] provide a means to measure, with highspecificity and high sensitivity, unique biochemical analytesand biological phenomena. They hold great promise in manyapplications of biotechnology including diseases diagnosisand environmental monitoring. Electrochemical impedancespectroscopy (EIS) techniques are the best means tointerrogate many tBLM-based biosensors. Currently, bench-top instruments are used to perform EIS [2,3], and no chip-scale EIS systems exist.

These biosensors offer their greatest potential when usedin high-density arrays of tBLMs modified with differentproteins, which encourages the development of compactsystems. Two constraints impede the further progress in theminiaturization of tBLM-based biosensor arrays [4]. First,routing hundreds of raw signals off the array chip introducesbandwidth challenges as well as performance-limiting noise;thus on-chip instrumentation capable of processing andreducing the raw data is necessary to fully enable thesearrays. Second, the measurement speed of traditional EISmethods is not adequate to interrogate a high density arrayrapidly enough to ensure all important data is recorded.

This paper described an on-chip EIS system targetingthese constraints. In section II, the characteristics of the

This work was supported in part by the Engineering Research CentersProgram of the National Science Foundation under Award Number EEC-9986866.

tBLM biosensor and its interrogation method are discussed.In section III, a new measurement scheme targeting high-density tBLM based biosensor arrays is introduced, and itscircuit realization is presented in section IV.

II. TBLM BASED BIOSENSORS

A. Protein modified tBLM and equavalent circut modelA tBLM is a synthetic lipid membrane that is tethered to

the surface of a solid electrode. Proteins, including ionchannels as shown in Fig. 1(a), can be embedded in thetBLM to mimic the function of a cell membrane orimmobilize the protein for characterization. Only veryspecific analytes will cause these channels to open and allowions to pass through them. The open/closed state of the ionchannels reflects the presence of a certain analyte in thesolution, and the impedance across the membranecorresponds to the analyte concentration. Thus, the protein-modified tBLM can serve as a very sensitive and selectivesensor element. tBLM based biosensors modified bydifferent proteins can be formed into an array to detect andmeasure a wide range of analytes efficiently.

To measure a tBLM biosensor electrically, an equivalentcircuit model is used as shown in Fig. 1(b). The two ends ofthis equivalent circuit present the solution side and solidelectrode side of the tBLM biosensor. R, represents the serialresistance of the solution. Cdl represents the double layercapacitance of the electrode metal-solution interface. CM isthe capacitance of the lipid bilayers. RM is the resistance ofthe lipid bilayer, which is normally much larger than the

(a) (b)Figure 1. (a) Structure and (b) equivalent circuit model of a tBLM-basedbiosensor with an ion channel protein.

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solution resistance R,. The states of the ion channel proteinschange the lipid bilayer resistance. Therefore RM relatesdirectly to the analyte concentration in the solution.

B. Interrogation oftBLM based biosensorIn measuring analyte concentrations, the most important

component in the equivalent circuit model is RM. However,RM cannot be measured directly by applying a DC voltage orcurrent, because Cdl blocks the DC path. Instead,electrochemical impedance spectroscopy (EIS), whichmeasures the impedance over a certain frequency range, isemployed to acquire the overall impedance response of thetBLM biosensor. Because RM dominates the response withina certain frequency range (roughly 0. 1-1OHz for tBLMsensors), the value of RM can be extracted from theimpedance response. Typically, admittance (1/impedance) ismeasured rather than impedance because it is generallyeasier to apply a voltage stimulus and read the current thanthe reverse. If needed, impedance values can always becalculated from admittance data.

There are two common methods for making EISmeasurements. Many systems stimulate the sensor with apulse and then process the response using the Fast FourierTransform (FFT) algorithm [5]. This is not practical for high-density arrays as the digital signal processing (DSP) blocksnecessary to implement the FFT consume a lot of space, andas noted earlier, routing hundreds of raw signals off-chip forexternal processing is also not ideal. The other commonmethod is called a Frequency Response Analyzer (FRA).This system stimulates the sensor one frequency at a timeand then processes the response using multiplication andintegration. The drawback of this approach is that anintegrator needs operate over several periods of theexcitation signal to filter out the AC interference. As a result,FRA is extremely slow (_104 sec) when measuring the lowfrequency range, thus limiting its application for tBLM-based biosensor arrays.

III. NEW INTERROGATION METHOD

To enable on-chip membrane protein biosensor arrays,both the size and the speed of the measurement system iscritical. The traditional FRA method can be compact ifrealized on chip, but suffers from a long settling time for lowfrequency interrogation. To overcome this problem, a newEIS method had been developed to dramatically improvemeasurement speed and provide a response time that isindependent of measurement frequency.

