biosensors

Article
Design and Fabrication of a BiCMOS Dielectric
Sensor for V iscosity Measurements: A Possible
Solution for Early Detection of COPD
Pouya Soltani Zarrin 1, * ID , Farabi Ibne Jamal 1 ID , Subhajit Guha 1 , Jan W essel 1 ,
Dietmar Kissinger 1,2 and Christian W enger 1,3 ID
1 IHP , Im T echnologiepark 25, 15236 Frankfurt/Oder, Germany; [email protected] (F .I.J.);
[email protected] (S.G.); wessel@ihp-microelectr onics.com (J.W .);
dkissinger@ihp-microelectr onics.com (D.K.); wenger@ihp-microelectr onics.com (C.W .)
2 Institute of High-Frequency and Semiconductor System T echnologies, T echnical University of Berlin,
10623 Berlin, Germany
3 Brandenburg Medical School Theodor Fontane, 16816 Berlin, Germany
* Correspondence: soltani@ihp-micr oelectronics.com; T el.: +49-(335)-5625 (ext. 218)
Received: 22 June 2018; Accepted: 17 August 2018; Published: 21 August 2018
     
  

Abstract:
The viscosity variation of sputum is a common symptom of the progr ession of Chr onic
Obstructive Pulmonary Disease (COPD). Since the hydration of the sputum defines its viscosity level,
dielectric sensors could be used for the characterization of sputum samples collected fr om patients for
early diagnosis of COPD. In this work, a CMOS-based dielectric sensor for the real-time monitoring
of sputum viscosity was designed and fabricated. A pr oper packaging for the ESD-protection and
short-cir cuit prevention of the sensor was developed. The performance evaluation results show that
the radio fr equency sensor is capable of measuring dielectric constant of biofluids with an accuracy
of 4.17%. Integration of this sensor into a portable system will result in a hand-held device capable of
measuring viscosity of sputum samples of COPD-patients for diagnostic purposes.
Keywords:
Sputum–Mucin; dielectric measurements; CMOS viscosity sensor; radio frequency sensor;
V iscometer; biosensors; pr ecision diagnostics
1. Introduction
Chr onic Obstructive Pulmonary Disease (COPD) is one of the leading causes of death among
developed countries [
1
]. Although studies suggest that the early diagnosis could effectively decr ease
the mortality rate of COPD, many patients go undiagnosed until the late stages of their disease [
2
].
Abnormal sputum, infection, and br onchial spasm are the thr ee main syndromes of chr onic bronchial
disease. Sputum specimens contain saliva, serum transudate, and glycoproteins. Mucus glycopr oteins
(mucin) ar e good mediums for bacterial growth and ar e responsible for the viscous pr operties of mucus.
As a r esult, characterization and rapid screening of the mucus could be used for early diagnosis of
COPD [
3
]. Since the muco–protein content and the hydration of the sputum determine its viscosity
level, monitoring the viscosity of the sputum collected fr om a patient could provide useful diagnostic
information for the disease [ 3 , 4 ].
Recent advancements in the development of viscosity sensors for biofluids are discussed in [
5
].
A wide range of commer cially available viscometers were designed based on piezoelectric sensors.
