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Design, fabrication, and feasibility analysis of a colorimetric detection system with a smartphone for self-monitoring blood glucose


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Maintaining appropriate insulin levels is very important for diabetes patients. Effective monitoring of blood glucose can aid in maintaining the body's insulin level, and thus reduce disease severities, secondary complications, and related mortalities. However, existing blood glucose measurement devices are inconvenient to carry and involve complex procedures, reducing the willingness of diabetes patients to regularly measure blood glucose. We aim to provide a rapid, convenient, and portable meter for diabetes patients. We introduce an integrated blood glucose detection device (IBGDD) that has no electronic component and uses the optical sensing module of a smartphone to inspect colorimetric blood strips. To demonstrate accuracy conformance of the developed device to the ISO 15197:2013 standard for blood glucose measurement, 20 diabetes mellitus patients used the IBGDD with smartphones to measure their blood glucose level. The measurement results revealed an accuracy of 100%, completely satisfying the requirements of the ISO 15197:2013 standard. Overall, our specially designed IBGDD with a smartphone could achieve high accuracy and convenient usage for the measurement of blood glucose concentration. Furthermore, the device is highly portable and simple to operate. This contributes toward achieving self-monitoring of blood glucose by diabetes patients and improved mobile health in the future.
Content may be subject to copyright.
Design, fabrication, and feasibility
analysis of a colorimetric detection
system with a smartphone for self-
monitoring blood glucose
Hung-Chih Wang
Fuh-Yu Chang
Tung-Meng Tsai
Chieh-Hsiao Chen
Yen-Yu Chen
Hung-Chih Wang, Fuh-Yu Chang, Tung-Meng Tsai, Chieh-Hsiao Chen, Yen-Yu Chen, Design, fabrication,
and feasibility analysis of a colorimetric detection system with a smartphone for self-monitoring
blood glucose,J. Biomed. Opt. 24(2), 027002 (2019), doi: 10.1117/1.JBO.24.2.027002.
Downloaded From: on 02 Oct 2019
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Design, fabrication, and feasibility analysis of
a colorimetric detection system with a smartphone
for self-monitoring blood glucose
Hung-Chih Wang,aFuh-Yu Chang,a,*Tung-Meng Tsai,bChieh-Hsiao Chen,b,c and Yen-Yu Chenb
aNational Taiwan University of Science and Technology, Department of Mechanical Engineering Taipei, Taiwan
biXensor Co. Ltd., Taipei, Taiwan
cChina Medical University and Beigang Hospital, Taichung, Taiwan
Abstract. Maintaining appropriate insulin levels is very important for diabetes patients. Effective monitoring of
blood glucose can aid in maintaining the bodys insulin level, and thus reduce disease severities, secondary
complications, and related mortalities. However, existing blood glucose measurement devices are inconvenient
to carry and involve complex procedures, reducing the willingness of diabetes patients to regularly measure
blood glucose. We aim to provide a rapid, convenient, and portable meter for diabetes patients. We introduce
an integrated blood glucose detection device (IBGDD) that has no electronic component and uses the optical
sensing module of a smartphone to inspect colorimetric blood strips. To demonstrate accuracy conformance of
the developed device to the ISO 15197:2013 standard for blood glucose measurement, 20 diabetes mellitus
patients used the IBGDD with smartphones to measure their blood glucose level. The measurement results
revealed an accuracy of 100%, completely satisfying the requirements of the ISO 15197:2013 standard.
Overall, our specially designed IBGDD with a smartphone could achieve high accuracy and convenient
usage for the measurement of blood glucose concentration. Furthermore, the device is highly portable and
simple to operate. This contributes toward achieving self-monitoring of blood glucose by diabetes patients and
improved mobile health in the future. ©The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.
Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. [DOI: 10.1117/1.JBO.24.2
Keywords: blood glucose; colorimetric blood strip; diabetes; smartphone.
Paper 180557R received Sep. 30, 2018; accepted for publication Jan. 22, 2019; published online Feb. 21, 2019.
1 Introduction
Rapid development of the economy and subsequent changes in
lifestyle have led to the prevalence of diabetes, affecting over
382 million people in 2013. This number is expected to rise
to 592 million by 2035, which will impose a large and increas-
ing global health burden.1Some studies pointed out that
frequent monitoring of blood glucose changes and effective con-
trol of blood glucose levels can help reduce the incidence of
diabetic complications.28However, current devices for blood
glucose monitoring are inconvenient to carry or their testing pro-
cedures are complicated. Therefore, the willingness of patients
to detect blood glucose frequently is reduced. This could
seriously impact the health of diabetic patients with high blood
glucose levels.
In general, glucose oxidase (GOx), glucose dehydrogenase
(GDH), and hexokinase are used in existing glucose measure-
ment techniques, which are based on the principles of enzymatic
reactions.9Each enzyme has characteristic advantages and
limitations, including redox potentials, cofactors, turnover
rates, and selectivity for glucose.10 Glucose biosensors for self-
monitoring of blood glucose (SMBG) are usually based on the
two enzyme families, GOx and GDH. GOx is the standard
enzyme for biosensors. It is easy to obtain, cheap, can withstand
greater extremes of pH, ionic strength, and temperature, and
has a relatively higher selectivity for glucose than many other
enzymes. Thus, the manufacture of GOx involves less stringent
conditions than other enzymes.10,11 The majority of current
glucose biosensors are of the electrochemical type because of
their higher sensitivity, reproducibility, and easy maintenance.
Electrochemical sensors may be divided into potentiometric,
amperometric, or conductometric types.1214 However, electro-
chemical sensors have two disadvantages: one is interferences
with nonspecific electroactive particles and the other is compli-
cations related to signal conversion.15,16
In the colorimetric method for SMBG, blood glucose test
strips with special enzymes are used to produce chemical
reactions with blood glucose, and changes in the glucose con-
centration are monitored by evaluating changes in the color of
the strips. The conventional colorimetric method employs visual
comparison to determine the value of blood glucose. Although
this method has the advantages of low cost without an additional
blood glucose meter, it has a serious drawback of low accuracy,
especially due to differences in the personal visual evaluation.
