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Yadav et al, BioImpacts, 2020, 10(3), 141-150
doi: 10.34172/bi.2020.18

Microfluidic system for screening disease based on physical properties
of blood
Siddharth Singh Yadav1, Basant Singh Sikarwar1* ID , Priya Ranjan2, Rajiv Janardhanan3

1 Department of Mechanical Engineering, Amity University Uttar Pradesh, Noida, India
2 Department of Electrical Engineering, Amity University Uttar Pradesh, Noida, India
3 Department of Public Health, Amity University Uttar Pradesh, Noida, India

Blood is a non-Newtonian shear-thinning fluid and its
rheological properties such as plasma viscosity, hematocrit,
red blood cell accumulation, and deformability vary with
age and sex.1,2 Blood viscosity increases from childhood to
adult age but decreases in elderly men whilst progressively
increasing in elderly women.3 The rheological properties
of blood undergo certain changes during both the process
of ontogenesis in humans, as well as shrinkage due to the
age-related involution. Pathological test reports indicate
that patients afflicted with tuberculosis and anemia have

low red blood cell and platelets count causing the blood to
become thinner with lower levels of viscosity.4-6 A recent
study has reported that fluid and flow properties of blood
affect tissue perfusion, which contributes significantly to
hydrodynamic resistance in vessels.7 Similarly, a variety
of human diseases could be detected due to the variance
of surface tension in the blood.8 In a weightless state,
the surface tension of blood is known to influence the
formation of blood clots, thereby affecting the character
of bleeding from the skin.9 Blood rheology and surface
tension have a statutory role in healing.10

*Corresponding author: Basant Singh Sikarwar, Email: [email protected]

© 2020 The Author(s). This work is published by BioImpacts as an open access article distributed under the terms of
the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/). Non-commercial uses of the work are
permitted, provided the original work is properly cited.

PPuubblliisshh FFrreeee







Introduction: A key feature of the ‘One Health’ concept
pertains to the design of novel point of care systems
for largescale screening of health of the population
residing in resource-limited areas of low- and middle-
income countries with a view to obtaining data at a
community level as a rationale to achieve better public
health outcomes. The physical properties of blood are
different for different samples. Our study involved the
development of an innovative system architecture based
upon the physical properties of blood using automated
classifiers to enable large-scale screening of the health of
the population living in resource-limited settings.
Methods: The proposed system consisted of a simple, robust and low-cost sensor with capabilities
to sense and measure even the minute changes in the physical properties of blood samples. In this
system, the viscosity of blood was derived from a power-law model coupled with the Rabinowitsch-
Mooney correction for non-Newtonian shear rates developed in a steady laminar Poiseuille flow.
Surface tension was measured by solving the Young-Laplace equation for pendant drop shape
hanging on a vertical needle. An anticipated outcome of this study would be the development of a
novel automated classifier based upon the rheological attributes of blood. This automated classifier
would have potential application in evaluating the health status of a population at regional and
global levels.
Results: The proposed system was used to measure the physical properties of various samples like
normal, tuberculous and anemic blood samples. The results showed that the physical properties of
these samples were different as compared to normal blood samples. The major advantage of this
system was low-cost, as well as its simplicity and portability.
Conclusion: In this work, we proposed making a case for the validation of a low-cost version of a
microfluidic system capable of scanning large populations for a variety of diseases as per the WHO
mandate of “One Health”.