For example, Micr ovisk (Microvisk Ltd., Oxfor dshire, UK), a commer cially available viscometer ,
analyzes glucose concentration in blood for Point-of-Care (POC) applications using Micr o Electro
Mechanical Systems (MEMS). Similarly , various resear ch-oriented viscometers have been developed for
blood analysis or coagulation monitoring using the MEMS technology [
5
–
7
]. The key principle of these
Biosensors 2018 , 8 , 78; doi:10.3390/bios8030078 www .mdpi.com/journal/biosensors

Biosensors 2018 , 8 , 78 2 of 13
piezoelectric-based viscosity sensors is based on the deflation of their piezo material-based cantilevers
or beams when they ar e exposed to the viscous fluid. Deformation of these structur es generates an
electrical output depending on their readout mechanism. As a result, the generated electrical output
indicates the viscosity of the fluid exposed to the sensor . Although MEMS-based sensors are one of the
most well-established sensing technologies, some drawbacks restrict their application for viscosity
measur ements. The main disadvantage of these sensors is the r esetting of their cantilevers back to
the original position, causing calibration and accuracy issues. Mor eover , the viscous nature of the
sensing fluid causes a considerable amount of damping on the cantilever vibration, impairing the
sensor ’s function. Furthermore, ther e is a significant amount of coupling between the fluid flow and
the cantilever vibration that influences the acquir ed results fr om the sensor . In addition, the existing
amount of drift in these sensors questions their reliability for long term operations [
7
]. In a work
by Cakmak et al., a MEMS-based viscosity sensor was developed on a Complementary Metal Oxide
Semiconductor (CMOS) platform. Although miniaturization of the system reduced damping ef fects
and fluid flow rate, no significant impr ovements in terms of sensor accuracy or drift were achieved [
8
].
As an alternative technology , a pressur e-based viscometer was developed for measuring blood glucose
levels [
9
]. The needle-type glucose sensor consisted of two hollow fibers in which the viscous fluid
was pumped up with a constant rate of 5
µ
L/h. In this design, two pr essure sensors wer e placed at
both ends of the fibers and the pr essure dif ference cr eated by the flow determined the viscosity of the
sample fluid. Apart from the innovative design of the sensor , its long response time (5 to 10 minutes),
low r esolution, and limited accuracy made its clinical application unacceptable [
9
]. In contrast, optical
biosensors ar e known as a well-established modality capable of providing accurate r esults for clinical
applications [
10
–
13
]. However , they suffer fr om a few disadvantages for POC applications such as
high power consumption, high cost, lar ge sample volume requir ements, lack of portability , operation
complexity , and incapability of label-free measur ements. Alternatively , Kuenzi et al. designed and
developed a magnetically actuated r otational microviscometer [
14
]. The generated viscous friction by
the fluid on the r otating magnet affected its r otation speed and angular position which were r ecorded
for viscosity measur ements. Although the system was able to pr ovide accurate results, its bulky size
limited its use for r eal-world POC systems [ 14 ].
Silicon-based technologies such as CMOS pr ovide countless advantages for POC and
Internet-of-Things (IoT) applications such as miniaturization, portability , high accuracy , reliability , low
cost, high noise immunity , low power consumption, and complete integration with Lab-On-a-Chip
(LOC) [
15
]. Due to these advantages, CMOS-based dielectric sensors have been used in numer ous
biological applications such as micr oorganism detection and characterization, neuronal activity
detection, dielectric spectr oscopy for medical diagnosis, and disease detection [
16
–
18
]. The developed
biosensors detect and characterize biological tar gets based on their intrinsic properties or biochemical
r eactions. These biological parameters include biomarkers, biomolecules, proteins, DNA, pathogenic
or ganisms, hormones, medical analytes such as glucose, and medical parameters like blood
pr essure [
17
,
18
]. For example, CMOS-based electr ochemical sensors have been designed and
developed for DNA detection and characterization [
19
–
21
]. In these works, Interdigitated Capacitors
(IDC) wer e used to determine the biochemical properties of DNA molecules. An IDC sensor is
a parallel-plate capacitor whose electr odes are positioned horizontally to pr ovide a single sided
access to the Material-Under -T est (MUT). In other wor ds, the dielectric constant (relative permittivity)
of the MUT defines the capacity of the IDC [
22
]. IDC-based sensors have been used in various
studies to detect the dielectric constant of or ganic fluids as well as characterization of biological cell
suspensions [
23
,
24
]. It is noteworthy that the relative permittivity is a fr equency-dependent complex
number that r epresents the characteristics of a medium in an interaction with electr omagnetic fields.