To overcome this issue, many researchers are currently attempt-
ing to apply image analysis software and hardware, such as
a computer with a scanner or camera, to analyze the color
value of blood glucose strips.17,18 These works provide a
means to improve the accuracy of detection, but the significant
and outstanding disadvantages lie in that they require additional
and unportable hardware and complex operation with nonuser-
friendly steps. To simplify the complex operation, smartphones
have been used in several studies to detect the concentration
*Address all correspondence to Fuh-Yu Chang, E-mail: fychang@mail.ntust
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of whole blood glucose.1922 However, in these experiments, the
measurement of the concentration of blood glucose was time
consuming. Therefore, the development of a portable device
with simple procedure is of high significance for regular SMBG.
In this study, a convenient and portable colorimetric SMBG
system is introduced. The system combines a designed inte-
grated blood glucose detection device (IBGDD) with an auto-
matic glucose concentration analysis software installed in a
smartphone. The IBGDD consists of a blood glucose test site
(BGTS), a disposable lancet, a cover and baseplate set, and a
light guide channel. The IBGDD is designed to have a minimum
feature size and can be connected to the smartphone easily. In
addition, the IBGDD does not have any electronic component
and does not require any extra-light source during the detection
of blood glucose concentration. Light from the smartphones
liquid crystal display (LCD) is reflected and guided to the
detection area, as the required light source for capturing and
analyzing color changes of blood glucose test strips. An optical
simulation is performed to guide the light channel for achieving
proper illuminance and uniform illumination on the BGTS. The
smartphones camera is used to capture the image of the strip,
and then the software installed in the smartphone analyzes the
image and provides accurate values of blood glucose concentra-
tion. For developing the automatic glucose concentration analy-
sis software, whole blood samples with 10 different blood
glucose concentrations, from 50 to 500 mg/dL, were collected
and a normalized algorithm and a line process were applied to
establish reference mainlines for calculating the blood glucose
concentration values. Finally, blood samples were collected
from 20 diabetes mellitus patients and measured for blood glu-
cose using the developed SMBG system with smartphone and
a standard biochemical blood glucose analyzer. The measured
results were compared and analyzed to confirm the accuracy and
stability of the proposed SMBG system.
2 Design and Simulation
2.1 IBGDD Design
The major components of the IBGDD are the BGTS, a cover and
baseplate set, a disposable lancet, and a light guide channel, as
shown in Fig. 1. In our study, the smartphones LCD was used
as the light source to capture the BGTS image. In order to guide
the light to the BGTS area efficiently, after the IBGDD 3-D
model was built using the computer-aided design software,
an optical simulation using Tracepro (Lambda Research
Corporation) was performed to find the optimal design for
the IBGDD, especially the reflectors angle.
2.1.1 Blood glucose test site
The main function of the BGTS is to observe changes in
the color of test strip and measure the concentration of blood
glucose. It is divided into two components: a test strip and
a substrate. The substrate has a 2-mm hole, through which
changes in the color of test strip after reaction can be observed.
The diameter of the test strip is 2.5 mm and it is placed on the
substrate with the same center as the through hole. To effectively
observe and evaluate the color change in the observation area,
optical simulation was performed in this study to determine the
final design of the IBGDD with the optimal illuminance and
illumination uniformity of the BGTS.
2.1.2 Cover and baseplate set
The main functions of the cover and baseplate are to lead the
blood to the BGTS and block the ambient light source,
which affects the image signal of BGTS. A black-colored blood
guide hole made of hydrophilic acrylic plastic was designed on
the cover. The hydrophilic property can effectively assist to lead
the blood to the BGTS, and the black feature can completely
isolate the ambient light.
2.1.3 Light guide channel
Because the direction of LCD light emission is parallel to the
vertical direction of the BGTS, a light guide channel is required
to redirect the light on the BGTS. According to the law of
the light reflection theory, a reflect angle (RA) structure was
designed in the guide light channel. This RA has an important
effect on the brightness and illumination uniformity of the
BGTS. The simulation experiment was aimed at determining
an optimal RA of the light-guiding channel.
Fig. 1 Smartphone and IBGDD, comprising the BGTS, cover, baseplate, light guide channel, and
disposable lancet. The red arrows indicate the light path in the IBGDD.
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2.1.4 Disposable lancet
The disposable lancet is mostly used to obtain blood from the
fingers because it is currently the safest and easiest method. In
this study, a special and small disposable lancet was designed
such that it can work with our IBGDD and is convenient for
users to carry. The lancet functions according to a spring mecha-
nism, and the total size is only 6 mm in diameter and 37.9 mm in
length. When the lancet is pushed against a finger, a hidden
needle rapidly and gently pierces the finger. Then, the blood
flows from the finger around the fingertip, and it is absorbed
by the BGTS through capillary action when the finger touches
the blood guide hole on the cover.
2.2 Simulation and Measurement Method for
Achieving Uniform Illumination of
the BGTS Area
The light source plays an important role in image analysis. To
find an optimized RA that can guide light into the BGTS area, in
this simulation experiment, the RA of the light guide channel
was set from 30 deg to 70 deg with 5 deg intervals as the analysis
conditions. In this manner, the most optimal angle for the best
illuminance and illumination uniformity on the observation area
of the BGTS could be determined. The actual illumination of
the smartphones LCD was measured to be the light source
illuminance value in the simulation. First, the screen was set to
be white, and the screen brightness was raised to the maximum,
and then a T10 illuminance meter (Konica Minolta, Japan) was
used to measure the actual illumination of the screen. The
average illumination is 230 lux. According to this measurement,
the light source area was set to be 7.5 mm ×6.3 mm in the
simulation. The light wavelength was set by the general colori-
metric method, in which the 550- nm wavelength is the most
commonly used. The number of simulated traces was set to
be 3 million.
