Keywords

1 Introduction

Onset of disease directly affects the mechanical, electrical (Cole et al. 2017; Petchakup et al. 2017; Huh et al. 2005; Schwan 1957), and optical (Antfolk and Laurell 2017) properties of the cell, which can act as a biomarker. Importance of studying different cells and sampling of biological fluids have increased, which forces researchers to analyze single cells individually (Petchakup et al. 2017). Analysis of single cell is very useful in drug discovery application by studying blood containing rare cells such as fetal cells (Fiddler 2014), circulating tumor cells (CTC) (Zhang et al. 2016), and stem cells; also, it is useful in immunological research. Bulk analysis of the cell sample and extraction of the information for single cell using probabilistic approach (as followed previously) does not provide accurate information (Wang and Bodovitz 2010). Here, the probabilistic analysis means instead of studying the cells individually; a stochastic average of the bulk measurement is considered to collect the information about the single cell. In contrast, analyzing single cells based on their optical and electrical properties gives a clearer picture. The conventional methods are available to analyze single cells but they have some limitations such as the conventional cell analysis method uses a large volume of samples to analyze the cells which is very crucial for the cases where low volume of samples is available (Preckel 2010a). Also, it is difficult to automate the analysis processes in the conventional methods (Preckel 2010b). The microfluidics technique uses small structures comparable to the biological cells which gives explicit control over the cells. This precise control leads to a better isolation of cells based on the targeted properties (Dittrich and Schwille 2003), but this explicit control over cells is missing in conventional methods. The conventional methods take long analysis time that may affect the viability and usefulness of the cells (Antfolk and Laurell 2017). Microfluidic technique looks promising to overcome the limitations present in the conventional methods. As microfluidic techniques depend on the intrinsic cell properties rather than traditional biomarkers (Antfolk and Laurell 2017). Microfluidic concepts like a lab-on-chip and micrototal analysis system bring more sophisticated tool for analyzing single cells (Yin and Marshall 2012).

Microflow cytometer is a very powerful microfluidic tool because of its ability to differentiate group of cells in a heterogeneous mixture (Guo et al. 2015). Recent development in the microflow cytometer has given the ability to analyze thirteen parameters simultaneously, which leads researcher to find well-defined interesting biological subsets in biofluids. Flow cytometry is also helpful for diagnosis of hematological disorders (Huh et al. 2005; Sobti and Krishan 2003). Flow cytometry is able to characterize cells or particle based on their optical, fluorescence (Ibrahim and van den Engh 2007), and electrical properties (Cheung et al. 2010). In a cytometer, particles are allowed to pass through a light beam in a moving fluid and produce a scatter or fluorescence signal (Etcheverry et al. 2017). Then, the signal analysis gives the information about biochemical and biophysical aspects of the particle. The scattering signal tells about size and structure of the particle or cell, whereas fluorescence signal is related to the cellular components (Brown and Wittwer 2000). Flow cytometers are divided into two types based on their ability to sort particles. First one is sorting type, and second one is non-sorting type flow cytometers. Sorting-based flow cytometers are capable of sorting particles from the heterogeneous mixture based on fluorescence and scatter signal. FACS(Fluorescence-activated cell sorter) is an example of sorting type flow cytometer (Fig. 1) (Adan et al. 2016). A flow cytometry consists of fluidic system, optical system, sorting system, and electronics system (Weaver 2000). Fluidic system is responsible to transport the particles in a channel to the interrogation zone. Optical system consists of a light source, optical filters, optical components, detectors, and electronic system, which is useful in converting a detected light signal into an electronic signal (Cho et al. 2010). Some flow cytometer uses electronics to create sorting mechanisms.