The r eal part of the permittivity is known as the dielectric constant, which repr esents the amount of
ener gy absorbed by the material from an electr omagnetic field. For medical applications, measuring
the r eal part of the permittivity is useful for medium characterization like estimating the glucose
concentration or determining the ratios of specific mixtur es. On the other hand, the imaginary part of

Biosensors 2018 , 8 , 78 3 of 13
the permittivity r eflects the materials energy loss to an external electric field. For example, conductivity
of the material (which is the featur e used for detecting the ratio of dead sperms during semen analysis)
is corr elated to the energy loss [
25
]. Over recent decades, r esearchers have investigated the corr elation
between the dielectric pr operties of biological samples (e.g., blood) and specific diseases at micr owave
fr equencies [
26
]. It has been shown that biomolecules and biocells existing in analyzed biological
samples pr ovide differ ent dielectric characteristics for subjects with diseases compared to healthy
ones [
18
]. The same concept is applicable for sputum samples collected from patients diagnosed with
COPD, as pr eviously mentioned. At differ ent stages of COPD, the viscosity of the sputum varies due
to its hydration change. Since the dielectric constant (permittivity) of the sputum is correlated to its
hydration, it is possible to characterize the viscosity of the sputum by measuring its dielectric constant.
In spite of the afor ementioned advancements in developing biosensors for various POC
applications, a r eliable technology for early diagnosis and monitoring of COPD is still missing.
Considering the fact that the viscosity of the sputum sample collected fr om a COPD diagnosed
patient is a r eliable indicator of the disease pr esence, development of a portable viscometer capable
of pr oviding real-time measur ements with high accuracy and resolution is significantly important.
Ther efore, the objective of this work was to design and develop a CMOS-based dielectric sensor for
r eal-time viscosity characterization of controls such as ethanol, methanol, and isopr opanol. This work
was aimed to identify the shortcomings of our pr evious prototype and develop a newer generation
of the dielectric sensor with a proper packaging and impr oved accuracy [
27
,
28
]. Future integration
of this biosensor into a medical device can be used for early diagnosis of COPD through viscosity
characterization of sputum. The working principle of the intended sensor is based on the dielectric
measur ement of the MUT using capacitance sensors mounted on a CMOS platform. The capacitance
change of the sensor affects the fr ee oscillation fr equency of the LC r esonant tank which would
be used for the r eadout mechanism. The operating frequency of the sensor is chosen to be in the
range of 10–30 GHz, wher e the permittivity of water is considerably high compared to other existing
biomaterials in the sputum [
17
]. Due to the existing permittivity contrast in the mentioned frequency
range, a better Signal-to-Noise Ratio (SNR) is expected. In addition, a high frequency sensor has
generally a small-sized chip which significantly r educes the sample volume requir ements. Furthermore,
the mentioned fr equency range provides the most accurate r esults for dielectric sensing applications
considering the fact that the undesir ed parameter-dependent dispersion mechanism of the biological
cells, which exists in low-fr equency ranges, has negligible ef fects on the sensor functionality . On the
other hand, based on the single Debye’s relaxation mechanism, the dielectric permittivity of water
decr eases after 17 GHz making extremely high fr equency measurements inadequate for the intended
application [ 17 ].
2. Materials and Methods
2.1. First Generation of the Sensor
A first pr ototype of the CMOS-based dielectric sensor for the detection of viscosity changes in
sputum–mucin was pr esented previously [
27
,
28
]. The details of this prototype along with its modified
version ar e presented below .