The nine-point uniformity method was used to analyze the
method of achieving uniform illumination in this study. The
BGTS observation area was divided into nine symmetrical sam-
pling areas, P1 to P9, as shown in Fig. 2. The sampling square
size was 0.4 mm ×0.4 mm. The nine-area uniformity is defined
by the minimum illuminance measured at the nine sampling
areas divided by the maximum illuminance measured at the
nine sampling squares, as
where Uis the BGTS uniformity.
2.3 Simulation Result
Our analysis of the simulation result indicates that the angle of
reflection of the light guide channel has a significant effect on
the illuminance and illumination uniformity of the BGTS obser-
vation area. At an angle of 30 deg, the illuminance and illumi-
nation uniformity are 50.43 lux and 90.43%, respectively. When
the angle increases, both illuminance and illumination uniform-
ity continuously increase. At 50 deg, the illuminance and illu-
mination uniformity reach the highest values of 53.67 lux and
95.47%, respectively. With continued increase in the reflection
angle, the illumination uniformity begins to decline. When the
Fig. 2 Illuminance analysis of the BGTS area using the optical simulation program TracePro, with the
BGTS area divided into nine symmetrical squares with sizes of 0.4mm ×0.4mm.
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angle increases to 70 deg, the illumination uniformity declines
to 90.68%, as shown in Fig. 3. It is concluded that when the RA
of the light guide channel is too low, it cannot effectively reflect
the light to the BGTS, and therefore both illuminance and illu-
mination uniformity are low. However, when the angle is higher
than 50 deg, the light intensity gradually decreases toward the
BGTS observation area, and therefore the illumination and illu-
minance uniformity of the observed area will decline. According
to the simulation, the final design of RA of light guide channel
was selected to be 50 deg to achieve the optimal illuminance and
illumination uniformity.
3 Experiment
3.1 Fabrication and Integration of the IBGDD
All IBGDD components were fabricated by plastic injection
molding, because the process allows components with consis-
tent characteristics at reasonable production cost. After fabrica-
tion, all components were cleaned by ultrasonic cleaning and
then assembled together. The mold of the reflector channel in
the reflective area was polished, which can ensure a mirror-like
surface roughness and enhance the light reflection efficiency of
the reflector.
In this experiment, generally marketed products of colori-
metric blood glucose strip were selected as the BGTS material,
which had concentrations ranging from 40 to 500 mg/dL. Since
general strip dimension cannot meet IBGDD size a knife tool
was used to cut the strip to the size 7.5 mm ×6.3 mm.
3.2 Verification of the Illuminance and Illumination
Uniformity of the BGTS Area
The illuminance measuring instrument used is Konica Minolta
T10 illuminance meter. In order to verify the basic illuminance
and illumination uniformity, a standard card of 4 mm diameter
was used. The standard card has Pantone White and completely
uniform color characteristics. After inserting the standard card
into the IBGDD, the glucose measurement program was started
and the smartphones LCD was switched on and guided to the
BGTS area by the light guide channel, after which white balance
locking and ISO value adjustment were performed. The program
divided the BGTS area image into nine symmetrical sampling
areas of square frame with four pixels each, and red, green, and
blue (RGB) data from each rectangle image were collected to
measure the minimum and maximum values. The measured
data with the standard card were used to adjust the glucose
measurement program for setting the basic illuminance and illu-
mination uniformity. This operation was repeated five times to
ensure the repeatability of the measurement.
3.3 Preparation of Blood Glucose Samples with
Different Concentrations
In this experiment, a Yellow Springs Instrument (YSI) bio-
chemical blood glucose analyzer equipment (YSI-2300) was
used to establish the different concentrations of blood glucose
from the collected whole blood samples.
Sterile heparin tubes were used to collect 120 c.c. venous
blood samples from each patient at environmental temperature
of 22°C. After 24 h of standing, the blood glucose of
the samples degraded to 0 mg/dL, and then proper amounts of
glucose solutions were added to the samples without blood
glucose according to the required blood glucose concentration.
After complete mixing with a rotor equipment, the YSI-2300
blood glucose meter was used to measure the blood glucose
3.4 Colorimetric Enzyme Reaction Analysis and
Establishing the Signal Reference Mainline
The color of the colorimetric enzyme strip after reaction may
vary with different blood glucose concentrations and reaction
time. The first target of this experiment was to determine the
signal of RGB specific and sensitive to the colorimetric enzyme
strip and the time required to clearly distinguish the blood glu-
cose concentration value of the samples. To avoid variations of
blood glucose concentration caused by differences in tempera-
ture, the environmental temperature was set to 22°C. After
inserting the strip into the IBGDD, the glucose measurement
program was started and the image of the BGTS area was cap-
tured by the smartphones front camera (iPhone 5s, Apple Inc.)
and the digital image of color change was separated into R, G,
and B signals using the ColorAssist (FTLapps, Inc.) app
according to the blood glucose concentration and reaction time.
The concentration was adjusted from 50 to 500 mg/dL with an
Fig. 3 Simulation results of illuminance and illuminance uniformity.
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interval of 50 mg/dL. The experiment was repeated three times
for each of the 10 different blood samples. Subsequently, the
normalized algorithm was applied to obtain 10 different concen-
tration curves of RGB signals, which could assist in determining
the signal most suitable for the colorimetric strip, and the deter-
mined signal was used to establish linear equations with the
parametric regression analysis method. Normalization was per-
formed by dividing the reaction signal value by the unreacted
signal. Given that the normalized signal values for each concen-
tration were too low so as to easily distinguish them, the range of
the normalized signal values for each concentration was rescaled
up to 400 times. Finally, the linear equations were used as the
signal reference mainline to convert the imaged strip colors to
the blood glucose concentration values.
