three dimensional surface reconstruction of...
TRANSCRIPT
i
THREE DIMENSIONAL SURFACE RECONSTRUCTION OF
LOWER LIMB PROSTHETIC MODEL USING INFRARED SENSOR ARRAY
SITI ASMAH BTE DAUD
A thesis submitted in fulfillment of the
requirements for the award of the degree of
Doctor of Philosophy (Biomedical Engineering)
Faculty of Biosciences and Medical Engineering
Universiti Teknologi Malaysia
JANUARY 2016
iii
To my beloved husband and family
iv
ACKNOWLEDGEMENT In preparing the thesis, I was in contact with many lecturers and friends.
They have contributed in their own way towards my understanding and thoughts of
the whole research project. In particular, I wish to express my sincere appreciation
to my supervisor, Dr. Nasrul Humaimi bin Mahmood, for his encouragement,
guidance, critics, idea generations and friendship. I am also very thankful to my co-
supervisor Dr. Leow Pei Ling, Assoc. Prof. Dr. Azli bin Yahya, and Dr. Fauzan
Khairi bin Che Harun for their guidance, advices and motivation. Without their
continuous support and interest, the thesis would not have been the same as
presented here.
I was also indebted to my entire lab mates who have helped me by giving
brilliant ideas throughout the completion of the project. My sincere appreciation also
extends to all those who have provided assistance at various occasions. Their views
and tips are useful indeed.
A special thanks to my husband, father and mother for their constant support
throughout the years, specifically for supporting me in accomplishing the project,
without their help the project would not be complete.
v
ABSTRACT
This thesis addresses the development of a shape detector device using
infrared sensor to reconstruct a three-dimensional image of an object. The three-
dimension image is produced based on the object surface using image processing
technique. Conventionally, infrared sensors are used for detection of an obstacle and
distance measurement to avoid collisions. However, it is not common to use infrared
sensors to measure the size of an object. Hence, this research aims to investigate the
feasibility of infrared sensors in measuring the object dimension for three-dimension
image reconstruction. Experiments were executed to study the minimum distance
range utilising GP2D120 infrared sensor. From the experiment, the distance between
the sensor and object surface should be more than 5 cm. The scanning device
consists of the infrared sensor array was placed in a black box with the object in the
center. The scanning process required the object to turn 360 ° clockwise in an xy
plane and the resolution for z-axis is 2 mm, in order to obtain data for the image
reconstruction. Reference polygon shape models with various dimensions were used
as scanning objects in the experiments. The device scans object diameter every 2
mm in thickness, 100 mm in height, and the total time required to collect data for
each layer is 60 seconds. The reconstructed object accuracy is above 80 % based on
the comparison between a solid and printed model dimension. Four different lower
limb prosthetic models with different shapes were used as the object in the scanning
experiments. The experimental findings show that the prosthetic shapes
reconstructed with an average accuracy of 97 %. This system shows good
reproducibility where the collected data using the infrared sensor device need further
improvement so that it can be applied in medical field for orthotics and prosthetics
purpose.
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ABSTRAK
Kajian ini bertujuan bagi mencipta alat pengesan bentuk menggunakan sensor
inframerah bagi melakar semula tiga dimensi objek berkenaan. Permukaan tiga
dimensi objek ini dihasilkan menggunakan teknik pembinaan semula imej.
Kebiasaannya, sensor inframerah digunakan bagi mengesan halangan dan jarak bagi
mengelakkan pelanggaran. Walau bagaimanapun, ianya jarang digunakan untuk
mengukur saiz sesuatu objek. Justeru itu, kajian ini dilakukan bagi mengenal pasti
kebolehupayaan sensor inframerah untuk mengukur saiz objek bagi tujuan
pembinaan semula imej tiga dimensi. Eksperimen dijalankan bagi menentukan jarak
terdekat dengan menggunakan sensor inframerah GP2D120. Hasil kajian
menunjukkan bahawa, jarak di antara sensor inframerah dan objek haruslah melebihi
5 cm. Alat pengesanan ini terdiri daripada beberapa sensor inframerah yang
diletakkan di dalam kotak hitam bersama dengan objek yang berada di tengah kotak.