2.1.1. Sensor Design and Operation Principle
A CMOS-based Radio Fr equency (RF) dielectric sensor for the characterization of the
sputum–mucin was designed and manufactured, as shown in Figur e 1 a. The sensor was fabricated
thr ough the standard 250 nm SiGe:C BiCMOS technology of IHP (IHP , Frankfurt/Oder, Germany)
and operated at a fr equency of 12 GHz. The working principle of the sensor was based on measuring
the dielectric constant of liquid samples in or der to characterize their viscosity . For this purpose,
planar IDC sensors wer e coupled with inductors forming an LC resonant tank for the CMOS oscillator ,
as shown in Figur e 1 b. The capacitance of the IDC varied based on the dielectric constant of the

Biosensors 2018 , 8 , 78 4 of 13
MUT , leading to a change in the oscillation fr equency . As a result, fr equency changes of the oscillator
indicated the viscosity variation of the MUT .
Although the developed sensor proved the practicality of the concept of viscosity characterization
using dielectric sensors, its susceptibility to Electr ostatic Discharges (ESD) made handling the system
pr oblematic. As a result, ESD-pr otection diodes (ESD9B, ON Semiconductor , CO, USA) and capacitors
(0603 X5R:EIA, Murata Manufacturing Co., Nagaokakyo, Japan) wer e mounted on the Printed Circuit
Boar d (PCB) in order to r educe the impact of ESD distortions on the sensor functionality , shown
in Figur e 2 a. In or der to increase the accuracy and sensitivity of the sensor , a new chip with a
lar ger sensing area coverage (with wider IDC elements) was designed, as demonstrated in Figur e 2 b.
The details of the cir cuit design is available in our previous work [ 27 – 29 ].
Figure 1.
(
a
) First generation of the dielectric sensor , (
b
) sensor chip showing IDCs and inductors
embedded in a CMOS oscillator [ 27 , 28 ].
Figure 2.
(
a
) ESD-protection elements mounted on the PCB, (
b
) modified chip with a larger sensing
area coverage.
2.1.2. Sensor Performance and Required Modifications
The sensor was initially calibrated using ethanol, methanol, acetone, and isopropanol with
known permittivity and viscosity values. Following sensor calibration, two sets of experiments were
performed to evaluate the sensor . First, two solution mixtures (glycer ol–water and glycerol–ethanol)
wer e characterized with varying water and ethanol contents in order to obtain dif ferent permittivity
and viscosity values. Second, the sensor performance was validated by characterizing the permittivity
of thr ee differ ent biological liquids including: human serum, human saliva, and sputum–mucin
clot. The sensor pr ovided an oscillation frequency change of 200 MHz for a change of 60% in the
sputum–mucin viscosity . The details of the assessment methods and its results ar e available in [
27
,
28
].
The first pr ototype of the sensor provided pr omising results and pr oved the feasibility of the
method for measuring the viscosity of biological samples using dielectric sensors. However , a few

Biosensors 2018 , 8 , 78 5 of 13
limitations associated with the system r estricted its use in real-world applications. These issues ar e
as follows:
1.
Even though the RF output of the first-generation sensor was useful for conducting pilot
experiments and evaluating the system during preliminary studies, its numer ous drawbacks
made it an unfavourable choice for out-of-the-lab applications. The main drawback of the RF
output was the necessity of having costly and bulky spectrum analyzers for the signal acquisition
which is an unr ealistic intention for the development of POC devices. In addition, the RF signal is
generally very sensitive to external distortions which causes a considerable amount of noise on
the sensor outcome.
2.
Due to the lack of an adequate packaging, the sensor was extr emely susceptible to ESD-caused
damages. As a consequence, handling the system during the wire bonding pr ocess, soldering of
PCB elements, and running experiments wer e significantly inefficient and complicated. Moreover ,
the spr eading of conductive liquids on the PCB surface, especially during the characterization of
biological samples containing water , caused the sensor to short-circuit. Hence, a proper packaging
for ESD pr otection and short-circuit pr evention of the system was requir ed.
3.
Considering the inhomogeneous natur e of biological liquids, including mucin and saliva, a series
of sensing elements wer e requir ed to increase the overall sensing ability of the system and impr ove
its r epeatability .
4.