Article Type:
Original Article

Article History:
Received: 22 Dec. 2018
Revised: 26 Mar. 2019
Accepted: 14 May 2019
ePublished: 22 May 2019

Screening system
Surface tension

Article Info

Yadav et al

BioImpacts, 2020, 10(3), 141-150142

only with respect to body temperature but also surface
tension, which in turn has a statutory effect of many
vital functions of the human body.25 Fathi-Azarbayjani
and Jouyban reported that surface tension measurement
combined with a routine lab test is a novel non-invasive
technique used for not only diagnosing various diseases
but also ranking the patients in the order of their
severity.26 Sikarwar et al proposed the non-linear system
of architecture for screening diseases based on the certain
pattern in blood samples stains.15 Kim et al proposed a
novel technique for measuring hemoglobin for screening
anemia with help of microfluidics system which consists
of a novel single sidewall air bubble-free microfluidic
cuvette.27 Yap et al designed and fabricated microfluidics
systems for facilitating the diagnosis of iron deficiency-
induced anemia.28 They used this system for detecting
various diseases such as human immunodeficiency virus
(HIV), malaria and dengue as well. The viscosity of blood
was observed to decrease substantially in patients suffering
from dengue or malaria and this attribute could be used
not only for large-scale screening of populace afflicted
with the disease along with their surrogate markers but
also to find the precursors of the above-mentioned two

Pathological features of diseases vary in nature and
magnitude. Taken together with inherent variances in the
genetic base across the Indian sub-continent, correlation
of variances in rheological and physical properties of blood
could be used effectively for preliminary screening of the
health status of a community using minimally invasive
techniques. Although viscometer and surface tensiometer
systems are very common in the field of engineering, their
usage in the context of biological fluids and medicine is still
in its infancy.29,30 A reason for this discrepancy could be
the fact that the rheology and surface interface properties
of biological fluids have not been applied extensively to
characterize the disease pathophysiology extensively.

This formed the premise for the design and fabrication of
a simple low-cost system for large-scale screening diseases
based on the physical properties of blood. This system
consists of a micro-capillary scanning viscometer and a
micro-tensiometer to measure the physical properties
of blood samples. Later, automated linear and nonlinear
classifiers were also developed for automated reasoning
and presentation of results on a user-friendly interface.
The major advantages of this system are low cost and high
accuracy for measuring data not to mention its portability.
This system requires only a few microliters (µL) of blood
for making its measurements. The portability of the
system could be exploited to develop novel points of
care systems with the capability of large-scale subjects
in resource-limited settings across the low- and middle-
income countries (LMICs) which is in accord with the
WHO’s mandate of “One Health”. This system has been
calibrated and tested over a spectrum of blood samples
and the result has been found to be satisfactory.

The rheological attributes of the Blood have been
extensively studied over the last 25 years by groups with
divergent professional competencies such as physicists,
material scientists, as well as engineers.12,13 It is only in
the last decade or so that biologists and doctors have
evinced interest in using the physical properties of blood
to classify and typify many human and cattle diseases.
Given its significance, unfortunately, there is an acute
lack of systematic studies correlating rheology and surface
tension to pathological disease states,12-14 although few
studies have tried to ascribe the diseased state of an
individual with rheological properties and surface tension
of blood.15,16

A variety of disease states are known to affect the
physical properties of blood and many scientists11,17,18 have
reported this observation as a part of studies focusing on
the pattern recognition of bloodstains for healthy and
diseased patients on the basis of microscopic structures as
shown in Fig. 1. These studies have demonstrated that the
pattern of the stains of blood varies extensively for blood
samples representing different disease states.

Moreover, they relate this anomaly to the physical
properties of blood such as surface tension and
viscosity.11,16,19 Impact of viscosity and surface tension on
biomedical formulation and technology has been studied
in significant detail.18,20 Broberg et al sought to determine
the relationship between blood viscosity and iron
deficiency and their impact on the clinical presentation of
cyanotic congenital heart diseases.21 The viscosity of blood
is known to increase in the case of patients burdened with
iron deficiency.22 Sikarwar et al were able to decipher a
recognition pattern in the bloodstains from patients with
a variety of pathophysiological disorders.23 Mukesh Roy
et al reported flow and fluid properties to be the prime
factors for producing high wall shear stress close to the
narrow zone of veins in their simulations.24 Rosina et al
showed that rheological properties of blood differed not