Fig. 1.
figure 1

a Schematic of a FACS (PMT photomultiplier tube, SSC represent side scatter, and FSC forward scatter), b Schematic of sorting system of a FACS. Reprinted by permission of the publisher Taylor & Francis Ltd., http://www.tandfonline.com (Adan et al. 2016)

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It is very important to analyze the particles accurately by the flow cytometer. To accurately analyze the individual particle, it is necessary to have single particle in the interrogation zone (Ateya et al. 2008). To achieve this condition, the flow-focusing techniques are used, where the sample fluid is focused to a single file stream. Then, these particles are analyzed by the optical components, and based on this light signal, particles are sorted. In this chapter, we discuss each system in detail. The Fig. 1 shows the schematic of a flow cytometer.

2 Fluidic System

It is very important to have single file stream of a sample fluid to get accurate information of scattered, fluorescence signal, and impedance value in optical and impedance-based flow cytometer, respectively. The focusing of the sample fluid is important to ensure single file stream condition in a microchannel, and the use of a narrow channel may lead to clogging as well as microparticles may adhere to walls of a microchannel and may not be useful for a sample containing different size of particles. There are different techniques available to converge sample fluid in a microchannel such as hydrodynamic flow focusing, droplet generation, acoustophoresis, dielectrophoresis (DEP), and electrokinetic focusing (Fu et al. 2004).

3 Hydrodynamic Focusing

The hydrodynamic focusing is the one where sample fluid is focused by using a sheath flow. The focused sample fluid width is adjusted such that a narrow width is comparative to the size of the particle in a channel. The width of a focused sample is a function of relative flow rates (Lee et al. 2006). In a microchannel, hydrodynamic focusing is extensively used. There are two types of hydrodynamic flow focusing, two dimensional (2-D) and three dimensional (3-D). The general concept of these flow-focusing methods is described with a schematic diagram shown in Fig. 2.

Fig. 2.
figure 2

Schematics of a 2-D hydrodynamic focusing (q flow rate of a sample, Q/2 one side sheath flow rate in a channel, w width and h height, a focused sample width) b four sheath inlet 3-D hydrodynamic flow focusing (q flow rate of a sample, Q/2 one side sheath flow rate in a channel, w width and h height, a focused sample width). Reproduced from Shivhare et al. (2016), With permission of Springer

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The 2-D focusing channel fabrication is easy compare to 3-D flow focusing. The 3-D flow-focusing channel fabrication requires multilayer fabrication process. In a 2-D focusing channel, the sample fluid is focused horizontally within the center with the help of two sheaths. The increase in the flow rate of a sample and keeping the flow rate of a sheath constant causes broadening of the sample width and inversely by keeping the flow rate of a sample constant and increasing the sheath flow rate leads to a narrowing of a sample width. Basically, by changing the sheath flow rate to the sample flow rate ratio, the width of the sample fluid is varied. The same experimental study has done by Lee et al. (2006) on variation of sample width in a microchannel of width 250 µm and height 445 µm by varying flow rate ratio; the Fig. 3 shows the experimental result.

Fig. 3.
figure 3

Experimental images of 2-D flow focusing with different flow rate ratio (Q s and Q i are one side sheath flow rate and flow rate of a sample, respectively) in microchannel with aspect ratio of 1.78 (Lee et al. 2006)

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The analytical model of 2-D hydrodynamic flow focusing can be derived by assuming uniform, steady and laminar flow in a channel, also consider the fluid is Newtonian fluid. The pressure variation along the y and z directions (Fig. 2) is zero, and the sample and sheath fluid interface is assumed to be flat. Therefore, the Navier–Stokes equation for the considered assumptions can be written as follow

$$ \frac{{\partial^{2} u}}{{\partial y^{2} }} + \frac{{\partial^{2} u}}{{\partial z^{2} }} = \frac{1}{ \mu }\frac{\partial p}{\partial x} $$
(1)

where u is fluid velocity, and µ represents the dynamic viscosity of the fluid. To make the analytical model dimensionless, it is required to introduce dimensionless parameters such as \( \hat{u} = u/u_{0} \), ŷ = y/w, ẑ = z/h and \( \hat{x} = x/L \), where L, w, and h represent length, width, and height of a channel. Hence, the equation becomes

$$ \alpha^{2} \frac{{\partial^{2} \hat{u}}}{{\partial \hat{y}^{2} }} + \frac{{\partial^{2} \hat{u}}}{{\partial \hat{x}^{2} }} = P $$
(2)

where, \( P = \frac{{h^{2} }}{{u_{0} uL}}\frac{\partial p}{\partial x} \) and \( \alpha = h/w \).

