Abstract Medical mechatronics explains innovative solutions for exploiting mechatronics in the medical instruments by optimizing the available conventional instruments and also creating new innovative, intelligent and accurate instrument. This paper gives a brief introduction about sensing and actuating technologies, automation and control systems used in the medical field. The paper also discuss about the principles and methods of processing and controlling mechanism in mechatronics system. In controlling, the artificial neural networks (ANNs) and fuzzy expert systems are commonly used one. ANNs are biologically inspired computer programs designed to simulate the way in which the human brain processes information. Whereas fuzzy expert system uses predefine membership functions and fuzzy inference rules to map numeric data into linguistic variable terms and to make fuzzy reasoning work

Priya K

Sivabalakrishnan R

Yasodharan R

CiteSeerX

 
Yasodharan. R et al, International Journal of Pharmaceutical Sciences and Business Management, 
                                                    Vol.2 Issue. 11, November- 2014, pg. 52-59  
                 ISSN: 2310-6913 
 
© 2014, IJPSBM All Rights Reserved, www.ijpsbm.com                                                                52 
 
 
STUDY OF MEDICAL MECHATRONICS  
Yasodharan. R 
1
, Sivabalakrishnan. R
2
, Priya. K
3 
 
1Assistant Professor, SNS College of Technology, Coimbatore, yaso.snstech@gmail.com 
2Assistant Professor, SNS College of Technology, Coimbatore, sivaeinfo@gmail.com 
3Assistant Professor, SNS College of Technology, Coimbatore, priyakrishnanjune10@gmail.com 
 
Abstract 
 
Medical mechatronics explains innovative solutions for exploiting mechatronics in the medical instruments 
by optimizing the available conventional instruments and also creating new innovative, intelligent and 
accurate instrument. This paper gives a brief introduction about sensing and actuating technologies, 
automation and control systems used in the medical field. The paper also discuss about the principles and 
methods of processing and controlling mechanism in mechatronics system. In controlling, the artificial neural 
networks (ANNs) and fuzzy expert systems are commonly used one. ANNs are biologically inspired 
computer programs designed to simulate the way in which the human brain processes information. Whereas 
fuzzy expert system uses predefine membership functions and fuzzy inference rules to map numeric data into 
linguistic variable terms and to make fuzzy reasoning work. 
Keywords: Medical Mechatronics, Sensors, Actuators, Artificial neural network, Embedded system  
 
 
1. Introduction to Mechatronics: 
 
―Mechatronics‖ is a term coined by the Japanese to describe the integration of mechanical 
and electronic engineering. The concept may seem to be anything but new, since we can all look 
around us and see a myriad of products that utilize both mechanical and electronic disciplines. 
Mechatronics, however, specifically refers to a multidiscipline, integrated approach to product and 
manufacturing system design. As shown in Figure.1, mechatronics is the combination of mechanical, 
electrical, electronic, computer and various other systems. It represents the next generation of 
machines, robots, and smart mechanisms necessary for carrying out work in a variety of 
environments.  
Early medicine emphasized external examination of the patient. Later, breakthroughs such as 
x-ray permitted internal examination from the outside. Electronic and photonic advancements have 
enhanced these diagnostic techniques, but new devices and extreme miniaturization now permit 
examination, sensing, and monitoring from inside the patient. 
 
Yasodharan. R et al, International Journal of Pharmaceutical Sciences and Business Management, 
                                                    Vol.2 Issue. 11, November- 2014, pg. 52-59  
                 ISSN: 2310-6913 
 
© 2013, IJPSBM All Rights Reserved, www.ijpsbm.com                                                                        53 
 
 
Figure.1 Mechatronics system 
Concurrent breakthroughs in molecular biology and better understanding of coding and functions of 
DNA, is building up knowledge that will make diagnostics even more powerful and allow 
deployment of preventive and interceptive medical techniques much earlier for greater success. 
Molecular based medicine is the ultimate frontier. 
2. Sensing and Actuating Technology: 
 