Fig. 1. Micrograph is depicting morphological attributes of a blood smear
(235 pixel/mm): (A) a blood smear sample of a normal woman, (B) a smear
from a woman suffering from anaemia, (C) a smear sample of a normal
man, and (D) a person with hyperlipidaemia.11

Microfluidic system for screening disease based on physical properties of blood

BioImpacts, 2020, 10(3), 141-150 143

Materials and Methods
Details of proposed system
A simple, low-cost system was designed and fabricated
for screening diseases based on physical properties of
blood as shown in Fig. 2. It consists of two micro-fluidic
modules namely capillary scanning viscometer and
pendant drop tensiometer (Fig. 2A-B) integrated with
system architecture and user interface (UI) for disease
mapping. It measures the physical properties of blood
for the development of a unique disease mapping system
(Fig. 2C) which classifies the disease based on measured
viscosity and surface tension of blood sample along with
the automated risk stratification of susceptibility patterns
in a user-friendly manner.

The system for measuring the physical properties was
fabricated at Mechanical Engineering Department, Amity
University Uttar Pradesh NOIDA and some parts of this
system were fabricated in the local market of Noida, India.
The details of the components bought for fabrication
are shown in Table 1. A micro-capillary viscometer with
a surface tension measurement device is to be designed
and fabricated. The schematic diagram is shown in Fig.
2. The device is portable and maintains blood samples
in a closed system, which is coated with biocompatible
material and temperature-controlled, simulating in vivo
conditions. It can be placed directly in the blood sample
laboratory, permitting blood to be drawn directly into the
device, precluding the need for anticoagulation. Scanning
capillary tube viscometer, as shown in Fig. 2A, consists
of charge-coupled systems that are positioned vertically,
two light-emitting diodes with two transparent riser
tubes used to measure the flow rate of blood through the
capillary at different pressure head. The inside diameter
of both the transfer and riser tubes used in the present
tests were d1=d2=3 mm. The inside diameter and length

of the capillary tube were dcap=0.797mm and Lcap=100
mm, respectively. The small diameter of the capillary tube,
compared with those of both the transfer and riser tubes,
is chosen to ensure that the friction in the capillary tube
was significantly greater than those in the others.

The blood is a non-Newtonian shear-thinning fluid. Its
viscosity is represented as:

b kµ γ

−=  (1)

Where μb is the viscosity of blood, k the flow consistency
index, n the flow behavior index, and γ the rate of

3 1 8


n Q
n d


+ 
=  
 


The viscosity of the blood was derived from the power-
law model coupled with the Rabinowitsch-Mooney
correction for non-Newtonian shear rates developed in a
steady laminar Poiseuille flow. Hence the volume flow rate
(Q) is estimated as:


rd dhQ

π 

=  
 


Accordingly, the law of conservation energy for scanning
capillary tube viscometer is31:

[ ]


4 3 1
( ) ( ) h(t ) 2


c r
i o

c c

kL dn dh
h t h t

d n d dt
  +  

− − ∆ = ∞ =    
    


For sake of simplicity, one may define a new function
( ) ( ) h(t )i oh t h t α− − ∆ = ∞ = and so that equation 4


( )

1/ 3

24 3 1


c c

c r

gD dn
kL n d


   
=   

+   

Fig. 2. Schematic diagram of microfluidic system for physical properties of blood; (A) scanning capillary tube viscometer system, (B) pendant drop tensiometer,
and (C) system architecture for diseases mapping.

Yadav et al

BioImpacts, 2020, 10(3), 141-150144

( )1/ n



= − (5)

Equation 5 is the first-order linear differential equation,
and its analytical solution is

[ ]
( 1 11

(t) (0)

n n


α α λ

− − −  
= −  

  


The computer code written to determine the viscosity
from experimental data is depicted as a flow diagram
(Fig. 3).