Proses pengesanan memerlukan objek untuk berpusing sebanyak 360 ° mengikut
arah jam di paksi xy dan berketepatan sebanyak 2 mm bagi tujuan pembinaan semula
imej. Beberapa bentuk poligon yang terdiri daripada pelbagai saiz digunakan di
dalam eksperimen ini. Alat ini mengesan objek bagi setiap 2 mm ketebalan, 100 mm
tinggi, dan jumlah masa yang diperlukan adalah sebanyak 60 saat bagi setiap lapisan.
Ketepatan pembinaan semula objek adalah melebihi 80 % berdasarkan kepada
perbezaan di antara rujukan dan data yang diperolehi. Empat bentuk model prostetik
dengan bentuk yang berbeza turut digunakan di dalam ujikaji ini. Hasil kajian
menunjukkan purata ketepatan imej adalah 97 %. Alat ini menunjukkan keputusan
yang baik dalam pengambilan data menggunakan sensor inframerah dan
penambahbaikan perlu dilakukan supaya ia boleh digunakan secara meluas didalam
bidang perubatan orthotik dan prostetik.
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TABLE OF CONTENTS
CHAPTER TITLE PAGE
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENT iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENTS vii
LIST OF TABLES xi
LIST OF FIGURES xiii
LIST OF ABBREVIATION xvii
LIST OF SYMBOLS xix
LIST OF APPENDICES xxi
1 INTRODUCTION 1
1.1 Background 1
1.2 Problem Statement 3
1.3 Research Objectives 4
1.4 Scope of the Thesis 5
1.5 Significant Findings 6
1.6 Thesis Overview 6
2 BASIC CONCEPTS AND THEORIES 8
2.1 Introduction 8
2.2 Background of the Prosthetic Limb 9
viii
2.3 Current Techniques for Prosthetic Lower Limb
Fabrication 12
2.3.1 Medical Imaging 12
2.3.2 Laser Scanning 13
2.3.3 3D Digital Model 13
2.3.4 Camera 14
2.3.5 Sensors 16
2.3.6 The Accuracy of Medical Imaging Devices 16
2.4 Socket Development Process 17
2.4.1 Computer-aided Design and Computer-aided
Manufacturing (CAD/CAM) 18
2.4.2 Finite Element Analysis (FEA) 18
2.5 Image Reconstruction Method for 3D Image 19
2.5.1 Phong Illumination Theory 21
2.5.2 Analog-to-Digital Converter (ADC) 22
2.5.3 Power Interpolation Function 22
2.6 Research in Infrared Sensor Applications 23
2.7 Other Sensors used with Infrared Device 27
2.7.1 Ultrasound (US) 27
2.7.2 3D Sensor 28
2.7.3 Laser Diode 29
2.8 Comparison of The IR Sensor With Other Method 29
2.9 Summary 30
3 CONCEPTUAL DESIGN OF SHAPE DETECTOR
USING IR SENSOR ARRAY 32
3.1 Introduction 32
3.2 Infrared Sensor 34
3.3 Working Principle of The Circuit Control Board 37
3.4 Sensor Array Model 40
3.5 Device Hardware 45
ix
3.6 Shapes Detector Device Microcontroller
3.6.1 Arduino Microcontroller Algorithm
Development
3.6.2 Flow Chart
46
46
48
3.7 Summary 49
4 SHAPE DETECTOR DEVICE TESTED WITH
VARIOUS SHAPES OF A POLYGON MODEL 50
4.1 Introduction 50
4.2 Shapes Model 51
4.3 Image Processing using Matlab Software
4.3.1 IR Sensor Conversion Formula
4.3.2 Image Processing Post-processing Technique
57
57
60
4.4 Shape Detector Device Data Collections 65
4.5 3D Reconstructions for Various Object
4.5.1 3D Surface Reconstruction
4.5.2 Repeatability
4.5.3 Image Accuracy
65
66
69
72
4.6 Summary 73
5 APPLICATION ON THE LOWER LIMB PROSTHETIC
MODEL 75
5.1 Introduction 75
5.2 Lower Limb Prosthetic Models 76
5.3 3D Image Reconstruction for Lower Limb Prosthetic
Model 78
5.4 Image Analysis 82
5.5 Shape Detector Device Tested with Real Skin (Chicken
Drumstick) 88
5.6 Summary 91
6 CONCLUSION AND FUTURE WORKS 92
6.1 Conclusion 92
x
6.2 Future Works 94
REFERENCES 97
Appendices A - B 108-131
xi
LIST OF TABLES
TABLE NO. TITLE PAGE
2.1 Results of non-matching vertices for six selected objects 15
2.2 Comparison of the devices used to reconstruct the 3D
image of lower limb prosthetic socket design with the
accuracy
17
2.3 Control points for measuring characteristics of the
GP2D120 sensor [77]
23
2.4 Comparison between traditional process, 3D camera, and
IR sensor in reconstructing image of an object
30
3.1 IR analog output voltage when different value of
capacitor installed at the VCC and GND of the IR
36