A sensor is a device which is used to sense or measure a input quantity and converts it into 
an signal, which can be read by an observer or by an instrument. They are used to detect the 
physical, chemical, and biological signals, which can be measured & recorded. The various Physical 
properties that can be sensed include temperature, pressure, vibration, sound level, light intensity, 
load or weight, flow rate of gases and liquids, amplitude of magnetic and electronic fields, and 
concentrations of many substances in gaseous, liquid, or solid form.  
With advances in micro machinery and easy-to-use microcontroller platforms, the uses of 
sensors have expanded beyond the more traditional fields of temperature, pressure or flow 
measurement for example into MARG sensors, Manufacturing and Machinery, Airplanes and 
Aerospace, Cars, Medicine and Robotics. 
Sensors have played an important role in many industries, providing the mechanical ―vision‖ used 
for counting, sorting, reading, and robotic guidance and also used to detect specific chemical 
pressures and fluid levels. Tactile sensors, typically piezoelectric materials, generate voltage when 
 
Yasodharan. R et al, International Journal of Pharmaceutical Sciences and Business Management, 
                                                    Vol.2 Issue. 11, November- 2014, pg. 52-59  
                 ISSN: 2310-6913 
 
© 2013, IJPSBM All Rights Reserved, www.ijpsbm.com                                                                        54 
 
touched, squeezed, or bent, or when their temperature is changed. In the short term, sensors used in 
medical applications will emit a signal that can be read at the point of determination or transferred by 
wire or wireless transmission to remote locations. Advances in microprocessor technologies have 
created a smart sensor that unites sensing capability and data processing in a single integrated circuit 
chip. The next step is combining sensing and processing with an actuator, such as 
microelectromechanical systems. One of the major health care trends affecting mechatronics 
technology is miniaturization. The use of micro sensors and micro actuators is driving development 
of tiny mechatronics designs for 
2.1 Instruments.  
Tiny smart motion systems and all-in-one microstages move optics in hand-held scientific 
instruments for flow cytometry, DNA identification, IVD, pathogen detection, DNA sequencing and 
more. They enable smaller, field-portable systems and faster, lower-cost tests. 
2.2 Endoscopic surgery. Steer a beam in an endoscopic laser scalpel, focus a lens in an in vivo 
camera, manipulate a scraper, collect a sample or dispense a liquid. Small enough to fit inside the 
endoscope head, our mechatronics systems improve accuracy and eliminate the need for a cable 
control system. 
2.3 Electrophysiology. Motorized microdrive arrays enable precision electrode positioning. 
2.4 Medical imaging. Small, precise modules for lens control and laser tuning enable systems for 
point-of care-diagnostics, home monitoring and telemedicine, real-time automated data collection 
and augmented vision eyewear. 
2.5 Implantable devices. Adjust implanted devices in situ for drug delivery, orthopedics (bone 
growth and spine straightening), audiology, neurology, pain management, sleep apnea treatment and 
more. The implanted devices can be non-magnetic and MRI-safe. 
2.6 Robotic surgical devices. Everything from robotic grippers and retractors to miniature mobile 
robots for minimally invasive surgery. 
 
 
 
 
 
Yasodharan. R et al, International Journal of Pharmaceutical Sciences and Business Management, 
                                                    Vol.2 Issue. 11, November- 2014, pg. 52-59  
                 ISSN: 2310-6913 
 
© 2013, IJPSBM All Rights Reserved, www.ijpsbm.com                                                                        55 
 
3. Automation and control systems 
 
Automation or automatic control is the utilization of several control systems for operating 
systems such as machinery, processes in factories, boilers and heat treating ovens, switching in 
telephone networks, steering and stabilization of ships, aircraft and other applications with minimal 
or reduced human intervention. On-off control is widely used in industrial applications. An example 
is the thermostats used on household appliances. Although technically it is a form of automation, its 
capabilities are primitive. (Old style HVAC systems used crude thermostats that were limited to on-
off control, but some modern systems use more sophisticated sensors and digital controllers for 
variable speed fans or controlling other functions.) 
Sequence control, in which a programmed sequence of discrete operations is performed, 
often based on system logic that involves system states. An elevator control system is an example of 
sequence control. The advanced type of automation that revolutionized manufacturing, aircraft, 
communications and other industries, is feedback control, which is usually continuous and involves 
taking measurements using a sensor and making calculated adjustments to keep the measured 
variable within a set range 
All the elements constituting the measurement and control of a single variable are called a 
control loop. Control that uses a measured signal, feeds the signal back and compares it to a set 
point, calculates and sends a return signal to make a correction, is called closed loop control. If the 
controller does not incorporate feedback to make a correction then it is open loop. An operator 
monitoring signals from various sensors and manually making corrections either physically, such as 
turning the handle on a valve, or remotely, such as using a dial on a control panel, is performing 
open loop control. Timers and sequence controllers using logic, such as those on an elevator, are also 
open loop. 
Feedback control is accomplished with a controller. To function properly, a controller must 
provide correction in a manner that maintains stability. The theoretical basis of feedback control is 
control theory, which also covers servomechanisms, which are often part of an automated system. 
Maintaining stability is a principal objective of control theory. Stability means that the system should 
not oscillate excessively around the set point or get into a situation where it shuts down or runs 
away.As an example of feedback control, consider a steam coil air heater in which a temperature 
sensor measures the temperature of the heated air, which is the measured variable. This signal is 
 