A. Mathematical model ofnew method.In contrast to tradition impedance measurement methods,

the new method quickly extracts complex (real andimaginary) data by simultaneously characterizing twoidentical sensor elements. AC interference is canceledautomatically by analog processing of the complex signal.The system level diagram is shown in Fig. 2. Two identicalsensor elements are interrogated at the same time usingsinusoid stimuli with a 90 phase shift. By processing thestimuli and response in the complex domain (dealing with

W Bosenor eetmnentFigure 2. Signal flow diagram of new EIS method that generates (a) theimaginary portion of admittance and (b) the real portion of admittance.

_~~~~~~~~ 14

V _ aW

Vsinl(-

¢oslt1 Aco$(2

Figure 3. Simplified block diagram of the proposed EIS system thatrealizes the method shown in Fig. 2. Blocks labeled A convert stimulus to adifferential signal and add DC offset. Blocks labeled B convert sensorresponse to a differential signal.

the real and imaginary signals), the real portion andimaginary portion of the admittance are computed directly atthe output without AC interference. Assuming that abiosensor has a current response to a sinusoidal voltagestimulus at frequency c given by

A sin (cot + p) = f(sin (cwt)) (1)

where A is the amplitude and 9 phase response, then the realand imaginary portions of its admittance are Acos(p) andAsin(p), respectively, which can be derived from:

Asin(p) =Asin(wt + ) cos(wt) - Acos(wt + ) sin(wt) (2)

Acos((p)=Asin(wt++) sin(ot)+Acos(tt++) .cos(t) (3)

The signal flows in Fig.2 implement (2) and (3). Theadvantage of this representation is that the output is only aDC value; all AC components are canceled automatically.

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B. Implementation ofthe new method.To apply this new method to the three-electrode

measurement system widely used in electrochemicalinterrogation, the system in Fig. 3 was developed. Twoidentical biosensors are interrogated simultaneously in thissystem. A configurable multiplier pair performs the signalprocessing shown in (2) and (3) in the analog domain andproduce the real or imaginary portion of admittancedepending on the configuration. The circuits in area A havetwo functions: 1) converting the stimulus signal from singleended form to differential signal for differential inputs of themultiplier pair, and 2) applying proper DC bias andtransferring the AC excitation for the sensor. The currentresponse of the sensors is converted into differential voltagefor the multiplier pair within the circuit in area B.

IV. CIRCUIT REALIZATION

A. Configurable multiplier pair blockThe multiplier pair realizes the subtraction or summation

of two products to perform the analog signal processingdescribed by (2) and (3). A modified CMOS four-quadrantanalog multiplier was designed as shown in Fig. 4. Its inputsare differential voltages and its output is a differentialcurrent. The four analog multipliers in this circuit generatethe four different products in (2) and (3). Ctrl configures thecircuit to perform (2) or (3). In either configuration, only twoproducts are needed at any given time, leaving two of themultipliers in an idle state. Although these idle multipliersrequire more chip area, they avoid the linearity degradationassociated with switching the input voltage signal path toreuse the multiplier. Switches at the output generatenegligible nonlinearity because the output is a current. Toachieve 8-bit performance for the whole system, themultiplier pair must provide more than 8-bits of resolution.

B. Interfacing and signal conditioning circuitTo implement (2) and (3), the multiplier pair needs both

the input excitation signal and the current response signal ofthe sensor. However, the properties of the raw excitation and

ipiOr I&

sensor response signals are not ideally suited for analogprocessing. The sensors respond well to small excitationsignals and have a current-mode output, and all inputs andoutputs are single ended. In contrast, the multiplier pairprefers large differential signal inputs in order to achievegood linearity and minimize the effect of noise and offset.The circuits shown in areas A and B in Fig. 3 realize theinterfacing and signal conditioning necessary to bridge thisdifference.

For the circuits in area A of Fig. 3, OPA3, a differentialop-amp, is employed to convert the single-ended stimulus todifferential form. To minimize the effects of the noise andoffset of the OPA3, the amplitude of the input stimulus is setlarge enough for use by the multiplier. To generate a smallamplitude stimulus for the biosensor, the signal is derivedfrom the single-to-differential converting circuit through thetip of a variable resistor. It is fed to the positive input ofOPAl, which forms a feedback loop with the sensor to applythe proper excitation based on the signal at its positive input.OPAI drives the auxiliary electrode of the tBLM, whichcould be a large capacitive load in the nanofarad range [1].The stability of the loop is very critical. Thus, OPAI isdesigned with a cascoded folding structure with a sourcefollower as the output stage. It can provide enough gain andgood phase margin with large capacitive loading.

The circuits in area B are designed to bridge the currentoutput of the biosensor and the differential voltage input ofthe multiplier pair. Two stages are used. The first stagerealizes the conversion from current into voltage. Theconversion gain is tunable through a variable resistor in thefeedback loop to adapt to the impedance of the sensor andprovide a large output swing for the multiplier pair toachieve better accuracy. The second stage finishes the single-ended-to-differential conversion.