As shown in the Fig. 2 there are two regions, region-I is representing sample fluid, and region-II represents sheath fluid. By applying above equation to these regions and solving those equations for û, hence û becomes

$$ \begin{aligned} \hat{u}_{1} & = \sum\limits_{{n = 0}}^{\infty } {\left[ {\frac{{ - 4P}}{{((2n - 1)\pi )^{3} }} + A\cos {\text{h}}\left( {\frac{{(2n - 1)\pi }}{\alpha }\hat{y}} \right) + B\sin {\text{h}}\left( {\frac{{(2n - 1)\pi }}{\alpha }\hat{y}} \right)} \right]} \\ & \quad \sin (2(2n - 1)\pi \hat{z}) \\ \end{aligned} $$
(3)

and

$$ \begin{aligned} \hat{u}_{2} & = \sum\limits_{{n = 0}}^{\infty } {\left[ {\frac{{ - 4P}}{{((2n - 1)\pi )^{3} }} + C\cos h\left( {\frac{{(2n - 1)\pi }}{\alpha }\hat{y}} \right) + D\sin {\text{h}}\left( {\frac{{(2n - 1)\pi }}{\alpha }\hat{y}} \right)} \right]} \\ & \quad \sin (2(2n - 1)\pi \hat{z}) \\ \end{aligned} $$
(4)

where A, B, C, and D can be find by applying boundary conditions. The sheath flow rate (Q) and sample flow rate (q) are then find by integrating corresponding velocity field over a cross section. The mathematical expressions for these flow rates are as given below

$$ q = 4 \times \sum\limits_{n = 1}^{\infty } {\left[ { \frac{ - 2Pb}{{((2n - 1)\pi )^{4} }} + \frac{{{\text{A}}\alpha }}{{((2n - 1)\pi )^{2} }} {\text{sin}}\,{\text{h}}\left( {\frac{(2n - 1)\pi }{2\alpha }b} \right)} \right]} $$
(5)
$$ Q = 4 \times \sum\limits_{n = 1}^{\infty } {\left[ {\frac{ - 2P(1 - b)}{{((2n - 1)\pi )^{4} }} + \frac{\alpha }{{((2n - 1)\pi )^{2} }} (C \times X + D \times Y )} \right]} $$
(6)

where, \( X = \left[ {{ \sin }\,{\text{h}}\left( {\frac{(2n - 1)\pi }{2\alpha }} \right) - { \sin }\,{\text{h}}\left( {\frac{(2n - 1)\pi b}{2\alpha }} \right)} \right]\) and \( Y = \left[ {{ \cos }\,{\text{h}}\left( {\frac{(2n - 1)\pi }{2\alpha }} \right) - { \cos }\,{\text{h}}\left( {\frac{(2n - 1)\pi b}{2\alpha }} \right)} \right] \).

Stiles et al. (2005) have demonstrated an alternate method to create a 2-D flow focusing by creating a relative change in a hydraulic flow resistance that has been created by maintaining the outlet at negative pressure and with a geometry which supports flow rate difference (Stiles et al. 2005). Another way to produce 2-D flow focusing is the use of air as a sheath flow. Producing a two-phase flow in a channel, air sheath from two side is use to focus sample in a channel (Huh et al. 2002). In a two-dimensional flow focusing, sample is focused horizontally not vertically. The sample is still in touch with the top wall and bottom wall of a channel which gives parabolic velocity profile in vertical direction. The parabolic profile means particles will experience different velocities at different location in a microchannel which may cause two or more particle in interrogation zone. The 2-D focusing is minimizing the problem rather eliminating it completely. Hence, it is important to focus the sample in all direction.