Yasodharan. R et al, International Journal of Pharmaceutical Sciences and Business Management, 
                                                    Vol.2 Issue. 11, November- 2014, pg. 52-59  
                 ISSN: 2310-6913 
 
© 2013, IJPSBM All Rights Reserved, www.ijpsbm.com                                                                        56 
 
constantly "fed back" to the controller, which compares it to the desired setting (set point). The 
controller calculates the difference (error), then calculates a correction and sends the correction 
signal to adjust the air pressure to a diaphragm that moves a positioner on the steam valve, opening 
or closing it by the calculated amount. 
4. Processing and controlling mechanism 
Embedded system has faced a vast growth in medical field nowadays. The efficacy of 
embedded system in medical Mechatronics provides a various benefit like small devices 
capable of capturing patient data and making control decisions in treatment for the patients 
with the reduction of size, low power consumption, increase in processing power, may help 
in providing patients with better treatments. A case study about embedded system in medical 
field depicts in controlling the speed of a centrifugal pump of a heart-lung machine as shown 
in Figure.2. This application requires the real time patient data from various sensors to 
analysis the condition of the patient and able to make control on medical device for better 
functioning of artificial organs. The fuzzy controller are used in this application as a closed 
loop control to increase flexibility and easy computation in analysis the patient data. 
 
Figure.2 Heart lung machine  
 
4.1 Artificial Neural Networks 
The neural structure of the brain is taken as the model to create the Artificial Neural 
Networks. In general the brain basically learns from our day to day experience. It is practical 
 
Yasodharan. R et al, International Journal of Pharmaceutical Sciences and Business Management, 
                                                    Vol.2 Issue. 11, November- 2014, pg. 52-59  
                 ISSN: 2310-6913 
 
© 2013, IJPSBM All Rights Reserved, www.ijpsbm.com                                                                        57 
 
proof that some problems that are beyond the scope of current computers are indeed 
solvable by small energy efficient packages. Artificial Neural Network is a brain modelling 
which promises a less technical way to develop machine solutions. This new approach to 
computing also provides a more graceful degradation during system overload than its more 
traditional counterparts.  
 
 
Fig.3 Artificial Intelligence Neural Network Nodes 
 
The basic unit of neural networks are the artificial neurons, simulate the four basic functions 
of natural neurons. Neural Network (NN) is a system composed of several artificial neurons 
(see Figure.3) and weighted links binding them. This set of neurons that process 
information, is organized into interconnected layers along chosen patterns. Every neuron in 
its layer, receives some type of stimuli as input, processes it and sends through its related 
links an output to neighbouring neurons. In the field of Artificial Intelligence, NN models 
are also called Artificial Neural Network (ANN) in contrast to their biological counterparts 
that strongly inspired researchers in the beginning. 
These biologically inspired methods of computing are thought to be the next major 
advancement in the computing industry. Even simple animal brains are capable of functions 
that are currently impossible for computers. Computers do rate things well, like keeping 
ledgers or performing complex math. But computers have trouble recognizing even simple 
patterns much less generalizing those patterns of the past into actions of the future.  
Now, advances in biological research promise an initial understanding of the natural 
thinking mechanism. This research shows that brains store information as patterns. Some of 
 
Yasodharan. R et al, International Journal of Pharmaceutical Sciences and Business Management, 
                                                    Vol.2 Issue. 11, November- 2014, pg. 52-59  
                 ISSN: 2310-6913 
 
© 2013, IJPSBM All Rights Reserved, www.ijpsbm.com                                                                        58 
 
these patterns are very complicated and allow us the ability to recognize individual faces 
from many different angles. This process of storing information as patterns, utilizing those 
patterns, and then solving problems encompasses a new field in computing. This field, as 
mentioned before, does not utilize traditional programming but involves the creation of 
massively parallel networks and the training of those networks to solve specific problems. 
This field also utilizes words very different from traditional computing, words like behave, 
react, self-organize, learn, generalize, and forget.  
 