3.2 Results from the experiment in order to choose the
optimum IR sensor need to be install in the device
38
3.3 Analog output voltage collected with a different distance
between IR sensor and object surface
42
3.4 Functions of components in a shape detecting sensor
device
46
4.1 Mathematical equation to calculate volume of a polygon
shape model
53
5.1 Dimension of lower limb prosthetic model for each layer
in a diameter (mm)
77
5.2 List of output data obtained from the IR sensor after the
conversion equation is applied at each layer
84
5.3 The accuracy of 3D reconstructed models 86
xii
5.4 Comparison of an accuracy (mm) between existing
medical and sensor device
87
xiii
LIST OF FIGURES
FIGURE NO. TITLE PAGE
1.1 Lower limb prosthetic model design 2
1.2 (a) The prosthetic lower limb, (b) the 3D model image of
the amputee’s skin, and (c) a plaster casting mould of the
patient produce from the 3D model image 2
2.1 (a) Measurement of stump with liner and (b) chalk
negative cast with critical zones [34] 10
2.2 (a) Negative cast with opening into critical zones and
(b) positive cast [34] 11
2.3 (a) MRI image of a bones model and (b) using CT-Scan
in scanning lower limb prosthetic bones model [14] 12
2.4 3D modeling of the prosthetic limb [14] 14
2.5 Deformation process helps in matching the measured
point to the registered vertices, (a) the residual limb
shape after deformation is applied and (b) the actual
shape of the residual limb [38] 15
2.6 Finite element analysis that show the pressure at the
residual limb while wearing the prosthetic socket [14] 19
2.7 (a) Multiple rotating range sensors and (b) sensor system
overlapping area [11] 24
2.8 Range finding based on IR techniques [72] 25
2.9 The patterns of the ring surface plotted using
measurement results (a) 1 mm, (b) 2 mm, and (c) 4 mm
[74] 25
2.10 Experiment setup of the device [6] 26
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2.11 YAIR infrared ring layout and shadowed sectors show
the sensitivity lobes [10] 28
3.1 Schematic structure of shape detector device 33
3.2 Infrared sensor GP2D120XJ00F (Optoelectronic device) 34
3.3 IR soldered with 100 µF capacitor 35
3.4 Circuit diagram of the 100 µF capacitor soldered in the
IR sensor 35
3.5 Transmitted and reflected signal from the IR sensor to
the object surface 37
3.6 Unwanted reflected signal from other sensors received by
a different sensor will cause error in a reading 38
3.7 Schematic design for control board circuit 39
3.8 Time diagram between the outputs of the Arduino from
PWM pins to the IR sensor to measured distance 40
3.9 Model array sensor dimension 41
3.10 Minimum distance between the IR sensor and object
surface and the maximum height of an object that can be
use to reconstruct 3D image 42
3.11 The arrangement of five IR’s installed in the sensor array
rotating an object model 43
3.12 Comparison collected sensor value data between turning
the sensor array and object model 44
3.13 The rotation of object model during data collection and
sensor measured distance at each point 44
3.14 Model sensor device 45
3.15 Time line diagram of the turn ON and OFF of the IR
sensor in a sensor array 47
3.16 Arduino board flow chart 48
4.1 Conversion from IR sensor data to Matlab data
acquisition arrangement 51
4.2 Various polygon shape model used in the experiment
(a) moon, (b) quatrefoil, (c) rectangle, (d) hemisphere,
(e) cylinder, and (f) ellipse (dimension in mm) 52
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4.3 The setup experiment in choosing the colour of the
printed model 53
4.4 IR sensor response for different colour papers 54
4.5 The condition of the reflectance signal of the IR sensor
both in rough and smooth surface of a model 55
4.6 3D printed polygon model using 3D printer 56
4.7 Printed 3D polygon model is measured to compared with
the design dimension (a) from the top view and (b) with a
polygon model in a flat position 56
4.8 GP2D120 example of output characteristics with inverse
