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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 262
TRACKING LIMB MOTION USING INERTIAL MEASUREMENT UNITS
(IMU)
Ms. R .Lakshmi 1, G. Pranavraj2, D. Prince Santhanaraj3 ,R.V. Ranjith Kumar4, A. Vijayan5
1Assistant Professor, Dept. of Information Technology,Valliammai Engineering College, Taminadu, India
2 Dept. of Information Technology,Valliammai Engineering College, Taminadu ,India
3 Dept. of Information Technology,Valliammai Engineering College, Taminadu ,India
4 Dept. of Information Technology,Valliammai Engineering College, Taminadu ,India
5 Dept. of Information Technology,Valliammai Engineering College, Taminadu ,India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The system is provided with highly accurate
human body motion capture and interactive three-
dimensional by combining low cost MEMS inertial
measurement units (IMU).It presents thedevelopmentofalow
cost wireless real-time inertiallimbtrackingsystemforvirtual
training. 9 Degrees of Freedom (DOF) Inertial Measurement
Units (IMU) is used for tracking and sensing motion of any
platform and is an ideal sensor system for motion control of
aerial autonomous systems like multi-rotors, modelairplanes,
helicopters etc., and other systems that require to control the
pitch, roll and yaw. The 9DOF Razor IMU incorporates three
sensors - an ITG-3200 (MEMS triple-axis gyro), ADXL345
(triple-axis accelerometer), and HMC5883L (triple-axis
magnetometer) - to give nine degrees of inertialmeasurement
.The IMU sensors are placed on user’s body and limbs
according to human skeletal action, and each sensorperforms
9 degrees of freedom (DOF) tracking at a high-speed update
rate. Secondly, the collected sensor data are transferred
through Microcontroller. The inner communication between
the Multipoint Control Unit (MCU) and the Inertial
Measurement Unit (IMU) is through Inter-Integrated Circuit
(I^2C). Finally The Inertial Measurement Units (IMU) sensor
values are serially connected with Mat lab based PC Program
for Motion detection.
Key Words: — IMU, MEMS, Degrees Of Freedom, inertial
limb tracking, Inter-Integrated circuit, IR Sensor, Multi
point Control Unit.
1.INTRODUCTION
The main idea is to accomplish thedevelopmentofa lowcost
wireless real-time inertial limb tracking system for virtual
training, which will make the Artificial limb to get the
movement as normal leg motion, therefore affected humans
can walk like a normal human and they can overcome the
feel that they are handicapped. The rehabilitation of the
motion in limb muscle plays the major role in Inertial
Measurement Units. The monitoring of any rehabilitation
program is desirable to ensure the correct execution of the
exercise by the patient and also to quantify the progress
toward the recovery of muscle strength, endurance, and
increase in the range of motion. Hip abduction/adduction,
hip and knee extension are among the most popular and
most effective rehabilitation exercises for improving lower-
limb muscle function and treating. Even when exercises are
performed under supervision, often clinicians and
physiotherapists use only visual, and thus subjective,
observations of the human’s movement.
The system is designed to provide highly accurate human
body motion capture and interactive three-dimensional by
combining low cost MEMS inertial measurement units
(IMUs).The 9DOF Razor IMU incorporates threesensors - an
ITG-3200 (MEMS triple-axis gyro), ADXL345 (triple-axis
accelerometer),andHMC5883L(triple-axismagnetometer)-
to give nine degrees of inertial measurement.Thegyroscope
and accelerometer provide information about accelerations
in all three directions, and rotations around each axis.
Gravity provides a background direction from the
accelerometer, so short term movements can be tracked.
However, in order to track the real position and orientation
in space, the six-axis sensor is not quite efficient because
small errors build up in each axis and over the time these
errors can add up to a drift in the absolute direction. We can
deal with this problem by adding one more. Absolute
directional sensor called 3-axis magnetometer. The extra
magnetic field information allows the sensing algorithms to
compensate for small drifts over Much longer periods of
time, so there is a very good chance of tracking the absolute
change in position and orientation much more accurately
and the location during complex movements can be
measured and tracked precisely.