The Fig. 2b shows the schematic of a 3-D focusing, and the sample fluid is allow to focus at the center, where the sheath flow is forcing the sample from four directions. The flow rate ratio is modulated to get the required sample width like 2-D focusing. Shivhare et al. (2016) had done set of experiments by varying the flow rate ratio and validated it with simulation results. The graph shown in Fig. 4 shows the sample width variation with flow rate ratio.

Fig. 4.
figure 4

a Variation of sample width b (non-dimensional) with flow rate (f) in 2-D focusing channel, b Variation of sample width b (non-dimensional) with flow rate (f) in 3-D focusing channel. Reproduced from Shivhare et al. (2016), with permission of Springer

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There are different ways to obtain 3-D focusing in the channel. Howell et al. made a chevron-shaped groove at the top wall and at the bottom wall of a channel as shown in Fig. 5a. These grooves are helping to surround the sample with a sheath flow. Lee et al. (2009) had studied contraction and expansion microchannel in a series to create a 3-D focusing of a sample fluid. Basically, the fluid entering from expansion region to contraction region at the entrance creates a counter-rotating fluid flow field due to centrifugal forces. These secondary counter-rotating flow fields enclose sample fluid with a sheath flow. The schematic diagram of a contraction and expansion array is shown in Fig. 5b. The advantage of this 3-D focusing method is that it uses only one sheath flow and requires one layer of fabrication.

Fig. 5.
figure 5

Schematic of a chevron-shaped grooves 3-D focusing channel b contraction and expansion-based 3-D flow focusing. Reproduced from Lee et al. (2009) with permission of The Royal Society of Chemistry

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Frankowski et al. (2013) had demonstrated two different concepts of 3-D hydrodynamic flow focusing, and those are cascade focusing and spin focusing. These methods produce very stable and fully controlled focusing of a sample flow. The schematics of these techniques are shown below (Fig. 6).

Fig. 6.
figure 6

Schematic of a two cascade focusing b spin focusing (Frankowski et al. 2013)

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Frankowski et al. (2013) have discussed two stage cascade focusing method which uses only single inlet for the sheath fluid. In this approach, each stage has different size of a sheath channel and sample channel. The flow channel dimensions can be changed gradually by using high precision milling. The typical dimensions of a first stage sheath channel are 300 µm width and 1000 µm height, and for the second stage, width is 270 µm for a height of 1000 µm, and for the sample channel, first stage is of 125 µm × 125 µm and the corresponding second stage having a dimensions of 200 µm × 200 µm. In a cascaded channel, the particles get focused better than the single stage focusing mechanisms due to successive acceleration in a sample flow and sheath flow. The schematic of a cascaded focusing channel is shown in the Fig. 6a. In a spin focusing channel, the sample flow is focused perpendicular to the plane joining two sheath flows. Sheath flows which are flowing in two different parallel planes merge at the point where sample flow is getting injected into a channel. This particular geometry creates a vortex in the channel enclosing sample fluid at the center. The principle of this spin focusing is explained with the help of a schematic diagram in Fig. 7a and supported by experimental image of spin focusing channel in Fig. 7b.

Fig. 7
figure 7

a Schematic diagram of a spin focusing principle b experimental fluorescence image taken with a rhodamine dye 6G as a sample fluid (Frankowski et al. 2013)

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4 Sheath Less Particle Focusing

The sheath-based flow-focusing devices use complicated fluidic systems for precise control over the relative flow rates, and sometimes sheath fluid may dilute the sample. To overcome these limitations, sheath less focusing is emerged. Sheath less focusing is divided into two major types. First is field-based techniques in which particles are focused with the help of external forces. Second is flow-assisted methods in which particles are guided with the help of microstructures or microchannel.