Fig. 2B shows a tensiometer which consists of a transparent
cubical chamber (1 cm × 1 cm × 4 cm), sufficiently large as
compared to the size of the droplet. Its bottom is exposed
to constant humidity levels throughout the experiment,
via a thick porous layer of paper to ensure that there is no
evaporation of drop inside the test cell. In this method,
approximately 5 µL stable drop at 20-gauge blunt needle
tip is formed under controlled conditions and an image of
the drop is captured by a camera-aided with appropriate
lighting. The shape of the captured droplet interface is
obtained using image processing. Based on the Young-
Laplace equations which is as follows:

1 2

1 1

r r
 

∆ = + 
  (7)

Equation 7 is solved for numerically appropriate
boundary conditions to estimate the interface shape

Table 1. The details of components used in fabrication of scanning capillary tube viscometer and pendant drop tensiometer

Components Specification Manufacturer

Syringe pump

Injection accuracy = ±3%, pump mechanical accuracy=±2%
reproducibility =0.1%, Maximum number of syringes = 1 power
consumption=30 VA, volume limit range=0.1 mL to 999.9 mL and
weight=2.0 kg

Hygeia Medical Supplies and Services Sheridan
Boulevard Unit 3C, Lakewood, CO 80214, USA

Micro-capillary tube

Diameter: 0.797 mm and length: 100 mm
Characteristics: (a) transparent, (b) resistant to almost all inorganic
chemicals, (c) tasteless, (d) smooth polished inner wall, (e) low gas
permeability, (f) non-aging and non-oxidizing, and (g) high dielectric

IDEX India Pvt Ltd, 205, Matharu Arcade, Plot
No. 32 Subhash Road, Vile Parle (East)

Riser tube
Suitable for above micro-capillary tubes
Diameter: 3 mm

IDEX India Pvt Ltd, 205, Matharu Arcade, Plot
No. 32 Subhash Road, Vile Parle (East)

Transfer tube
Suitable for above micro-capillary tubes
Diameter: 3 mm

IDEX India Pvt Ltd, 205, Matharu Arcade, Plot
No. 32 Subhash Road, Vile Parle (East)

CCD (charged
coupled device)

High sensitivity high resolution, Low smear and low dark current
Continuous variable-speed shutter horizontal register: 5 V drive
Reset gate: 5 V drive


LED (light emitting

Model: WC301-08 white color
Frequency: 0.31×0.32
Intensity: 17,000 mcd

Bhagwati Lighting Industries Peeragarhi,
New Delhi

High speed camera
Max.Resolution-1280 × 1280
Max.FPS-1850 fps

Phantom LAB3a10 with Nikon AF-S

Syringes 10 mL plastic syringes Fisher scientific

of a drop. The shape of a pendant droplet interface of
volume 5 µL can be found theoretically (solving equation
7 numerically) by iterating the value of surface tension
till the predicted interface equals to the captured drop
interface. Fig. 4 shows the flow diagram for measuring the
surface tension of blood samples.

Fig. 5 shows the image of the blood drop captured by
the camera. Fig. 5B-C shows the experimentally measured
drop interface in circular symbols versus numerical

Fig. 3. Flow diagram depicting the measurement of viscosity of the blood

Microfluidic system for screening disease based on physical properties of blood

BioImpacts, 2020, 10(3), 141-150 145

prediction (line). As per the algorithm of surface tension
measurement (Fig. 4), the surface tension value is iterated
untill the numerical prediction interface fits best with the
experimentally measured interface.

Once the data obtained from rheological attributes of
blood are generated using the microfluidic system-based
system, our observations would be automated using non-
linear algorithms to develop a predictive analytics based
risk score for disease onset in a user-friendly fashion.
This is accomplished based on the table-lookup kind of
wedge base where different values of blood rheological
properties are mapped with the values representing
different diseases such as anemia or anomalous conditions
like dehydration. This lookup table has been built after
extensive experimentation and can be thought of as a
brain of the proposed machine as shown in Tables 1 and

2. The system architecture for disease mapping is shown
in Fig. 2C. The input of this system is age, gender, and
physical properties of blood and the output of the system
is an artificial intelligence risk prediction score to a host
of communicable and non-communicable diseases. The
functionalization of disease mapping has been shown in
Fig. 6.