1.2 Existing system
In the existing system, the usage of MEMS sensor will
provide only 3-axis propagation, which is comfortable for
human walking movements. The microcontroller used is
Arduino board which posses high power consumption.
Kinect sensor provides accuracy but it is more expensive.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 263
The RF transmitter will transmit the data which contains
noise that leads to inaccurate data calculation.
2. SYSTEM DESCRIPTION
2.1 IMU sensor:
The IMU is one of the units in electronics module which
collects angular velocity and linear acceleration data which
is sent to the main processor. The IMU actually contains two
separate sensors. The first sensor is the accelerometer triad
which generates three analog signals describing the
accelerations along each of its axes produced by, and acting
on the object. Due to threshold range system and physical
limitations, themostsignificantofthesesensedaccelerations
is caused by gravity. The second sensor is the angular rate
sensor triad. It also outputs three analog signals. These
signals describe the angular rate about each of the sensor
axes. Even though the IMU is not located at center of object
mass, the angular rate measurements are not affected by
linear or angular accelerations. The data from these sensors
are collected by the IMU 6811 microprocessor by a 12 bit
ADC board. The sensor information is then returned to the
main processor through RS422 serial communications
interface at a rate of about 200 Hz. The accelerometer triad,
and angular rate sensors within the IMU are mounted such
that their sensor coordinate axes are not aligned with those
of the objects. This is due to the fact that the two sensors in
the IMU are mounted in two different orientations in the
object, along with the fact that the axes of the IMU are not
aligned with the object axes.
Fig -1: IMU SENSOR
2.2 .ZIGBEE module:
The main applications with 802.15.4 are aimed at control
and monitoring applications where relatively low levels of
data throughput are needed. Remote, battery powered
sensors, low power consumption is a key requirement, also
sensors, lighting controls, security and many more
applications will play major role in new technologies.
North America is allowed to operate in one of the three
license free bands at 2.4 GHz, 915 MHz for and 868 MHz for
Europe. In this way the standard is able to operate around
the globe, there will be deviations in specifications for each
and every bands are slightly different. At 2.4 GHz there are a
total of sixteen different channels available, and the
maximum data rate is 250 kbps. For 915 MHz there are ten
channels and the standard supports a maximum data rate at
40 kbps, while at 868 MHz there is only one channel and this
can support data transfer at up to 20 kbps.
The modulation techniques also vary according to the band
which is in use. Direct sequence spread spectrum is used at
any cases. However for the 868 and 915 MHz bands are the
correct form modulation which is binary phase shift keying.
For the 2.4 GHz band, offset quadrature phase shift keying is
employed.
.
Fig -2: ZIGBEE MODULE
2.3 MICOCONTROLLER:
The ARM7 includesARM7TDMI,ARM7TDMI-S,ARM720T,
and ARM7EJ-S processors. The ARM7TDMI is the core
processor in industry’s most widely used 32-bit embedded
RISC microprocessor solution. ARM7 has Optimization of
cost and power-sensitive applications, the ARM7TDMI
solution provides the low power consumption, small size,
and high performance needed in portable, embedded
applications.
The ARM7TDMI core uses a three-stage pipeline which will
increase the flow of instructions to the processor. Therefore
providing the features to allows multiple simultaneous
operations to take place and continuous operation in the
processor and memory systems. The ARM7TDMI memory
interfacehasoptimumperformance potential andminimized
memory usage. Speed critical control signalsarepipelinedto
allow system control will function the exploit fast-burst
access modes supported by many memory technologies.
There is an option to make use either a single bidirectional
data bus or two separate unidirectional data input and
output buses. The ARM7TDMI can be configured to treat
stored words in either big-endian or little-endian format.