Since the sensor measures the dielectric constant of a sample, electrical featur es of the sample
determine the sensor outcome rather than its mechanical features. For instance, incr easing the
concentration of ethanol in an ethanol–glycer ol mixture decr eases both the permittivity and the
viscosity of the mixtur e. Conversely , increasing the concentration of water in a water -glycerol
mixtur e increases the permittivity of the mixtur e while decreasing its viscosity . Thus, the measured
permittivity for a given viscous sample is dependent on the constituents of that sample. In other
wor ds, it is only the permittivity of the solution which is detected by the sensor rather than its
absolute viscosity values. This is due to the fact that there is no dir ect mathematical correlation
between the viscosity and any electrical quantity . Consequently , differ ent calibrations ar e requir ed
based on the intrinsic characteristics of the tested samples. This issue causes calibration complexity
and makes the viscosity detection of unknown samples impractical. Ther efore, a mor e reliable
calibration and validation method is necessary to impr ove sensor outcome. For this purpose, the
dir ect calibration of the sensor using a commercialized viscometer is r ecommended.
A second generation of the sensor pr ototype was designed and developed in order to addr ess
these shortcomings, as pr esented in the following section.
2.2. Second Generation of the Sensor
Functioning on the same sensing principle as the first prototype, a new version of the sensor for the
detection of dielectric constant changes due to viscosity variations of sputum–mucin was developed,
Figur e 3 . Capacitive elements were coupled with inductors to define the oscillation fr equency of the
r esonator component. In this design, the capacitive elements are a pair of micr ostrip open-stubs with
an electrical length below the quarter-wavelength of the sensor operation fr equency , as shown in
Figur e 3 a. The operation frequency of the sensor is in the range of 30 GHz, which r esults in a high
SNR [
17
]. Similar to the previous sensor, the 250 nm SiGe:C BiCMOS technology of IHP was used
to fabricate the sensor . The limitations of the first prototype wer e addressed in or der to impr ove the
sensor functionality .

Biosensors 2018 , 8 , 78 6 of 13
Figure 3.
(
a
) Sensor oscillator circuit [
30
], (
b
) second-generation chip with a quadruple-sensor
configuration, (
c
) integration of the DC readout cir cuit and the sensor on the CMOS platform [
31
],
( d ) test board of the second-generation dielectric sensor with DC inputs and outputs.
2.2.1. Sensor Design and Functionality
As shown in Figur e 3 b, the second generation of the sensor with a 9.2 mm
2
chip size was designed
and fabricated. The larger size of the chip, compar ed to previous generations, is due to two r easons:
quadruple-sensor design for the detection of inhomogeneous samples, Figur e 3 b—the full integration
of the complementary r eadout circuit and the sensor on the CMOS platform, Figur e 3 c.
Unequal dispersion of inhomogeneous fluids over the sensing area of the first generation of the
sensor led to poor r epeatability . In order to addr ess this issue, four analogous sensors wer e integrated
in a quadruple design to incr ease the sensing area in contact with MUT and to r educe sample dispersion
ef fects on the sensor measurements, as shown in Figure 3 b. Despite having four sensors, the chip
consumes 80 mW power which makes it an appr opriate technology for POC devices.
The r eadout mechanism for the new generation of the sensor was modified to eliminate noise
caused by the RF output. As demonstrated in Figure 3 c, a fr equency discriminator was implemented
into the sensor r eadout circuit to convert the RF information into a DC output. Subsequently , a power
detector was used to extract the output power . Therefor e, DC signals corresponding to the sensor
oscillation fr equency were generated as the system output. Figure 3 d illustrates the inputs and outputs
for all four sensors. T wo DC inputs of 2.5 V are r equired for the system power sour ce. On the other
hand, each sensor provides two DC outputs in a range of 0–1 V for the real and imaginary parts of
the measur ed permittivity , as shown in Figure 3 d. Further details regar ding the cir cuit design are
available in our pr evious work [
30
,
31
]. Using DC inputs and outputs, the amount of perturbation on
the system was diminished and the sensor performance was significantly impr oved. In addition, the
low power consumption of sensors and ease of handling DC signals made the integration of the whole
system into a compact portable device possible. The packaging process of the system is described in
the following section.