3.5 Verification Plan for the Developed SMBG
In 2013, ISO published a new standard ISO 15197:2013 and
tightened the accuracy acceptance criteria.23 The standard stip-
ulates that to satisfy the minimum acceptable accuracy for a glu-
cose monitoring system, 95% of measurement results must fall
within 15 mgdL of the reference measured glucose concen-
tration < 100 mgdL or within 15% of the reference measured
glucose concentration 100 mgdL. To verify the accuracy of
the new SMBG system within the criteria of ISO 15197:2013,
a verification test was performed with venous blood from
20 diabetic patients. The diabetic patients in this verification
plan covered diabetes types 1 and 2. The collected venous blood
specimens were measured not only by the SMBG system but
also by the YSI-2300 analyzer for accuracy comparison.
4 Results and Discussion
4.1 Illuminance and Illuminance Uniformity of
the BGTS Area
The T10 illuminance meter was used to measure the illuminance
of the BGTS area and the average illuminance was 54.6 lux from
five times of measurement. The nine-point uniformity method
was used to measure and analyze the RGB signals with the stan-
dard card in the BGTS area. The measured uniformity values for
RGB signals from five times of measurement were all higher
than 94.5%. The values of G signal uniformity were signifi-
cantly higher than those of the R and B signals, with an average
value of 97.4%. The coefficient of variation (Cv) value of
the RGB signals, ratio of the standard deviation to the mean
value, was lower than 0.82%. The Cv of the G signal reached
as low as 0.27%. This indicates that the designed reflector angle
and reflection channel can provide uniform and stable light to
the BGTS area. Uniformity and illuminance stability of the light
source are extremely important factors affecting the accuracy
and stability of the subsequent blood glucose measurement.
The measured illuminance and uniformity were also com-
pared with the simulation results, and the comparison results
proved the reliability of the simulation model. The simulation
model will be used to improve the SMBG design in the future.
4.2 Selection of the RGB Signal and Reference
The developed SMBG system was applied to record the RGB
signal values every 0.2 s for 50 s, and each concentration sample
was measured three times. The normalized algorithm was
applied and 10 different concentration curves of RGB were
obtained, as shown in Fig. 4. The figures show that the normal-
ized curve of the R signal cannot be distinguished when the
concentration is over 300 mg/dL [Fig. 4(a)], and the normalized
curve of the B signal requires more than 30 s to distinguish
each concentration curve [Fig. 4(b)]. In contrast, the 10 different
concentration curves of the G signal could be distinguished
completely after 10 s, as shown in Fig. 4(b). Therefore, the
normalized curves of the G signal were selected to establish
the signal reference mainline, and normalized curve values of
each concentration at 10 s were collected. Subsequently, the
parametric regression analysis method was used to obtain
a linear equation y¼0.3247xþ219.25, and the coefficient
of determination R2was higher than 0.98, as shown in
Fig. 5. The linear equation was used as the reference mainline
to convert the imaged strip colors to the blood glucose
Fig. 4 Normalized curve from the measurement of 10 different con-
centration blood samples over 50 s. Each curve represents the aver-
age of three measurements. (a) The R signal cannot be distinguished
when the concentration reaches over 300 mg/dL. (b) The 10 different
concentration curves of the G signal can be clearly separated after
10 s. (c) More than 30 s is required to distinguish the concentration
curves of the B signal.
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4.3 Accuracy and Stability Tests for the Signal
Reference Mainline
To verify the accuracy and stability of the signal reference main-
line, six different blood samples with glucose concentrations
adjusted at 50, 100, 200, 300, 400, and 500 mg/dL were tested
and each sample was measured 10 times. The mean values of the
samples from 10 times of measurement with the developed
SMBG system were 49.0, 99.0, 198.3, 292.6, 397.0, and
488.7 md/dL, respectively; their standard deviations were 1.2,
2.9, 5.0, 9.6, 13.1, and 15.4, respectively; and their Cv values
were 2.4%, 2.9%, 2.5%, 3.3%, 3.3%, and 3.1%, respectively.
Compared with the adjusted glucose concentration of the sam-
ples, the accuracy of the measurements with the developed
SMBG system was found to be 97.4%, 95.9%, 95.7%,
98.3%, 97.4%, and 95.8%, respectively. As the experimental
results show accuracy values over 95% for all tested samples
and all Cv values under 3.8%, the developed SMBG system
with the established signal reference mainlines meet the stan-
dard criteria and clinical trial requirement for measuring blood
glucose concentration with high accuracy and stability. The
seven samples were also measured by the YSI-2300 analyzer
for comparison. The concentration values were 50.4, 103.3,
207.3, 297.6, 407.8, and 510.2 mg/dL, respectively. Comparing
these values, the developed system may measure the blood
glucose concentration with the same level of accuracy and
stability as the gold standard equipment.
4.4 Verification Result for the Developed SMBG
In the verification with venous blood collected from 20 diabetes
patients, 4 were diabetes type 1 patients and 16 were diabetes
type 2 patients. The age distribution is as follows: 5% under
the age of 20, 15% between 21 and 30, 20% between 31 and
40, 25% between 51 and 60, 10% between 61 and 70, and
5% over the age of 71. According to the analysis of data from
the 20 patients, measurement results of the developed SMBG
system and YSI-2300 analyzer were compared, and the data
were found to completely satisfy the 15 mgdL or 15%
criteria, as shown in Fig. 5. The accuracy acceptance percentage
is 100% and meets the ISO 15197:2013 (E) criteria successfully.