Procedure of lookup table building from experimental
The blood samples were collected from normal and
disease samples (anemic blood sample and TB blood
samples) from JAYPEE Hospital Noida.

The system was set up at a pathology laboratory in
JAYPEE Hospital Noida. Experiments were conducted
with normal blood samples, anemic blood samples, and
tuberculosis blood samples. Blood samples for this study
were taken according to the specified protocol (as shown
in Table 2). Using statistical techniques, we took thirty
samples for each case study. Experiments were performed
throughout the year to obtain the blood from a donor at a
particular age as per protocol. The system was connected
to a computer and software of measuring viscosity and
surface tension from the clinical samples after properly
calibrating the system. Backlight and charge-coupled
system (CCD) were switched on for capturing the images
and the height of blood samples was (h1 and h2) computed
at various time steps (1.5 seconds). The test was initiated
with a venipuncture on the patient using a 22-gauge
stainless steel needle. Fresh blood was first directly taken
from veins from the first to the second stopcock to collect
blood into the syringe. Two milliliters blood was collected
in the syringe for validation of system with a commercial
viscometer, tensiometer, and hematocrit measurement.

The viscosity was measured by scanning capillary
viscometer following the method as reported in the
literature.31 In this method, the second stopcock was
tuned to a position to allow blood flow to both the
capillary tube and the riser tube 2. When the blood
reached a predetermined height of 250 pixels in riser tube

Fig. 5. (A) Image of blood drop captured by camera, (B-C) Pendant drop: experimentally measured drop contour is shown by symbols versus the best fit of
the numerical prediction (line).

Fig. 4. Schematic diagram depicting measurement of surface tension of
blood samples.

Yadav et al

BioImpacts, 2020, 10(3), 141-150146

2, the second stopcock was shut to stop further blood flow
into riser tube 2, and the first stopcock was then turned to
direct blood flow into riser tube 1 up to a height of 1200

pixels. At t=0, the data acquisition system was enabled,
and both stopcocks were adjusted to allow blood to flow
from riser tube 1 to tube 2 as driven by gravity. Of note
is that the initial pixel difference of 950 was chosen to
produce the maximum shear rate of approximately 540
per second. The capillary tube was placed at a constant
temperature bath to maintain blood temperature at 37oC.
In this way, all data (h1 and h2) were acquired at various
time steps. Experimental data are shown in Table 3.

Simultaneously, some amount of blood flowed from
500 µm diameter capillary tube to tensiometer syringe
tip to form pendant mode of the droplet. This drop is
further captured by a 1-megapixel camera and saved in
the computer for measuring the surface tension of blood.
All the measurements were completed within 1 minute
from the time the blood samples were collected from the

Validation and data analysis
Data were analyzed after the microfluidics-based
measurements were validated against data available on
the physical properties of blood and other fluids. Fig.
7 shows the variation of blood viscosity with respect to
the shear rate. The blood sample was collected from
the donor in such a way that its hematocrit (HT) value
was the same as reported in the literature.32 The present
system results are quite satisfactory and in accord with
the published literature. Similarly, the data obtained
from surface tensiometer were validated against the data
available in the literature.25 Fig. 8 shows the measured data

Table 2. Matrix of blood sample collection from various pathologies

Type of samples Age range (y) No. of samples
Remarks (aging

of blood)



5-10 30

Free from
all diseases

and range of
hematocrit of
blood is 40 to


11-20 30
21-30 30
31-60 30


5-10 30
11-20 30
21-30 30
31-60 30



5-10 30 Iron deficiency
and free from
other diseases 11-20 30

21-30 30
31-60 30


5-10 30
11-20 30
21-30 30
30-60 30



5-10 30 Blood sample of
a patient that has

only TB11-20 30
21-30 30
31-60 30


5-10 30
11-20 30
21-30 30
31-60 30

Fig. 6. Schematic diagram of functioning of rheological attributes of blood as a function of risk scale for determining disease susceptibility patterns using an
automated classifier.