Performance, code density and operating states
The ARM instruction set allows a program to achieve
maximum performance with the minimum number of
instructions. The simpler thumb instruction set will offer
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 264
much increasedcodedensity reducingmemoryrequirement.
Code can switch between the ARM and thumb instruction
sets on any procedure call.
Fig -3: ZIGBEE MODULE
2.4 ARCHITECTURE DIAGRAM:
Fig -4: ARCHITECTURE DIAGRAM
In this transmitter section, the IMU sensor is
connected to the arm microcontroller the values that are
capture from the original leg is transferred to the ARM
microcontrollerthroughthe inter-integratedcircuit(I2C).I2C
is used for serial communication .The arm microcontroller
processes the captured values and transmit it to the level
analyzer through the UART .the arm microcontroller
transmits the asynchronous data through the UART Ports to
the level analyzer where the matlab coding takes place. the
level analyzer is used to analyze the values with the motion
captured data .hence after analyzingthesecaptureddata ,the
data is to be send to the zibgee .
In the reception module ,the values from the zigbee module
at the transmitter side is received to the another zigbee at
the receiver end.the values that are receivedaretransmitted
to the ARM microcontroller at the reciever end.this
microcontroller converts the analog signals todigital signals
to rn the mechanical setup. The last and thefinal stageisthat
the transmitter modle and the reception module are
integrated throug the two zigbees at the transmitter and the
reciever end.hence there is a wireless medium between
them.
2.5 BLOCK DIAGRAM:
TRANSMITTER SECTION:
This is the transmitter section which includes IMU sensor,
ARM LPC 2148, level analyzer, uart and zigbee transmitter.
Fig -4: TRANSMITTER SECTION
RECEIVER SECTION:
The receiver section will include zigbee receiver, ARM LPC
2148, PWM, and mechanical setup which ia fixed in the
artificial leg
Fig -4: RECEIVER SECTION
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 265
2.5. EXPERIMENT SETUP:
The system specification is a technical specification of
requirements for the software products. It is the first step in
the requirements analysis process and list the requirements
of a particular software system which includes functional,
performance and security requirements. The requirements
also provide usage scenarios from an user , and an
administrative perspective .The software requirements
specification purposes to provide a detailed overview of the
software project, its parameters and goals. This describes
the project target audience and its user interface, hardware
and software requirements.
One of the unique advantage of this project is that, it
establishes real time low cost wireless inertial tracking limb
motion .The limb tracking motion is done by the IMU sensor
which captures the motion of human leg which the sensor is
fixed with . The experimental setup consists of the
microcontroller, which is the central control of the
experiment. ARM LPC 2148 microcontroller is connected
with the sensors to get the input from the human beings in
the form of axis values and this sensor input pass through
the microcontroller and gets in to the disabled leg through
zigbee module .Level analysis is themainfunctionwhich will
analyze the range direction and axis rotation whicharefrom
the IMU sensor and activates the motion in the challenged
leg accordingly. This data is collected from IMU sensor and
then given as input to the Matlab for processing level
analysis.
2.6. EXPERIMENT RESULT :
On implementing this system the physically challenged
person can able to walk like normal human beings, hence
they come out of the feel that they are physically challenged.
IMU sensor and ARM LPC 2148 plays major role in motion
capture and processingaccuratevalueswhichimplement the
whole system to work.
CONCLUSIONS
On implementing this system the physically challenged
person can able to walk like normal human beings, hence
they come out of the feel that they are physically challenged.
IMU sensor and ARM LPC 2148 plays major role in motion
capture and processingaccuratevalueswhichimplement the
whole system to work.
REFERENCES
[1] Vincent Bonnet, Vladimir Joukov,Dana Kuli´c, Member, IE
EE, Philippe Fraisse, Member, IEEE,NacimRamdani, and
Gentiane Venture, Member, IEEE “MonitoringofHipandKnee
Joint Angles Using a Single Inertial Measurement Unit During
Lower Limb Rehabilitation”, IEEE Sensorsjournal,vol.16,no.