The parametric regression analysis of the data revealed a
coefficient of determination (R2) value of 0.9848, as shown
in Fig. 6(b). These analyses show that the developed system
measured the blood glucose concentration with the same
level of accuracy and stability as the gold standard equipment.
The design of the experiment and human subject involvement
were approved by China Medical University Hospital.
5 Conclusions
In this study, a convenient and portable self-monitoring blood
glucose system, comprising a special IBGDD and a smartphone,
was developed and tested. As no additional light source and
electronic part are required in the IBGDD, the device is as
small as a pen cap or a key chain. An optical simulation was
performed to optimize the design of the IBGDD in order to
guide the light from the smartphones LCD to the colorimetric
strip efficiently. The smartphones camera was used to capture
the image of the colorimetric strip, and then the developed
blood glucose concentration analysis program, installed in the
smartphone, was used to obtain the measured value of blood
glucose concentration. To confirm the accuracy and stability
of the developed system, data from blood samples of 20 diabetes
patients were used to measure their blood glucose and the
results were compared with measured data from a commercial
YSI-2300 blood glucose analyzer. The analysis results showed
that all measured data were within the 15 mgdL or 15%
Fig. 6 ISO 15197:2013 and parametric regression analysis results. (a) Comparison of the measured
data from the developed SMBG system and the YSI-2300 analyzer for 20 samples. The plot also
gives the superimposed tolerance bands according to the ISO 15197:2013 criteria for accuracy.
(b) Parametric regression analysis plot comparing results for the SMBG and YSI-2300 analyzer.
Fig. 5 Signal reference mainline obtained based on the normalized
value of the G signal with the parametric regression analysis method.
Glucose concentrations of 50 500 mgdL were recorded with the
IBGDD and G signal and the results were read with a smartphone.
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criteria. The accuracy acceptance percentage was 100%. The
results prove that the developed system can completely meet
the requirements of the ISO 15197:2013 standard for blood
glucose measurement.
In the next phase plan, a clinical trial will be conducted with a
hospital. It will enroll 120 subjects (type 1 and type 2 diabetes
patients). These subjects will use the IBGDD with smartphones
to measure their blood glucose levels. The measured data will be
compared with those of the YSI-2300 analyzer to verify whether
the clinical trial results meet the ISO 15197:2013 accuracy
In the future, our goal is to design a personal health manage-
ment system that combines glycosylated hemoglobin (HbA1C),
cholesterol, triglyceride, and blood glucose data. The personal
health system data will be used to analyze physiological infor-
mation, which will be sent to the cloud system of medical insti-
tutions via the internet. In this manner, concerned physicians can
quickly grasp and judge the health information and transmit the
related medical information to the patient. Through this
personal health management system, patients can effectively
employ digital technology to achieve physical health.
T. M. Tsai, C. H. Chen, and Y. Y. Chen are cofounders of
iXensor Co., Ltd., and H. C. Wang was an employee of
iXensor Co., Ltd. F. Y. Chang has no relevant conflict of inter-
ests to declare.
This research was supported by iXensor Co., Ltd., and approved
by IRB of China Medical University Hospital (CMUH102-
REC2-050). Ministry of Science and Technology, Taiwan,
Republic of China under Grant MOST 106-2221-E-011-
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Hung-Chih Wang is a PhD candidate at the National Taiwan
University Science and Technology, Taiwan. He received his BS
and MS degrees in mechanical engineering from the National
Taiwan University Science and Technology, Taiwan. He is experi-
enced in mechanical product design, optical and biomedical device
development for over 20 years.
Fuh-Yu Chang received his PhD in mechanical engineering, Leeds
University, United Kingdom. Currently, he is working as an associate
professor in the Mechanical Engineering Department of National
Taiwan University Science and Technology, Taiwan. He has over
10 years of experience in biomedical device development. He is
also interested in the semiconductor industry, electronics, and related
optical design.
Tung-Meng Tsai received his PhD in chemistry engineering from the
National Chung Hsing University, Taiwan. Currently, he is working in
iXensor as chief executive officer and cofounder. He has more than
20 years of experience in biomedical device development.
Chieh-Hsiao Chen received his MD degree from KMU and PhD in
biomedical engineering from NCKU, Taiwan. He specializes in
nanotechnologies for cancer treatment, biosignal processing, and
entrepreneurship. He works at iXensor as chief medical officer
and cofounder. He also participates in clinical strategy, algorithms,
and user experiences. He teaches biodesign and entrepreneurship
at CMU, KMU, and NCKU. He is also the director of urology at
CMUH, Beigang, and CEO of Brain Navi Ltd.
Yen-Yu Chen received his PhD in electrical engineering from
National Taiwan University, Taiwan. Afterward, he worked as a visit-
ing researcher at Massachusetts Institute of Technology, California
Institute of Technology, and Stanford University, to develop advanced
optical imaging systems for biomedical research. He is now the CTO
of iXensor and leads the companys technology and strategy develop-
ment. His fields of interest include medical devices, optical instru-
ments, and digital health.
Journal of Biomedical Optics 027002-7 February 2019 Vol. 24(2)
Wang et al.: Design, fabrication, and feasibility analysis of a colorimetric detection system with a smartphone for self-monitoring blood glucose
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... The number of simulated traces was set to be 3 million. In a previous study, the nine-point uniformity method was used to analyze and achieve optimized illuminance and illumination uniformity on the CTS area [29]. ...
... The normalized algorithm was applied and 10 different concentration curves of RGB were obtained. In this experiment, G signal was selected as a reference mainline as it can clearly identify different concentration of the blood glucose value of the sample after 10 seconds [29]. Subsequently, the parametric regression analysis method was used to obtain three linear equations of the three lots. ...