Microfluidic system for screening disease based on physical properties of blood

BioImpacts, 2020, 10(3), 141-150 147

in agreement with the published literature.32 In addition,
the error analysis of both microfluidic systems was carried
out. The confidence level of these systems is 98%.

Results and Discussion
The data generated from the proposed system have
been used to screen two diseases namely anemia and
tuberculosis. The samples were collected as per protocol
reported in the previous section. All the measured data
were tabulated in Table 3. Fig. 9 shows the variation
of viscosity with respect to the ages of male and female
patients and it was calculated for shear rate 100 s-1 of blood

flow. Fig. 9A shows the variation of viscosity with respect
to age for normal blood samples. However, Fig. 9B and
Fig. 9C show the viscosity for anemic and tuberculosis-
related (TB) blood samples. This plot shows that the
viscosity of blood samples is drastically different for
various diseases as compared to normal blood samples for
the same age and gender. It also shows that the viscosity
of all blood samples (normal, anemic, and tuberculosis)
at a given shear rate increases with increasing the age of
blood samples. In addition, the viscosity of normal blood
samples have very small difference with respect to gender
as shown in Fig. 9A. However, Fig. 9B and Fig. 9C show

Table 3. Physical properties of human blood during healthy and anemic condition

Type of samples Age range (y) Number of samples
Viscosity (mPa.s) at shear

rate 100 s-1 Surface tension (mN/m)



5-10 30 3.6 ± 0.07 52± 2.5
11-20 30 3.6 ± 0.22 52± 3.6
21-30 30 4.3 ± 0.05 53± 3.8
31-60 30 4.4 ± 0.09 60± 3.9


5-10 30 3.6 ± 0.10 55± 2.6
11-20 30 3.8 ± 0.12 60 ± 3.0
21-30 30 5.1 ± 0.09 62 ± 3.7
31-60 30 4.7 ± 0.13 60 ± 3.9

Anemic blood


5-10 30 2.16± 0.07 38 ± 2.40
11-20 30 2.18± 0.22 36 ± 2.45
21-30 30 2.58± 0.05 38 ± 2.50
31-60 30 2.64± 0.09 36 ± 2.56


5-10 30 2.16± 0.10 40 ± 2.5
11-20 30 2.20± 0.12 42 ± 2.54
21-30 30 2.90± 0.09 43 ± 2.58
30-60 30 2.78± 0.13 40 ± 2.60

Tuberculosis blood


5-10 30 1.08 ± 0.07 30 ± 2.40
11-20 30 1.08 ± 0.22 30 ± 2.45
21-30 30 1.29 ± 0.05 25 ± 2.50
31-60 30 1.32 ± 0.09 25 ± 2.56


5-10 30 1.08 ± 0.07 27 ± 2.5
11-20 30 1.14 ± 0.07 32 ± 2.54
21-30 30 1.53 ± 0.06 33 ± 2.58
31-60 30 1.41 ± 0.13 36 ± 2.60

Fig. 7. The comparative analysis of the viscosity values of blood samples
with respect to the shear rate published in literature32 and donor blood
samples measured by our system.

Fig. 8. The comparative surface tension values obtained from our
instrument with respect to data available in published literature.25

Yadav et al

BioImpacts, 2020, 10(3), 141-150148

drastic differences for two genders like female and male
blood samples which may belong to anemic or tuberculosis
patients. Blood viscosity depends on the content of the
blood, or the concentration of each of many components
in the plasma fluid. It depends on the concentration of red
blood cells and multiple proteins present in the plasma. It
is demonstrated that diseases like anemia and TB affect
the red cells of blood and this particular change of blood
viscosity in given samples is used in disease diagnostic