  1. (A)

    Dielectrophoresis (DEP)

A dielectric particle experiences a force in a non-uniform electric field. Basically, this technique is used to sort the different microparticles in a sample. The experienced dielectrophoretic force by the particles is given by the following mathematical equation.

$$ F_{\text{DEP}} = 2\pi a^{3} \varepsilon_{m} {\text{Re}}\{ {\text{CM}}\} \nabla \left| {\bar{E}} \right|^{2} $$
(7)

Where the particle radius is a, a medium permittivity ε m , the applied electric field is Ē, and the real part of Clausius–Mossotti factor is Re{CM}. The sign of CM factor decides the force experienced by the particle. The CM factor depends on conductivity of the particle, medium, and applied electric field frequency. Based on these factors, the particle will move toward high electric field region or toward minimum, and based on this, it is named as positive DEP and negative DEP, respectively. The electric field is generated in a microchannel with the help of planar electrodes. Holmes et al. (2006) developed a DEP focusing channel by placing two electrodes onto the top and bottom of a microchannel. The Fig. 8 shows the schematic diagram and experimental image.

Fig. 8
figure 8

a Experimental image showing focusing of 6 µm particles by electrodes b schematics of a 3-D flow focusing with the help of a two pair of electrodes. Reprinted from Holmes et al. (2006), with permission from Elsevier

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  1. (B)

    Acoustic force

In acoustophoresis, the particles suspended in a medium experience a force which is induced by creating standing waves. Acoustic radiation force (Eq. 2) is mainly responsible for manipulation of particles. This acoustic radiation force transports the particle into pressure nodes or antinodes depending on acoustic contrast factor (Eq. 3) which depends on a difference in density and compressibility of particle and medium. When particles are dense, they possess positive contrast factor, which leads them into nodes and vice versa.

$$ F_{\text{rad}} = 4\varPi a^{ 3} \phi k_{y} E_{\text{ac}} { \sin }(2k_{y} y) $$
(8)

where,

$$ \phi = \tfrac{{\kappa_{o} - \kappa_{p} }}{{3\kappa_{o} }} + \tfrac{{\rho_{p} - \rho_{o} }}{{2\rho_{p} + \rho_{o} }} $$
(9)

And a is particle radius, \( \varPhi \) is the acoustic contrast factor, E ac is the acoustic energy density, k y is the wave number, distance from wall is y, \( \kappa_{p} \) and \( \kappa_{o} \) are the particle isothermal compressibility and the isothermal compressibility of a fluid, respectively, \( \rho_{o} \) and \( \rho_{p} \) are the densities of the fluid and the particles, respectively.

Jakobsson et al. (2015) demonstrated acoustic actuated fluorescence activated cell sorter in which the particles are focused with a single acoustic actuation and further downstream they are sorted by small acoustic bursts based on the fluorescence signal. The schematic of the working principle of this device is shown in Fig. 9. The prefocusing zone uses the acoustic waves with the frequency 4 and 6 MHz for particle focusing, and sorting zone uses 2 MHz acoustic burst (Jakobsson et al. 2015).

Fig. 9.
figure 9

Schematic of the working principle of AFACS. Reproduced from Jakobsson et al. (2015) with permission of The Royal Society of Chemistry

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Other than these two-field-based flow-focusing methods, the third is optical focusing. In optical focusing, the scattering forces are used to deviates the particles in a stream. The optical forces depend on a square of a particle diameter; hence while designing the device, consideration of size of the particle is very important. Also, it helps in selecting the optical sources and components. This sheathless flow focusing has some advantages as well as disadvantages. The sheathless flow focusing is very much particle size dependent. In many flow cytometry applications, the size dependence creates a problem in maintaining a stable flow focusing of the particles.