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Blood glucose measurements help to guide insulin therapy, thus reducing disease severities, secondary complications, and related mortalities. Efforts are underway to allow diabetes patients to experience a more convenient way to measure blood glucose and consequently increase their adherence to regular self-monitoring of blood glucose (SMBG). This study demonstrated a new SMBG system that integrated all components of a glucometer via a smartphone’s optical sensing module to detect the colorimetric blood strip and obtains the blood glucose concentration with calculations performed by an application install in the smartphone. To validate the accuracy and applicability of the new SMBG system regarding the ISO15197:2013 accuracy criteria and patient requirements, a clinical trial and usability survey involving participants from different age groups were conducted in collaboration with the China Medical University, where enrolled 120 diabetic patients were asked to operate the new SMBG system to measure their blood glucose concentration, and feedback was obtained from their user experience. The results showed that three different reagent system lots fulfilled the accuracy requirements with values of 97.4–97.5% , and all of the data were within zones A and B of the consensus error grid, which satisfies the ISO 15197:2013 requirement. The usability survey showed that 97.5% of the participants found the operations convenient, and 100% found the design easy for carrying. This new system could lead to improvements in blood glucose monitoring by people with diabetes, and thus, better management of the disease.
... Data acquired via smartphone may be automatically directed to a health care team for further discussions and medical decisions. Such technology can be extended to blood sugar measurements for diabetes patients, and other information related to cholesterol, fats, and hemoglobin (92). Video technology could be on the cusp of a future where a patient's home is transformed into a "smartphone-based doctor's office" where numerous cardiovascular or blood-related metrics are assessed that would previously require expertise and communication across multiple health divisions. ...
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Regular blood pressure (BP) monitoring enables earlier detection of hypertension and reduces cardiovascular disease. Cuff-based BP measurements require equipment that is inconvenient for some individuals and deters regular home-based monitoring. Since smartphones contain sensors such as video cameras that detect arterial pulsations, they could also be used to assess cardiovascular health. Researchers have developed a variety of image processing and machine learning techniques for predicting BP via smartphone or video camera. This review highlights research behind smartphone and video camera methods for measuring BP. These methods may in future be used at home or in clinics, but must be tested over a larger range of BP and lighting conditions. The review concludes with a discussion of the advantages of the various techniques, their potential clinical applications, and future directions and challenges. Video cameras may potentially measure multiple cardiovascular metrics including and beyond BP, reducing the risk of cardiovascular disease.
... For a variety of analytes, MN-mediated sampling of interstitial fluid is evolving as a promising alternative to blood sampling, with glucose being a major target. Because of their short length (less than 1000 m), MNs can penetrate the stratum corneum and enter the ISF in the viable epidermis and top layers of the dermis without stimulating nociceptors or touching blood vessels, making them a minimally invasive method of extraction (Wang et al. 2019;Kap et al. 2021;Jendrike et al. 2017). Fracture and buckling are two possible failure scenarios of MNs. ...
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Diabetes mellitus is a severe condition in which the pancreas produces inadequate insulin or the insulin generated is ineffective for utilisation by the body; as a result, insulin therapy is required for control blood sugar levels in patients having type 1 diabetes and is widely recommended in advanced type 2 diabetes patients with uncontrolled diabetes despite dual oral therapy, while subcutaneous insulin administration using hypodermic injection or pump-mediated infusion is the traditional route of insulin delivery and causes discomfort, needle phobia, reduced adherence, and risk of infection. Therefore, transdermal insulin delivery has been extensively explored as an appealing alternative to subcutaneous approaches for diabetes management which not only is non-invasive and easy, but also avoids first-pass metabolism and prevents gastrointestinal degradation. Microneedles have been commonly investigated in human subjects for transdermal insulin administration because they are minimally invasive and painless. The different types of microneedles developed for the transdermal delivery of anti-diabetic drugs are discussed in this review, including solid, dissolving, hydrogel, coated, and hollow microneedles. Numerous microneedle products have entered the market in recent years. But, before the microneedles can be effectively launched into the market, a significant amount of investigation is required to address the numerous challenges. In conclusion, the use of microneedles in the transdermal system is an area worth investigating because of its significant benefits over the oral route in the delivery of anti-diabetic medications and biosensing of blood sugar levels to assure improved clinical outcomes in diabetes management.
... Monitoring applications often require repeated sampling over a sustained period (from hours up to months) to assess appreciable differences in disease states, and therefore benefit from being low-cost and noninvasive. In recent years, SBI systems have been proposed for monitoring of vital signs, 103-109 blood glucose, [110][111][112][113] blood pressure, 114,115 blood oxygenation, 68,116 hemoglobin concentration, 72 atrial fibrilation, 117,118 jaundice, 73,97,119,120 skin cancer, 121 and diabetic foot ulcers. 55,122 All of these applications propose utilizing either contact-based or contactless optical measurements using the smartphone camera, most often by individuals on themselves (i.e., selfmonitoring). ...