number of distance [94] 58
4.9 Post-processing block diagram 60
4.10 Point fitting graph represent for both unsmooth (red line)
and smooth data plotted (blue line) 62
4.11 Point fitting data results before and after the algorithm
applied to a random data 65
4.12 3D reconstructions for polygon circle-flat model shapes
of an object (a) moon, (b) rectangle, and (c) hemisphere 66
4.13 3D reconstructions for polygon circle based model
shapes of an object (a) quatrefoil, (b) cylinder, and (c)
ellipse 68
4.14 Other model shape used in the experiment with different
shape and it is not a polygon shape (a) star, (b) tulip,
(c) flower, (d) trefoil, (e) curvilinear, and (f) egg shape 70
4.15 Bar graph of a polygon model and its accuracy (Polygon
model vs accuracy percentage) 73
5.1 Example of a lower limb prosthetic patient cut (a)
Model1, (b) Model2, (c) Model3, and (d) Model4 76
5.2 Dimension of lower limb prosthetic model 76
5.3 Printed lower limb prosthetic model using 3D printer 77
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5.4 3D prosthetic model shape step-by-step image
reconstruction (a) 3D image of real sensor value data,
(b) smoothing algorithm applied to the data (robust
smooth and spline data), and (c) new reconstruction
image 78
5.5 Prosthetic models reconstructed image from the collected
data (a) Model1, (b) Model2, (c) Model3, and (d)
Model4 after smooth algorithm applied to the data 80
5.6 Whiskers bar graph between minimum and maximum
data at the same arch length (mm) using prosthetic model
(a) Model1, (b) Model2, (c) Model3, and (d) Model4 82
5.7 Chicken drumstick used in the test experiment (a) length
of the drumstick and (b) diameter of the drumstick 88
5.8 Experiment setup for a chicken drumstick inside the
sensor device 89
5.9 3D reconstruction of a chicken drumstick used in the
experiment is to be applied on real skin 90
6.1 Different type of IR sensors installed in the shape
detector sensor device to measure data of a model 95
xvii
LIST OF ABBREVIATION
3D - Three-Dimension
CT-Scan - Computed Tomography Scan
MRI - Magnetic Resonance Imaging
2D - Two Dimension
US - Ultrasound
LD - Laser diode
PSD - Position Sensing Detector
IR - Infrared
ToF - Time of Reflect
CAD/CAM - Computer-aided Design and Computer-aided
Manufacturing
FEA - Finite Element Analysis
ABC - American Board of Certification in Orthotics,
Prosthetics & Pedorthics
BOC - Board for Orthotics/Prosthetic Certification
AIPP - Amputee Independent Prosthesis Properties
RE - Reverse Engineering
ADC - Analog-to-Digital Converter
LED - Light emitting diode
FKCN - Fuzzy Kohonen Clustering Network
IC - Integrated circuit
PWM - Pulse Width Modulation
USB - Universal Serial Bus
ICPS - Input Capture Programming
xviii
ABS - Acrylonitrile Butadiene Styrene
.txt - Text file
PCB - Printed Circuit Board
xix
LIST OF SYMBOLS
θ - angle
α - Alpha
β - Beta
cm - centimeter
° - degree
Co - Diffusivity
D - distance
GND - ground
Hz - Heartz
Vin - Input Voltage
kPa - kilo Pascal
I - Light Intensity
µs - Light Source
MHz - Mega Heartz
µF - micro Farad
mm - millimeter
ms - milliseconds
% - percent
π - phi
η - Power of Specular Reflected Light
R - radius
Vref - Reference Voltage
µr - Reflected
xx
s - seconds
C1 - Specularity
Δθ - Step Size
µn - Surface Normal
µv - Viewing Vector
Vcc - Voltage
xxi
LIST OF APPENDICES
APPENDIX TITLE PAGE
A Author’s Publications List 108
A.1 Refereed Articles 108
A.2 Copyright Certificates 109
A.3 International Conferences 109
A.4 Awards 110
B Infrared Sensor GP2D120XJ00F Datasheet,
Schematic Diagram of An Arduino Board, Shape
Detector Device Circuit Connection, Polygon
Volume Shape Formula, IR Sensor Conversion
Equation, Arduino Control Board Algorithm, and
3D Image Reconstruction Developed Algorithm
111
B.1 Infrared Sensor GP2D120XJ00F Datasheet 111
B.2 Schematic Diagram of An Arduino Board 119
B.3 Shape Detector Device Circuit Connection 120
B.4 Polygon Volume Shape Formula 121