  1. (C)

    Inertial focusing

There are passive and active techniques for the particle focusing in a microchannel. One of the passive techniques is inertial focusing, where particles are focused at different equilibrium positions along the straight channel based on the channel aspect ratio at moderate Reynolds number flow. Equilibrium position of a particle is determined by the balance of shear gradient lift force and the wall lift force which counteracts each other in a channel. Basically, the shear gradient lift force comes in a picture because of parabolic velocity profile of a fluid in a channel which tries to force the particle away from the center of a channel, and the wall lift force acts away from the wall which is because of interaction between the wall and a particle. Though this particle focusing technique is popular in the recent time but it has some drawbacks such as it needs a long length of a channel to achieve equilibrium position for the particles, also the particle focusing is a function of a channel aspect ratio and at the same time we can have different equilibrium positions in a channel. These limitations of the inertial focusing can be eliminated by introducing secondary flow in a channel. The secondary flow exerts drag force on the particles. The secondary flow can be generated by incorporating geometrical changes in a channel. Zhao et al. (2017) demonstrated a high-throughput inertial focusing with arc-shaped grooves on the channel surface. The schematics of the arc-shaped groove array channel are as shown in Fig. 10.

Fig. 10
figure 10

a Schematic of a microchannel with curve grooves on the top of the channel and focusing of the particles b zoom in section of a microchannel with grooves with size parameters c CCD camera captured image of a channel (Zhao et al. 2017)

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The pressure gradient generated in a channel in the transverse direction because of groove structures tends to trap fluid which results in a secondary flow. This secondary flow forms vorticity in a channel cross section, forcing the fluid to move in a lateral direction along the vorticity rotation. The rotational direction movement of fluid exerts secondary flow drag force on a particle forcing them to move laterally. The particle simultaneously experiences the shear gradient lift force and the wall lift force. The equilibrium position of a particle is determined by the balance of all these forces. Here, the drag force is counteracting with inertial lift forces. This counteraction sets the particle in the equilibrium position at the upper corner of a channel. It has demonstrated in the same work that the strong secondary drag force can be generated by keeping approximately the same height of a curve-shaped groove and the channel. This method even shows the better focusing of the particles with different sizes and hence can be used effectively in a microflow cytometer.

5 Optical System

The second most important part of a flow cytometry is an optical system. The focused particles are then allowed to pass through an interrogation zone. The optical system provides a means by which particles are classified and detected. There are two main signals which help in analyzing the particles; they are scatter signal and fluorescence signal. The optical detection based on the fluorescence is used mostly because of its advantages such as high selectivity and sensitivity. The incident beam of light is focused into the observation window using different optical components. The particles after illumination of light produces scatter and florescence light signal. These light signals are then passed through the filters to the photodetectors to generate corresponding electrical signals. Traditionally, in a flow cytometer, bulky light sources such as mercury or xenon lamps and other bulky optical components are used, but to develop a miniaturized flow cytometer, it is very important to integrate optical components on-chip.

Waveguides are important to guide the light signals from a light source to the interrogation zone and from interrogation zone to the detectors. There are different ways to do this—either inserting optical fibers tip available in the market into the aligned groves in a microchannel chip (Wu et al. 2007) or fabricating optical waveguides with in a chip. When a laser beam hits the cell flowing in a microchannel, part of a light beam gets deflected, and this deflected light is called as scattering of light. There are mainly two types of scattering, forward scattering (FSC) and side scattering (SSC). The cell structure, size, membrane, and nucleus decide the scattering of the light signal (Adan et al. 2016). FSC is collected from front side of an exciting fiber at a small angle (0.5°–20°) (Guo et al. 2015) (Fig. 11). FSC signal tells about size of a particle or cell, whereas SSC signal which is collected at large angle (15°–150°) to the axis of excitation fiber gives information about cell/particle granularity, and internal complexity of a cell. To separate the particles from a heterogeneous mixture, FSC and SSC signals are very useful (Reggeti and Bienzle 2010).