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Significance: Smartphones come with an enormous array of functionality and are being more widely utilized with specialized attachments in a range of healthcare applications. A review of key developments and uses, with an assessment of strengths/limitations in various clinical workflows, was completed. Aim: Our review studies how smartphone-based imaging (SBI) systems are designed and tested for specialized applications in medicine and healthcare. An evaluation of current research studies is used to provide guidelines for improving the impact of these research advances. Approach: First, the established and emerging smartphone capabilities that can be leveraged for biomedical imaging are detailed. Then, methods and materials for fabrication of optical, mechanical, and electrical interface components are summarized. Recent systems were categorized into four groups based on their intended application and clinical workflow: ex vivo diagnostic, in vivo diagnostic, monitoring, and treatment guidance. Lastly, strengths and limitations of current SBI systems within these various applications are discussed. Results: The native smartphone capabilities for biomedical imaging applications include cameras, touchscreens, networking, computation, 3D sensing, audio, and motion, in addition to commercial wearable peripheral devices. Through user-centered design of custom hardware and software interfaces, these capabilities have the potential to enable portable, easy-to-use, point-of-care biomedical imaging systems. However, due to barriers in programming of custom software and on-board image analysis pipelines, many research prototypes fail to achieve a prospective clinical evaluation as intended. Effective clinical use cases appear to be those in which handheld, noninvasive image guidance is needed and accommodated by the clinical workflow. Handheld systems for in vivo, multispectral, and quantitative fluorescence imaging are a promising development for diagnostic and treatment guidance applications. Conclusions: A holistic assessment of SBI systems must include interpretation of their value for intended clinical settings and how their implementations enable better workflow. A set of six guidelines are proposed to evaluate appropriateness of smartphone utilization in terms of clinical context, completeness, compactness, connectivity, cost, and claims. Ongoing work should prioritize realistic clinical assessments with quantitative and qualitative comparison to non-smartphone systems to clearly demonstrate the value of smartphone-based systems. Improved hardware design to accommodate the rapidly changing smartphone ecosystem, creation of open-source image acquisition and analysis pipelines, and adoption of robust calibration techniques to address phone-to-phone variability are three high priority areas to move SBI research forward.
... Among the enzymes used for detection, glucose oxidase (GOx) is a common choice owing to its relatively higher selectivity toward the monomer [286,288]. It is also easy to obtain, cheap, can withstand higher pH conditions, ionic strength, and temperature compared to other enzymes, such as hexokinase and glucose 1-dehydrogenase, for example [127,289,290]. Moreover, GOx catalyzes the oxidation of b-D-glucose into b-D-glucono-1,5-lactone and hydrogen peroxide by using molecular oxygen as an electron acceptor [291,292]. ...
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Among the many biological entities employed in the development of biosensors, enzymes have attracted the most attention. Nanotechnology has been fostering excellent prospects in the development of enzymatic biosensors, since enzyme immobilization onto conductive nanostructures can improve characteristics that are crucial in biosensor transduction, such as surface-to-volume ratio, signal response, selectivity, sensitivity, conductivity, and biocatalytic activity, among others. These and other advantages of nanomaterial-based enzymatic biosensors are discussed in this work via the compilation of several reports on their applications in different industrial segments. To provide detailed insights into the state of the art of this technology, all the relevant concepts around the topic are discussed, including the properties of enzymes, the mechanisms involved in their immobilization, and the application of different enzyme-derived biosensors and nanomaterials. Finally, there is a discussion around the pressing challenges in this technology, which will be useful for guiding the development of future research in the area.
... While the other approach involves just developing the software for the smartphone to analyze the different aspects of the image and perform the required processing as we present here in this article [4,5]. Biochemical materials, nanomaterials, and hazardous materials were investigated, analyzed, and tested with the smartphone-based approach to naming a few, glucose [6][7][8], c-reactive protein [9], gold nanoparticles [10], nitrite [11,12], chromium [13,14], iron [14], mercury [15]. The concentration measurement is a key element in characterizing the material behavior, for example, in environmental protection, usually, the materials should be at a certain level of concentration when this exceeds the appropriate amount it leads to hazardous situations such as poisoning, fatigue, and death of certain species. ...
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In this paper, colorimetric analysis for biochemical samples has been realized, by developing an easy-to-use smartphone colorimetric sensing android application that can measure the molar concentration of the biochemical liquid analyte. The designed application can be used for on-site testing and measurement. We examined three different biochemical materials with the application after preparation with five different concentrations and testing in laboratory settings, namely glucose, triglycerides, and urea. Our results showed that for glucose triglycerides, and urea the absorbance and transmittance regression coefficient (R²) for the colorimetric sensing application were 0.9825, and 0.9899; 0.9405 and 0.9502; 0.9431 and 0.8597, respectively. While for the spectrophotometer measurement the (R²) values were 0.9973 @560 nm and 0.9793 @600 nm; 0.952 @620 nm and 0.9364 @410 nm; 0.9948 @570 nm and 0.9827 @530 nm, respectively. The novelty of our study lies in the accurate prediction of multiple biochemical materials concentrations in various lightning effects, reducing the measurement time in an easy-to-use portable environment without the need for internet access, also tackling various issues that arise in the traditional measurements like power consumption, heating, and calibration. The ability to convey multiple tasks, prediction of concentration, measurement of both absorbance and transmittance, with error estimation charts and (R²) values reporting within the colorimetric sensing application as far as our knowledge there has not been any application that can provide all the capabilities of our application.
Background Self-management is an important pillar for diabetes control and to achieve it, glucose self-monitoring devices are needed. Currently, there exist several different devices in the market and many others are being developed. However, whether these devices are suitable to be used in resource constrained settings is yet to be evaluated. Aims To assess existing glucose monitoring tools and also those in development against the REASSURED which have been previously used to evaluate diagnostic tools for communicable diseases. Methods We conducted a scoping review by searching PubMed for peer-review articles published in either English, Spanish or Portuguese in the last 5 years. We selected papers including information about devices used for self-monitoring and tested on humans with diabetes; then, the REASSURED criteria were used to assess them. Results We found a total of 7 continuous glucose monitoring device groups, 6 non-continuous, and 6 devices in development. Accuracy varied between devices and most of them were either invasive or minimally invasive. Little to no evidence is published around robustness, affordability and delivery to those in need. However, when reviewing publicly available prices, none of the devices would be affordable for people living in low- and middle-income countries. Conclusions Available devices cannot be considered adapted for use in self-monitoring in resource constraints settings. Further studies should aim to develop less-invasive devices that do not require a large set of components. Additionally, we suggest some improvement in the REASSURED criteria such as the inclusion of patient-important outcomes to increase its appropriateness to assess non-communicable diseases devices.