B.5 IR Sensor Conversion Equation 123
B.6 Arduino Control Board Algorithm 125
B.7 3D Image Reconstruction Developed Algorithm 129
1
CHAPTER 1
INTRODUCTION
1.1 Background
A three dimension (3D) image obtained from Computer Tomography (CT)
Scan, and Magnetic Resonance Imaging (MRI) are crucial in order to assist medical
diagnosis and analysis. These medical data provide good results but with high cost.
Meanwhile, by using two dimension (2D) images, several simulations can be done
for the needs of the user. However, a proper experiment analysis is required to
correct the obtained results that will cause additional cost for the test [1]. A 3D
image is very important as it gives full imaging details of the measured object which
will allow efficient evaluation.
A 3D image gives more data compared to 2D data images. Therefore,
providing 3D images for biomedical measurement is always better than having only
2D images to analyse patients’ conditions and their needs. Reconstructing a 3D
image requires the use of a sensor array that is normally consisted of more than one
sensor. A solution needs to be identified in order to reduce the number of sensors
used to obtain data in the 3D image. It will give an advantage to medical
practitioners by providing them with 3D data image, especially in orthotic and
prosthetic departments. Lower limb prosthetic, for example, requires detailed
information of a patient’s limb condition before designing a suitable and comfortable
prosthetic limb for the patient. Figure 1.1 shows an example of a lower limb
prosthetic model design.
2
Figure 1.1 Lower limb prosthetic model design
Conventionally, medical practitioners use chalk bandages to make new
design of prosthetic limb for their patients. Compared to other disability designs,
prosthetic is the most challenging research in order to properly interface between the
device and human body part to make sure that it fits and comfortable to the user [2].
Prosthetic is defined as a medical field in substituting or a replacement of a missing
limbs with an artificial substitution [3]. Basically, to reconstruct a residual limb, a
Prosthetic Technician needs to know the step from taking data to the reconstruction
of the image until the limb design is completed. This 3D reconstruction offers many
advantages, as the 3D image depends on the software and computer analysis to
produce more accurate data [4]. Figure 1.2 shows how researchers reconstructed a
3D image and finally produce a plaster mould of a residual limb.
(a)
(b)
(c)
Figure 1.2 (a) The prosthetic lower limb, (b) the 3D model image of the amputee’s
skin, and (c) a plaster casting mould of the patient produce from the 3D model image
Figure 1.2 shows the step by step reconstruction of the plaster mould based
on the prosthetic limb. In order to create the plaster based on the prosthetic limb, a
3D skin model is needed, and it is generated using various types of sensors. These
3
sensors are used and installed in the device to capture data for reconstructing the
images using the prosthetic lower limb.
Laser scanner, ultrasound (US), laser diode (LD), position sensing detector
(PSD), camera and infrared (IR) are used to reconstruct a 3D image of an object.
The sensor had its own advantages and drawbacks. The comparison between each
device can be seen based on their accuracy, resolution, cost, and time to collect data.
IR sensor has proven to be able to measure distance, and the data collected is used to
reconstruct an object’s surface.
Over the years, there have been significant improvements in the mobile robot
technology field as well as in devices implemented with infrared sensors. Infrared
sensor is one of the commonly used sensors in mobile robots. The sensor has many
applications such as to measure distance [5], avoidance system [6], and also obstacle
detection [7]. Other than that, it offers low price, easy installation, portable, and
provides a fast response.