6, march 15, 2016,Paris, France.
[2] Vincent Bonnet and Gentiane Venture “Fast
DeterminationofthePlanar BodySegmentInertialParameters
Using Affordable Sensors”,IEEE Transactions on neural
systems and rehabilitation engineering, vol. 23, no. 4, July
2015,Italy.
[3] Dongyu Yuan, Xiaochuan Ma, Yu Liu, Zhigang Shang, and
Shefeng Yan, Senior Member, IEEE , “Statistical Modeling of
Random Walk Errors for Triaxle Rate Gyros”, IEEE
transactions on instrumentation and measurement, vol. 65,
no. 2, February 2016,China.
[4]Zheming Wu, Student Member, IEEE, Zhenguo Sun,
Member, IEEE, Wenzeng Zhang and Qiang Chen, “A Novel
Approach for Attitude Estimation Basedon MEMS Inertial
Sensors using Nonlinear
ComplementaryFilters”,IEEE ensorsJournal,2016, japan.
[5]Tri-Nhut Do, Ran Liu, Chau Yuen Senior Member, IEEE,
and U-Xuan Tan*, Member, IEEE, “Personal Dead Reckoning
using IMU mounted on
upper Torso and inverted Pendulum Model”, IEEE SENSORS
JOURNAL, 2016,Germany.
[6]Yang Zhang1, Yunfeng Fei2, Lin Xu1*, and Guangyi Sun1†
“micro-IMU-Based Motion Tracking System for Virtual
Training”1. Institute of Robotics and Automatic Information
System, Nankai University Tianjin Key Laboratory of
Intelligent Robotics, Tianjin, China
[7]F. H¨oflinger1, J. M ¨ uller2, M. T ¨ ork1, L.M. Reindl1, W.
Burgard2 1IMTEK, University of Freiburg, Germany, “A
Wireless Micro Inertial Measurement Unit
(IMU)”{fabian.hoeflinger, maximilian.toerk,
reindl}@imtek.uni-freiburg.de2 Department of Computer
Science, University of Freiburg, Germany, {muellerj,
burgard}@informatik.uni-freiburg.de.

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Tracking limb motion using inertial measurement units (IMU)

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 262 TRACKING LIMB MOTION USING INERTIAL MEASUREMENT UNITS (IMU) Ms. R .Lakshmi 1, G. Pranavraj2, D. Prince Santhanaraj3 ,R.V. Ranjith Kumar4, A. Vijayan5 1Assistant Professor, Dept. of Information Technology,Valliammai Engineering College, Taminadu, India 2 Dept. of Information Technology,Valliammai Engineering College, Taminadu ,India 3 Dept. of Information Technology,Valliammai Engineering College, Taminadu ,India 4 Dept. of Information Technology,Valliammai Engineering College, Taminadu ,India 5 Dept. of Information Technology,Valliammai Engineering College, Taminadu ,India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The system is provided with highly accurate human body motion capture and interactive three- dimensional by combining low cost MEMS inertial measurement units (IMU).It presents thedevelopmentofalow cost wireless real-time inertiallimbtrackingsystemforvirtual training. 9 Degrees of Freedom (DOF) Inertial Measurement Units (IMU) is used for tracking and sensing motion of any platform and is an ideal sensor system for motion control of aerial autonomous systems like multi-rotors, modelairplanes, helicopters etc., and other systems that require to control the pitch, roll and yaw. The 9DOF Razor IMU incorporates three sensors - an ITG-3200 (MEMS triple-axis gyro), ADXL345 (triple-axis accelerometer), and HMC5883L (triple-axis magnetometer) - to give nine degrees of inertialmeasurement .The IMU sensors are placed on user’s body and limbs according to human skeletal action, and each sensorperforms 9 degrees of freedom (DOF) tracking at a high-speed update rate. Secondly, the collected sensor data are transferred through Microcontroller. The inner communication between the Multipoint Control Unit (MCU) and the Inertial Measurement Unit (IMU) is through Inter-Integrated Circuit (I^2C). Finally The Inertial Measurement Units (IMU) sensor values are serially connected with Mat lab based PC Program for Motion detection. Key Words: — IMU, MEMS, Degrees Of Freedom, inertial limb tracking, Inter-Integrated circuit, IR Sensor, Multi point Control Unit. 1.INTRODUCTION The main idea is to accomplish thedevelopmentofa lowcost wireless real-time inertial limb tracking system for virtual training, which will make the Artificial limb to get the movement as normal leg motion, therefore affected humans can walk like a normal human and they can overcome