Fig. 10 shows the variation of surface energy with respect
to age of different male and female blood samples. Fig. 10A
shows the variation of surface tension with respect to age
of normal blood samples for both genders. However, Fig.
10B and Fig. 10C show the variation of surface tension of
abnormal (anemic and tuberculosis) blood samples again
for both genders. Anemic and TB blood samples have low
surface tension as compared to normal blood samples,
as shown in Fig. 10. Hence, the surface tension of blood
directly interlinks with the percentage of RBC. TB infection
generally occurs by the entry of the mycobacterium to the
respiratory system. This bacterium moderates the surface
energy of blood.26 Hence, multiple lipids form in the body
during the TB to destroy the surfactant property of blood
samples. Therefore, Fig. 10 shows that the surface energy
of normal blood samples is larger than that of the anemic
and TB samples and this nature of variation of the surface
energy of blood samples is used as a disease signature in
the form of diagnostic tool.

Fig. 11 plots the range of viscosity and surface tension
of all blood samples across different age groups. Surface
tension and viscosity of normal blood samples are higher
than the same of abnormal or diseased blood sample
across genders. For a normal blood sample, the viscosity
of blood samples must be greater than 2.6 at shear rate

Fig. 9. Variation of viscosity at 100 shear rate (1/s) with respect to age: (A)
normal blood samples, (B) anemic blood samples, and (C) tuberculosis
blood samples.

Fig. 10. Variation of surface tension with respect to age: (A) normal blood
samples, (B) anemic blood samples, and (C) tuberculosis blood samples.

Fig. 11. Graphic showing the cut-off line for discrimination of normal and
abnormal blood samples.

(A) (B)


100/s. However, the surface tension of normal blood
samples must be higher than 45 mN/m. This information
has been used in this manuscript for designing screening
system criteria.

In this work, we proposed to make a case for the validation
of a low-cost version of a microfluidic system capable of
scanning large populations for a variety of diseases as per
the WHO mandate of “One Health”. We proposed the use
of this system for providing an affordable and accessible
diagnosis to populace living in resource-limited settings
found in LMICs. It has already been validated against the
data available in the literature. This system is an example
of a low-cost innovation aimed at providing affordable
and accessible screening of the populace for a variety of

Microfluidic system for screening disease based on physical properties of blood

BioImpacts, 2020, 10(3), 141-150 149

What is the current knowledge?
√ Design and development of simple, robust and low-cost
disease screening devices based on physical properties of
blood in clinical environment.
√ The main characteristics of these devices are: (a) cheap and
simple, (b) highly accurate and measuring data within range
of ±1% uncertainty, (c) any person that has basic computer
knowledge can use them, and (d) a very few μL volume of
blood is required pushing it towards non-invasiveness.

What is new here?
√ New system architecture based on prognosis and diagnosis
data using automated linear and nonlinear classifiers for
automated reasoning and presentation of screening results.
√ Finally, an impact of these devices on Indian health care
scenario will be measured.

Research Highlights

diseases. The main characteristics of this system are: (a)
cheap and simple, (b) highly accurate measurement of
data, (c) ease of use by lay-person, and (d) only a small
volume (5 µL) of blood is required pushing it towards
non-invasiveness. The Innovative system of architecture
will be a diagnostic aid with data being automated using
linear and nonlinear classifiers for large-scale screening of
patients for a variety of diseases.

The authors would like to recognize the contribution of Jaypee
Hospital and labs in NOIDA (India) for providing various blood
samples as per our requirement. In addition, the authors acknowledge
the Science and Engineering Research Board (SERB), Department of
Science & Technology (DST), and Government of India (Project no:
ECR/2016/000020) for using the equipment of this project. We are
grateful to everyone with whom we had the pleasure to work.

Funding sources

Ethical statement
There is none to be declared.

Competing interests
There is none to be declared.

Authors’ contribution
BSS, SSY: Draft preparation, writing and reviewing, data handling. BSS:
Conceptualization, experiments design, study validation, writing and
reviewing, data analysis. SSY, BSS: Data handling, data analysis, Writing.
BSS, PR, RJ: Conceptualization, trials design, supervision, writing and

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