OPA3 is used for single-to-differential conversion in bothof the circuits in areas A and B. However, the common modevoltages for these two cases are different, so OPA3 wasdesigned to support a large common mode swing.

4

t it qtr1-I 1 Iut- 1*Yfl +X2*Y2ctrl :0 Lout:=X2(Y1 -X1*Y2

Figure 4. Schematic of the configurable multiplier pairs.

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V. SIMULATION RESULT

The on-chip EIS system was implemented in 0.5ptmCMOS technology and occupies 1.2mm x 0.6mm (Fig. 5). Itconsumes 1.8mA with a 3.3V supply. A dedicated area withmetal contacts is reserved for post CMOS fabrication of theelectrode array and subsequent formation of bio-interfacelayers. The electrode array can be expanded over the entirechip surface without impacting the design or performance ofthe EIS circuit.

Post layout simulations of the multiplier pairs show theycan provide a linearity of at least 56dB for any combinationof input signals, with peak-to-peak swings ranging fromlOOmVpp to 800mVpp (maximum). 56dB assures that anoverall performance of 8 bits is not limited by linearity.

To evaluate the overall performance of the on-chip EISsystem, simulations were run at different frequencies usingthe biosensor model in Fig. 1. Figure 6 shows the admittanceof the Fig. 1 biosensor model, and Fig. 7 shows thesimulated results from the new EIS circuit for the samemodel. Two values ofRM are plotted to illustrate the sensorsoperational response. The similarity of Fig. 6 and Fig. 7shows that the changes on the biosensor are well tracked bythe EIS circuit. A statistical comparison summarized inTable 1 shows that the correlation coefficient between thetwo plots is high. Using linear regression to map the outputto admittance, the average percentage error was about2.65%. The error is expected to reduce further with higherorder regression and further circuit optimization.

While integrator based EIS systems have a response timeproportional to the excitation signal period, this system isindependent of the excitation frequency and the responsetime was measured to be less than 20msec. In the sub-Hertzrange, this provides three orders of magnitude in speedimprovement, guaranteeing a very fast measurement, whichis critical for readout of high-density arrays.

Table 1. Correlation of measurement to the model

RM =50K RM =500K Performance

Real Imaginary Real Imaginaryportion portion portion portion

Correlation 0.9998 0.99988 0.9998 0.9998 0.9998

Average-2.68% -2.72% 4.08% 1.111% 2.65%

% error

VI. CONCLUSION

A new on-chip electrochemical impedance spectroscopysystem was designed for rapid interrogation of on-chipbiosensor arrays. Its response time for the 1mHz to 100kHzfrequency range is less than 20msec. This design has beenfabricated with AMI 0.5ptm CMOS process. Simulationshows that it can provide 8 bits resolution while operating athousand times faster than the traditional method for lowfrequency measurement.

(a) (b)Figure 6. Admittance characteristics of a model tBLM biosensor withdifferent values of RM, (a) imaginary portion (b) real portion.

No" p¢nrtio rpo1 f

.... .......R N 50um

F~q(a) (b)

Figure 7. Simulated admittance measured by the new EIS system atdifferent values of Rm, (a) imaginary portion and (b) real portion.

REFERENCES

[1] G. Krishna, J. Schulte, B. Cornell, R. Pace, and P. Osman, "TetheredBilayer Membranes Containing Ionic Reservoirs: Selectivity andConductance," Langmuir, vol. 19(6), pp. 2294-2305, 2003.

[2] R. Bragos, R. Blanco-Enrich, 0. Casas, J. Rosell, "Characterisation ofdynamic biologic systems using multisine based impedancespectroscopy", IEEE Conf. Instrumentation and MeasurementTechnology, Budapest, Hungary, vol. 1, pp. 44- 47, Jan 2001.

[3] 5. Othman, E. Sacristan, C. Gonzalez, J. Pinzon, J. Aguado, P. Flores,et al,"In situ impedance spectroscopy of the intestinal mucosa in anischemia-reperfusion model", IEEE Int. Conf. on Engineering inMedicine and Biology Society, Cancun, Mexico, vol. 4, pp. 3207-32 10, Jan 2003.

[4] B. Hassler, R. Worden, A. Mason, P. Kim, N. Kohli, J. Zeikus, et al,"Biomimetic Interfaces for a Multifunctional Biosensor ArrayMicrosystem," IEEE Int. Conf. on Sensors, Vienna, Austria, pp. 991-994, October 2004.

[5] G. Popkirov, R. Schindler, "A new impedance spectrometer for theinvestigation of electrochemical systems", Review of ScientificInstruments, vol. 63, pp. 5366- 5372, Nov 1992.

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