the feel that they are handicapped. The rehabilitation of the motion in limb muscle plays the major role in Inertial Measurement Units. The monitoring of any rehabilitation program is desirable to ensure the correct execution of the exercise by the patient and also to quantify the progress toward the recovery of muscle strength, endurance, and increase in the range of motion. Hip abduction/adduction, hip and knee extension are among the most popular and most effective rehabilitation exercises for improving lower- limb muscle function and treating. Even when exercises are performed under supervision, often clinicians and physiotherapists use only visual, and thus subjective, observations of the human’s movement. The system is designed to provide highly accurate human body motion capture and interactive three-dimensional by combining low cost MEMS inertial measurement units (IMUs).The 9DOF Razor IMU incorporates threesensors - an ITG-3200 (MEMS triple-axis gyro), ADXL345 (triple-axis accelerometer),andHMC5883L(triple-axismagnetometer)- to give nine degrees of inertial measurement.Thegyroscope and accelerometer provide information about accelerations in all three directions, and rotations around each axis. Gravity provides a background direction from the accelerometer, so short term movements can be tracked. However, in order to track the real position and orientation in space, the six-axis sensor is not quite efficient because small errors build up in each axis and over the time these errors can add up to a drift in the absolute direction. We can deal with this problem by adding one more. Absolute directional sensor called 3-axis magnetometer. The extra magnetic field information allows the sensing algorithms to compensate for small drifts over Much longer periods of time, so there is a very good chance of tracking the absolute change in position and orientation much more accurately and the location during complex movements can be measured and tracked precisely. 1.2 Existing system In the existing system, the usage of MEMS sensor will provide only 3-axis propagation, which is comfortable for human walking movements. The microcontroller used is Arduino board which posses high power consumption. Kinect sensor provides accuracy but it is more expensive.
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 263 The RF transmitter will transmit the data which contains noise that leads to inaccurate data calculation. 2. SYSTEM DESCRIPTION 2.1 IMU sensor: The IMU is one of the units in electronics module which collects angular velocity and linear acceleration data which is sent to the main processor. The IMU actually contains two separate sensors. The first sensor is the accelerometer triad which generates three analog signals describing the accelerations along each of its axes produced by, and acting on the object. Due to threshold range system and physical limitations, themostsignificantofthesesensedaccelerations is caused by gravity. The second sensor is the angular rate sensor triad. It also outputs three analog signals. These signals describe the angular rate about each of the sensor axes. Even though the IMU is not located at center of object mass, the angular rate measurements are not affected by linear or angular accelerations. The data from these sensors are collected by the IMU 6811 microprocessor by a 12 bit ADC board. The sensor information is then returned to the main processor through RS422 serial communications interface at a rate of about 200 Hz. The accelerometer triad, and angular rate sensors within the IMU are mounted such that their sensor coordinate axes are not aligned with those of the objects. This is due to the fact that the two sensors in the IMU are mounted in two different orientations in the object, along with the fact that the axes of the IMU are not aligned with the object axes. Fig -1: IMU SENSOR 2.2 .ZIGBEE module: The main applications with 802.15.4 are aimed at control and monitoring applications where relatively low levels of data throughput are needed. Remote, battery powered sensors, low power consumption is a key