Fig. 11.
figure 11

a Schematics of FSC and SSC signal from a cell. Reprinted by permission of the publisher Taylor & Francis Ltd., http://www.tandfonline.com (Adan et al. 2016), b schematic diagram showing different groves location corresponds to SSC, FSC, FL (fluorescence) and excitation light fiber in a microchip

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A fluorescence signal is very important in the flow cytometer. A compound which has fluorescence ability absorbs a light over a specific range of wavelengths and emits the light over another range of wavelengths. Basically, by absorbing light, in an atom, electrons go to excited state, and when they come back to original ground state after sometime, during this transition, they emits an energy. That energy is called as fluorescence. The fluorescence-based flow cytometry required staining of cells with fluorochromes, because numbers of intrinsically fluorescent compounds in a cell are less. The staining of cells is useful in many applications such as cell sorting, finding nucleic acid, and immune phenotyping.

To detect the light signals generated in the flow cytometry, photodetectors are used. The photodetector converts light signal to a voltage waveform. There are two photo detectors, photodiode (PD) and photomultiplier tubes (PMT). They are widely used based on the required sensitivity. PMT is more sensitive than PD; hence, to detect SSC signal, PMT is used, and for FSC detection, PD is used. To detect fluorescence signal, PMT is used with different optical filters.

6 Sorting Systems

As discussed earlier there are two types of flow cytometer, the one which incorporates sorting mechanisms and the second which do not have sorting mechanisms. Sorting mechanism in a flow cytometry gives additional advantage to the flow cytometry. There are different mechanisms to sort focused particles such as electrokinetic flow switching, hydrodynamic flow switching using on-chip or off-chip valves, etc. Sorting system is activated based on optical signal. Dittrich and Schwille have demonstrated electro-osmotic induced particle separation mechanisms. The proposed device is capable of deflecting particles based on the applied voltage polarity to the electrodes (Fig. 12) (Dittrich and Schwille 2003). Wang et al. (2005) demonstrated the sorting of the focused particles by switching optical forces (Wang et al. 2005). Jakobsson et al. (2015) demonstrated acoustic actuated fluorescence activated cell sorter in which particles are sorted with the help of acoustic radiation (Fig. 9).

Fig. 12.
figure 12

Electro-osmotic particle sorting by changing the applied voltage polarity. Reprinted with permission from Dittrich and Schwille (2003)

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7 Electronic System

Electronics and data analysis software are very important for flow cytometry applications. The electronics and analysis software convert optical signals into a meaningful data. Incorporating electronics in the flow cytometry increases the efficiency and functionality of the system and makes the system more autonomous. Analog circuit amplifiers are widely used to amplify the signals generated by the photodetectors, which increases the sensitivity of a device. Also, the signal generated by the devices should have less noise content. One can improve the SNR (signal to noise ratio) by using analog and digital filters. In many applications, real time analysis of data is very important. Hence, to process such real time data micro controller and microprocessors with digital signal processing techniques can be used. There is a lot of opportunity to make a very sophisticated flow cytometer by incorporating electronics in it.

8 Conclusion

Flow cytometer has a potential to analyze a large number of individual biological particles within a short span of time by utilizing mainly light scattering, and fluorescence. This device is capable of determining ample parameters related to cells or particles. The use of less volume of a sample and the high efficiency to separate rare particles or cells in the sample are some advantages of flow cytometry. By adopting different focusing approaches which are discussed in this chapter, they are able to meet the condition of single cell at a time in the interrogation region. Integration of optical and electronics components in the microflow cytometer is very important to miniaturize the system. In this chapter, we have discussed methods to incorporate these components which lead to the device miniaturization. The sensitivity and the sorting capabilities of the device can further be increased by incorporating more robust electronics on the chip. Because of all these developments, microflow cytometer holds the potential to secure a place in all cell analysis laboratories.