Biosensors 2018 , 8 , 78 7 of 13
2.2.2. System Packaging
Figur e 4 a illustrates the packaging of the sensor , which was fabricated using a 3D printer at IHP
(Keyence Agilista-3200W , Keyence Co., Osaka, Japan). A droplet r eservoir was consider ed on the
packaging design for holding liquid samples, as shown in Figur e 4 b. A medical grade biocompatible
and electr onics-friendly glue (Loctite M-21HP , Henkel AG & Company , KGaA, Dusseldorf, Germany)
was used to seal the dr oplet reservoir thor oughly , as shown in Figure 4 c. As a r esult, the short
cir cuit of the sensor due to the spreading of the conductive liquids on the chip surface was pr evented.
Additionally , the bond wires wer e covered by a non-conductive biocompatible glue (TNP0400, Kyocera
Corporation, Kyoto, Japan) to pr otect them during assembling the packaging and testing samples.
Figur e 4 d illustrates the remaining sensing ar ea for sample measurements after the gluing pr ocess.
The ESD damages caused by the dir ect contact of the operators’ hands with the test boar d during
conducting experiments wer e minimized using the developed packaging. Moreover , the packaging
simplified the cleaning pr ocess of the chip after conducting measurements, since using conductive
liquids such as water for cleaning the sensing ar ea was possible. Therefor e, the system has become
mor e user-friendly to handle and conduct experiments.
Figure 4.
(
a
) The sensor packaging, (
b
) droplet r eservoir , (
c
) sealing of the reservoir for pr evention of
liquids spreading, ( d ) r emaining sensing area after the sealing step.
2.2.3. Experimental Setup
Since the dielectric constant of materials is highly temperatur e dependent, all experiments for
the sensor calibration and assessments wer e performed in a lab with a sustained temperature of
21
◦
C, as shown in Figur e 5 . Considering the frequency dispersive behavior of materials, Debye-based
r elaxation equations were used to calculate the dielectric constants of the tested materials at 21
◦
C and
30 GHz operating fr equency of the sensor , as presented in T able 1 [ 32 – 35 ].

Biosensors 2018 , 8 , 78 8 of 13
T able 1. Dielectric constant of utilized materials at 30 GHz and 21 ◦ C [ 32 – 35 ].
Material Dielectric Constant
Air 1
Isopropanol 3.08
Ethanol 4.51
Methanol 8.2
Acetone 15.4
Figure 5. Measurement setup for the sensor calibration and validation experiments.
3. Results and Discussions
3.1. Calibration
The initial measur ements of the sensor with no MUT featur es the dielectric characteristics of the
surr ounding air . As a result, the dielectric constants of air , isopropanol, ethanol, and acetone were
used to calibrate the sensor for dielectric measur ements.
The quadratic r egression method was used on the obtained r esults to establish a relationship
between the sensor output and the dielectric constant of the corresponding material. As illustrated
in Figur e 6 , the calibration line was fitted based on the calculated coef ficients of the quadratic
r egression expr ession.

Biosensors 2018 , 8 , 78 9 of 13
Figure 6.
The fitted calibration line using the quadratic regr ession method. In the equation, V repr esents
the corresponding DC output of the sensor in volt and ε 0
r is the dielectric constant of the MUT .
3.2. Performance Assessment
Following sensor calibration, experiments wer e performed on methanol to evaluate the sensor
ef ficacy . As presented in T able 2 , the experiments were conducted in triplicate and the dielectric
constant of methanol was calculated using the calibration equation pr esented in Figure 6 . Based on the
obtained r esults, the following performance measures wer e calculated:
•
Accuracy: calculated as the differ ence between the actual and the measured value divided by the
actual value (r elative error). The total error of all thr ee sets of measur ements is reported.