requirement, also sensors, lighting controls, security and many more applications will play major role in new technologies. North America is allowed to operate in one of the three license free bands at 2.4 GHz, 915 MHz for and 868 MHz for Europe. In this way the standard is able to operate around the globe, there will be deviations in specifications for each and every bands are slightly different. At 2.4 GHz there are a total of sixteen different channels available, and the maximum data rate is 250 kbps. For 915 MHz there are ten channels and the standard supports a maximum data rate at 40 kbps, while at 868 MHz there is only one channel and this can support data transfer at up to 20 kbps. The modulation techniques also vary according to the band which is in use. Direct sequence spread spectrum is used at any cases. However for the 868 and 915 MHz bands are the correct form modulation which is binary phase shift keying. For the 2.4 GHz band, offset quadrature phase shift keying is employed. . Fig -2: ZIGBEE MODULE 2.3 MICOCONTROLLER: The ARM7 includesARM7TDMI,ARM7TDMI-S,ARM720T, and ARM7EJ-S processors. The ARM7TDMI is the core processor in industry’s most widely used 32-bit embedded RISC microprocessor solution. ARM7 has Optimization of cost and power-sensitive applications, the ARM7TDMI solution provides the low power consumption, small size, and high performance needed in portable, embedded applications. The ARM7TDMI core uses a three-stage pipeline which will increase the flow of instructions to the processor. Therefore providing the features to allows multiple simultaneous operations to take place and continuous operation in the processor and memory systems. The ARM7TDMI memory interfacehasoptimumperformance potential andminimized memory usage. Speed critical control signalsarepipelinedto allow system control will function the exploit fast-burst access modes supported by many memory technologies. There is an option to make use either a single bidirectional data bus or two separate unidirectional data input and output buses. The ARM7TDMI can be configured to treat stored words in either big-endian or little-endian format. Performance, code density and operating states The ARM instruction set allows a program to achieve maximum performance with the minimum number of instructions. The simpler thumb instruction set will offer
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 264 much increasedcodedensity reducingmemoryrequirement. Code can switch between the ARM and thumb instruction sets on any procedure call. Fig -3: ZIGBEE MODULE 2.4 ARCHITECTURE DIAGRAM: Fig -4: ARCHITECTURE DIAGRAM In this transmitter section, the IMU sensor is connected to the arm microcontroller the values that are capture from the original leg is transferred to the ARM microcontrollerthroughthe inter-integratedcircuit(I2C).I2C is used for serial communication .The arm microcontroller processes the captured values and transmit it to the level analyzer through the UART .the arm microcontroller transmits the asynchronous data through the UART Ports to the level analyzer where the matlab coding takes place. the level analyzer is used to analyze the values with the motion captured data .hence after analyzingthesecaptureddata ,the data is to be send to the zibgee . In the reception module ,the values from the zigbee module at the transmitter side is received to the another zigbee at the receiver end.the values that are receivedaretransmitted to the ARM microcontroller at the reciever end.this microcontroller converts the analog signals todigital signals to rn the mechanical setup. The last and thefinal stageisthat the transmitter modle and the reception module are integrated throug the two zigbees at the transmitter and the reciever end.hence there is a wireless medium between them. 2.5 BLOCK DIAGRAM: TRANSMITTER SECTION: This is the transmitter section which includes IMU sensor, ARM LPC 2148, level analyzer, uart and zigbee transmitter. Fig -4: TRANSMITTER SECTION RECEIVER SECTION: The receiver section will include zigbee receiver, ARM LPC 2148, PWM, and mechanical setup which ia fixed in the artificial leg Fig -4: RECEIVER SECTION