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Paper-based immunoassays are becoming powerful and low-cost diagnostic tools, especially in resource-limited settings. Inexpensive methods for quantifying these assays have been shown using desktop scanners, which lack portability, and cameras, which suffer from the ever changing ambient light conditions. In this work, we introduce a novel approach of quantifying colors of colorimetric diagnostic assays with a smartphone that allows high accuracy measurements in a wide range of ambient conditions, making it a truly portable system. Instead of directly using the red, green, and blue (RGB) intensities of the color images taken by a smartphone camera, we use chromaticity values to construct calibration curves of analyte concentrations. We demonstrate the high accuracy of this approach in pH measurements with linear response ranges of 1-12. These results are comparable to those reported using a desktop scanner or silicon photodetectors. To make the approach adoptable under different lighting conditions, we developed a calibration technique to compensate for measurement errors due to variability in ambient light. This technique is applicable to a number of common light sources, such as sun light, fluorescent light, or smartphone LED light. Ultimately, the entire approach can be integrated in an "app" to enable one-click reading, making our smartphone based approach operable without any professional training or complex instrumentation.
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This is an IUPAC report on the definition and classification of electrochemical biosensors. It can serve as a primer on biosensors and includes details on construction, different sensor formats and transducer types.
We report on a smartphone spectrometer for colorimetric biosensing applications. The spectrometer relies on a sample cell with an integrated grating substrate, and the smartphone's built-in light-emitting diode flash and camera. The feasibility of the smartphone spectrometer is demonstrated for detection of glucose and human cardiac troponin I, the latter in conjunction with peptide-functionalized gold nanoparticles.
Complementary metal oxide semiconductor (CMOS) image sensors have received great attention for their high efficiency in biological applications. The present work describes a CMOS image sensor-based whole blood glucose monitoring system through a point-of-care (POC) approach. A simple poly-ethylene terephthalate (PET) chip was developed to carry out the enzyme kinetic reaction at various concentrations (110-586 mg/dL) of mouse blood glucose. In this technique, assay reagent is immobilized onto amine functionalized silica (AFSiO2) nanoparticles as an electrostatic attraction in order to achieve glucose oxidation on the chip. The assay reagent immobilized AFSiO2 nanoparticles develop a semi-transparent reaction platform, which is technically a suitable chip to analyze by a camera module. The oxidized glucose then produces a green color according to the glucose concentration and is analyzed by the camera module as a photon detection technique; the photon number decreases when the glucose concentration increases. The combination of these components, the CMOS image sensor and enzyme immobilized PET film chip, constitute a compact, accurate, inexpensive, precise, digital, highly sensitive, specific, and optical glucose-sensing approach for POC diagnosis. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE).
Backgkround: Rapidly increasing healthcare costs in economically advantaged countries are currently unsustainable, while in many developing nations, even 50-year-old technologies are too expensive to implement. New and unconventional technologies are being explored as solutions to this problem. In this study, we examined the use of a smartphone as the detection platform for 2 well-developed, relatively inexpensive, commercially available clinical chemistry assays as a model for rapid and inexpensive clinical diagnostic testing. Methods: An Apple iPhone 4 camera phone equipped with a color analysis application (ColorAssist) was combined with Vitros® glucose and urea colorimetric assays. Color images of assay slides at various concentrations of glucose or urea were collected with the iPhone 4 and quantitated in three different spectral ranges (red/green/blue or RGB) using the ColorAssist app. When the diffuse reflectance data was converted into absorbance, it was possible to quantitate glucose or blood urea nitrogen (BUN) over their clinically important concentration ranges (30-515mg/dl for glucose or 2-190mg/dl for BUN), with good linearity (R(2)=0.9994 or 0.9996, respectively [n=5]). Results: Data collected using the iPhone 4 and canine serum samples were in agreement with results from the instrumental "gold standard" (Beckman Coulter AU480 Chemistry System) (R(2)=0.9966 and slope=1.0001 for glucose; R(2)=0.9958 and slope=0.9454 for BUN). Glucose determinations of serum samples made using this smartphone method were as accurate as or more accurate than a commercial colorimetric dry slide analyzer (Heska® Element DC Chemistry Analyzer, Loveland, CO) and 2 glucometers: ReliOn® Ultima (Abbott Diabetes Care Inc) and Presto® (AgaMatrix Inc.H). BUN determinations made using the smartphone approach were comparable in accuracy to the Heska instrument. Conclusion: This demonstration shows that smartphones have the potential to be used as simple, effective colorimetric detectors for quantitative diagnostic tests, and may be applicable for both point-of-care applications in the developed world and field deployment in developing nations.
In recent decades, several standard colorimetric reactions for chemical analysis have been miniaturized to microwells on microplates, including methods useful for environmental measurements. Advantages of method miniaturization include a reduction in reagents required, improved safety, reduced waste stream, and increased sample throughput. However, the widespread use of microscale techniques employing microplates in classroom settings is likely limited by the high cost of microplate readers. Although spectrophotometers read peaks of specific wavelengths, absorbance spectra tend to be relatively broad and measurements at specific wavelengths are highly autocorrelated with those of nearby neighbors, which implies that broadband intensity data of red, green, and blue channels may indeed be adequate for digital colorimetric quantification. In this article, we demonstrate that digital image analysis of a scanned microplate image can substitute for a spectrophotometer for several common quantitative microscale procedures. This finding allows for cost effective and microscale quantification of several compounds to be demonstrated in the laboratory. Additionally, popular teaching and learning activities such as water quality monitoring can now be performed accurately and inexpensively using digital image analysis.
Three groups of the amperometric biosensors such as unmediated, mediated and based on direct transfer of electrons have been thoroughly described, and their advantages and disadvantages were shown. The amperometric biosensors are mostly utilized in commercial devices since they are studied to a greater extent and have some advantages. The modern commercial systems based on amperometric biosensors and its applications have been presented. The major field of employing biosensors is medical diagnostics where numerous commercial devices are currently functioning.