•
Repeatability: presented as the maximum standar d deviation of the errors observed during thr ee
experiments.
•
Hyster esis: calculated as the differ ence between the sensor initial measurements befor e and after
performing an experiment. The highest value of all trials is reported.
•
Drift: the sensor output with no MUT was recor ded from the initiation of the system for a time
period of 10 minutes. Drift was calculated as the differ ence between the lowest and the highest
dielectric constant value measur ed during the first and last 10 seconds.
•
Noise: calculated as the differ ence between the lowest and the highest dielectric constant value
acquir ed in a 10 second data set with no MUT .
T able 2. Results of the sensor verification experiments for methanol dielectric constant.
Methanol Actual V alue Exp. 1 Exp. 2 Exp. 3
Dielectric Constant ( ε 0
r ) 8.2 8.82 8.14 8.65
The functionality of the sensor to detect viscosity variation was evaluated by the mixtur e
characterization method. Six mixtures of methanol-isopr opanol, ranging fr om 0% methanol to 100%
methanol (in volumes), were pr epared. The effective permittivity and viscosity values of the mixtur es at
the working fr equency of the sensor were calculated using mixtur e theories [
28
,
30
,
36
]. The theoretical
values of the mixtur e permittivity and viscosity are plotted in Figur e 7 . The sensor r esults of the
dielectric constant of the mixtur es were calculated based on the sensor calibration and illustrated
in Figur e 7 .
The r esults of the experimental evaluation are pr esented in T able 3 . The sensor is capable
of measuring the dielectric constant of the MUT with an accuracy of 4.17% and a r epeatability of
5.36%. Therefor e, the r esults of the second-generation sensor are mor e reliable compar ed to the first

Biosensors 2018 , 8 , 78 10 of 13
pr ototype. Furthermor e, a hysteresis value of 2 mV was observed to have a negligible ef fect on the
sensor measur ements.
T able 3. Results of the performance evaluation of the second generation of the dielectric sensor .
Accuracy Repeatability Hysteresis Drift Noise
ε 0
r /(mV) 4.17% 5.36% 0.014 (2 mV) 0.038 (5 mV) 0.006 (1 mV)
The issues r elated to the susceptibility of the RF signal to external distortions were addr essed
and a mor e stable system with DC readout mechanism was developed. Therefor e, the level of noise
existing in the system has been r emarkably reduced (1 mV) compar ed to the first-generation sensor .
In addition, the sensor shows a low amount of drift (5 mV) which results in a calibration consistency
during long term measur ements. The low drift and hysteresis characteristics of the sensor make it a
mor e reliable technology for r eal-world applications.
The short-cir cuiting issue of the sensor was addressed using the sensor packaging. The droplet
r eservoir of the packaging was thoroughly sealed in or der to prevent the spr eading of the conductive
samples on the boar d during experiments. Furthermore, the packaging pr evented the dir ect contact of
operators’ hands with the boar d for ESD-protection.
Quadruple design of the chip impr oved the overall sensing ability of the system and therefor e,
mor e repeatable and consistent r esults were achieved. Further investigation to evaluate the sensor
performance during the characterization of inhomogeneous fluids is r equired.
Figur e 7 shows the variation of the viscosity and dielectric constant of the isopr opanol-methanol
mixtur e with respect to the concentration of methanol. It is shown that with the addition of methanol,
the viscosity of the r esultant mixture decr eases due to the low viscosity of methanol. Conversely ,
the permittivity of the solution incr eases considering the high permittivity of methanol. As a result,
the sensor is able to detect the viscosity variation of the solution based on its permittivity changes.
However , it should be noted that it is r equired to know the dielectric characteristics of the mixtur e’s
constituents to be able to detect its viscosity variation. Estimation of absolute viscosity values using a
dielectric sensor is not feasible since ther e is no direct mathematical corr elation between viscosity and
an electrical quantity .