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 265 2.5. EXPERIMENT SETUP: The system specification is a technical specification of requirements for the software products. It is the first step in the requirements analysis process and list the requirements of a particular software system which includes functional, performance and security requirements. The requirements also provide usage scenarios from an user , and an administrative perspective .The software requirements specification purposes to provide a detailed overview of the software project, its parameters and goals. This describes the project target audience and its user interface, hardware and software requirements. One of the unique advantage of this project is that, it establishes real time low cost wireless inertial tracking limb motion .The limb tracking motion is done by the IMU sensor which captures the motion of human leg which the sensor is fixed with . The experimental setup consists of the microcontroller, which is the central control of the experiment. ARM LPC 2148 microcontroller is connected with the sensors to get the input from the human beings in the form of axis values and this sensor input pass through the microcontroller and gets in to the disabled leg through zigbee module .Level analysis is themainfunctionwhich will analyze the range direction and axis rotation whicharefrom the IMU sensor and activates the motion in the challenged leg accordingly. This data is collected from IMU sensor and then given as input to the Matlab for processing level analysis. 2.6. EXPERIMENT RESULT : On implementing this system the physically challenged person can able to walk like normal human beings, hence they come out of the feel that they are physically challenged. IMU sensor and ARM LPC 2148 plays major role in motion capture and processingaccuratevalueswhichimplement the whole system to work. CONCLUSIONS On implementing this system the physically challenged person can able to walk like normal human beings, hence they come out of the feel that they are physically challenged. IMU sensor and ARM LPC 2148 plays major role in motion capture and processingaccuratevalueswhichimplement the whole system to work. REFERENCES [1] Vincent Bonnet, Vladimir Joukov,Dana Kuli´c, Member, IE EE, Philippe Fraisse, Member, IEEE,NacimRamdani, and Gentiane Venture, Member, IEEE “MonitoringofHipandKnee Joint Angles Using a Single Inertial Measurement Unit During Lower Limb Rehabilitation”, IEEE Sensorsjournal,vol.16,no. 6, march 15, 2016,Paris, France. [2] Vincent Bonnet and Gentiane Venture “Fast DeterminationofthePlanar BodySegmentInertialParameters Using Affordable Sensors”,IEEE Transactions on neural systems and rehabilitation engineering, vol. 23, no. 4, July 2015,Italy. [3] Dongyu Yuan, Xiaochuan Ma, Yu Liu, Zhigang Shang, and Shefeng Yan, Senior Member, IEEE , “Statistical Modeling of Random Walk Errors for Triaxle Rate Gyros”, IEEE transactions on instrumentation and measurement, vol. 65, no. 2, February 2016,China. [4]Zheming Wu, Student Member, IEEE, Zhenguo Sun, Member, IEEE, Wenzeng Zhang and Qiang Chen, “A Novel Approach for Attitude Estimation Basedon MEMS Inertial Sensors using Nonlinear ComplementaryFilters”,IEEE ensorsJournal,2016, japan. [5]Tri-Nhut Do, Ran Liu, Chau Yuen Senior Member, IEEE, and U-Xuan Tan*, Member, IEEE, “Personal Dead Reckoning using IMU mounted on upper Torso and inverted Pendulum Model”, IEEE SENSORS JOURNAL, 2016,Germany. [6]Yang Zhang1, Yunfeng Fei2, Lin Xu1*, and Guangyi Sun1† “micro-IMU-Based Motion Tracking System for Virtual Training”1. Institute of Robotics and Automatic Information System, Nankai University Tianjin Key Laboratory of Intelligent Robotics, Tianjin, China [7]F. H¨oflinger1, J. M ¨ uller2, M. T ¨ ork1, L.M. Reindl1, W. Burgard2 1IMTEK, University of Freiburg, Germany, “A Wireless Micro Inertial Measurement Unit (IMU)”{fabian.hoeflinger, maximilian.toerk, reindl}@imtek.uni-freiburg.de2 Department of Computer Science, University of Freiburg, Germany, {muellerj, burgard}@informatik.uni-freiburg.de.