 
Figure.4 Structure of artificial neural networks 
 
Basically, all artificial neural networks have a similar structure or topology as shown in 
Figure.4. In that structure some of the neurons interfaces to the real world to receive its 
inputs. Other neurons provide the real world with the network's outputs. This output might 
be the particular character that the network thinks that it has scanned or the particular image 
it thinks is being viewed. All the rest of the neurons are hidden from view.  
But a neural network is more than a bunch of neurons. Some early researchers tried to 
simply connect neurons in a random manner, without much success. Now, it is known that 
even the brains of snails are structured devices. One of the easiest ways to design a structure 
is to create layers of elements. It is the grouping of these neurons into layers, the 
connections between these layers, and the summation and transfer functions that comprises a 
functioning neural network. The general terms used to describe these characteristics are 
common to all networks. 
 
Yasodharan. R et al, International Journal of Pharmaceutical Sciences and Business Management, 
                                                    Vol.2 Issue. 11, November- 2014, pg. 52-59  
                 ISSN: 2310-6913 
 
© 2013, IJPSBM All Rights Reserved, www.ijpsbm.com                                                                        59 
 
Although there are useful networks which contain only one layer, or even one element, most 
applications require networks that contain at least the three normal types of layers - input, 
hidden, and output. The layer of input neurons receive the data either from input files or 
directly from electronic sensors in real-time applications. The output layer sends information 
directly to the outside world, to a secondary computer process, or to other devices such as a 
mechanical control system. Between these two layers can be many hidden layers. These 
internal layers contain many of the neurons in various interconnected structures. The inputs 
and outputs of each of these hidden neurons simply go to other neurons.  
4.2 Fuzzy control system 
A fuzzy control system is a control system based on fuzzy logic—a mathematical 
system that analyses analog input values in terms of logical variables that take on continuous 
values between 0 and 1, in contrast to classical or digital logic, which operates on discrete 
values of either 1 or 0 (true or false, respectively). 
Fuzzy logic is widely used in a machine control. The term "fuzzy" refers to the fact that the 
logic involved can deal with concepts that cannot be expressed as the "true" or "false" but 
rather as "partially true". Although alternative approaches such as genetic algorithms and 
neural networks can perform just as well as fuzzy logic in many cases, fuzzy logic has the 
advantage that the solution to the problem can be cast in terms that human operators can 
understand, so that their experience can be used in the design of the controller. This makes it 
easier to mechanize tasks that are already successfully performed by humans. 
 
5. Conclusion  
                    In this paper we discuss about the brief introduction about the mechatronics 
system, their components. Sensing and actuating techniques were studied detailed. Then 
software techniques. In general Medical mechatronics is a branch of mechatronics in which 
electronic instruments and equipment are used for such medical applications as diagnosis, 
therapy, research, anaesthesia control, cardiac control, and surgery.  
 
 
 References 
 
[1] Lee, M.Y., " Mechatronics in Medical Modality Development ", IEEE International 
Conference on Robotics and Automation, Vol. 3, 2002, pp. 2950 - 2955. 
[2] Mendoza G A, Baumgartner B, Schreiber U, Krane M, Knoll A, Bauernschmitt R. 
Automedic: Fuzzy control development platform for a mobile heart-lung machine. Volume 
25/7 of IFMBE Proceedings. 2009; 685–688. 
[3] Schreiber U, Eichhorn S, Mendoza A, Baumgartner B, Bauernschmitt R, Lange R, Knoll 
A, Krane M. A new fuzzy controlled extracorporeal circulation system. first results of an in-
vitro investigation. CINC 2009; 36:497–500. 


STUDY OF MEDICAL MECHATRONICS

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