Figure 7.
V iscosity and permittivity variation of the isopropanol-methanol mixtur e with respect to
methanol content.

Biosensors 2018 , 8 , 78 11 of 13
Although capabilities of the system wer e evaluated through the characterization of contr ol
liquids with known dielectric constant values, a dir ect viscosity calibration and validation method is
still missing. Our team is currently investigating this appr oach using a commercialized viscometer
(m-VROC, RheoSense Inc., San Ramon, CA, USA) to corr elate the absolute viscosity values of saliva
and sputum samples to the sensor r esults. However , the complexity of viscosity measur ements of
non-Newtonian fluids make it a challenging appr oach. These investigations are still ongoing.
The second generation of the sensor was able to addr ess the limitations of the previous design.
The drawbacks r elated to the RF output of the sensor were addr essed and a portable low-cost
system with a high accuracy and r epeatability was developed. The 3D printed packaging of the
sensor pr evented the damages previously caused by short-cir cuiting and ESD. The designed sensor
consisted of four symmetrical sensing elements to eliminate the effects of local concentration of
particles in inhomogeneous liquids on the sensor measurements. The calibration issue of the viscosity
measur ements caused by the indirect verification of sensor r esults is still under investigation.
4. Conclusions and Future W ork
In this work, the concept of viscosity measurement of sputum samples for the early diagnosis
of COPD using a dielectric sensor was investigated. T wo pr ototypes of the dielectric sensors were
designed and fabricated using the CMOS technology . The sensors measur ed the permittivity variation
of the MUT which was corr elated to their viscosity changes. The limitations of the first prototype wer e
identified and addr essed and a newer version of the sensor was developed. The sensor performance for
detecting the viscosity of liquids was evaluated using contr ols and through the mixtur e characterization
method. The sensor assessment results show that the RF sensor is capable of measuring the dielectric
constant of liquids with an accuracy and a r epeatability of 4.17% and 5.36%, respectively . Moreover ,
low amounts of noise and drift were observed during measur ements, providing r eliable r esults for
long-term medical applications. In addition, the packaging of the sensor simplified the system handling
during operation. The DC r eadout mechanism of the second prototype as well as its compact size
and low power consumption made it a suitable technology for POC applications. Ease of cleaning,
portability , low cost, and capability of rapid detection of viscosity are among the main novelties of this
biosensor for clinical applications.
As a next step, the sensor will be calibrated using a commer cialized viscometer and its
performance will be evaluated during the characterization of non-Newtonian fluids. Considering
the practical application of this sensor , providing absolute viscosity values is necessary for COPD
diagnostics. In addition, the developed sensor will be incorporated into a complete hand-held device
suitable for POC and IoT applications.
Author Contributions:
Conceptualization—P .S.Z, D.K., J.W ., and F .I.J.; Methodology—C.W ., S.G., F .I.J., and
P .S.Z; V alidation—P .S.Z. and F .I.J; Formal analysis—P .S.Z., F .I.J., and C.W .; Investigation—P .S.Z., S.G., and F .I.J;
Resources—D.K. and C.W .; W riting and preparation of the original paper draft—P .S.Z.; Review and editing– S.G.,
F .I.J., and C.W .; Supervision—C.W .; Funding acquisition—C.W .
Funding:
This resear ch was funded by the Federal Ministry for Education and Resear ch (BMBF) of Germany
under grant number [13U13862] for the EXASENS project.
Acknowledgments:
The authors thank the technology department of IHP for the fabrication of the chips.
The authors would also like to thank the staf f at IHP for their support and help with the development of the
system, especially Frank Popiela and Janett W itthaus for preparing the PCBs and Rita W inkler for the fabrication
of the packaging.
Conflicts of Interest: The authors declare no conflict of inter est.
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