IR sensors have been widely used in mobile robots with several functions,
and some of the researcher combines IR with other sensors to improve the results
obtained. For example, IR with the 3D camera to increase the resolution of the
image, IR combined with ultrasound helps in creating 3D images of an object [8],
and IR installed with 3D depth sensor can be used to measure the depth and distance
of an object [9].
1.2 Problem Statement
With the advancement of technology, there are a lot of devices that can be
used to reconstruct the 3D image from model surfaces. Some devices offer very
accurate data but with high cost, faster data preview but in 2D form, higher
resolution image but require a very high computational system, and also wide
sensing area but low in resolution. All the devices have their own advantages and
4
disadvantages. Infrared sensors offer low cost, small size, portable, lightweight and
require a few components in order to operate.
The problems with devices that are installed with infrared sensor in the
system are that they are highly dependent on object reflectance [10]. Transmitted
signal from the sensor is reflected when it hits the boundary of the reflected beam or
from the intensity of the reflected light [11]. The object surface is very important in
collecting a high impact of reflected signal to the sensor. If the object surface is too
rough, the transmitted signal is unable to highly reflect to the sensor receiver. Small
number of IR sensors installed in the device [15] will take more time to collect data
in a certain active area. Each sensor has their time of reflect (ToF) measured, which
will give results or data to the device [10]. With a small amount of IR sensors used,
total time required to obtain the data is longer.
In Orthotic and Prosthetic department, the development of lower limb
prosthetic socket required an expertise to reconstruct the shape of the residual limb
that takes a long time to complete the socket [12]. Some of the hospital used
advance technologies to reconstruct the 3D image of a residual limb. MRI and CT-
Scan have been used, and it requires patient to lie down at the bed that will deform
the actual shape of the limb [14, 15, 16]. Radiation from the CT-Scan will give a
negative effect to the patient [33, 34]. Other than that, the cost is too high and not
everybody can afford to use the technology. Traditional method to reconstruct the
residual limb is by using plaster casting. Problem occurred when the cast is dry it
will shrink, and the actual size of the socket is change. Patient will not be
comfortable with the socket that could cause skin irritation, tissue damage and ulcer
to the skin [2, 20].
1.3 Research Objectives
Based on the problem statement, there are three objectives in the research to
be achieved. All the objectives are listed below:
5
a. To design a system that is capable to control the function of an infrared
sensor array for prosthetic model data collection.
b. To develop an Arduino Microcontroller algorithm to control infrared
array sensor data acquisition and image reconstruction algorithm using
Matlab.
c. To analyse and evaluate the system performance based on the measured
results and the reconstructed images.
1.4 Scope of the Thesis
The scope of this research is divided into two different parts, which is
designing the device to collect data for a lower limb prosthetic model and post-
processing the information on the data analysis algorithm to reconstruct the 3D
image. Details of each scope are explained as follows:
a. Designing and implementing a controller circuit using Arduino
microcontroller for infrared array sensor and to rotate the prosthetic model.
Five infrared sensors are installed in the device with a control board that is
responsible to monitor the function of the overall system. Arduino is used as
a microcontroller in the device to harvest data from the IR sensors and
controls the rotation of the stepper motor. It also controls the switches of the
sensor since it will only turn ON one at a time to avoid any redundant
reflectance signal from other IRs.
b. Integrating the system with an actuator motor which is able to slowly bring
up the model to the sensor array to collect data for the whole body. An object
is placed at the center underneath the IR sensor array, and the data is
collected for image reconstruction purposes. In order to increase the height
of an object, a cupboard with a thickness of 2 mm has been slotted
underneath the object so that the device is able to measure data for the whole
object.
6
1.5 Significant Findings
This section describes the contribution of the research works in the field of a
3D image reconstruction for a lower limb prosthetic. Experimental investigation of
the development of the device is presented in this thesis. The major outcomes of this
thesis can be summarised as follows:
(1) To address the use of IRs installed in the device, an experimental
investigation was conducted on the principal sensor to measure the distance
of an object without any support from other sensors. Researchers added other
sensors in the device in order to obtain more accurate data for the results that
also required a correct arrangement between the sensors to avoid any
redundant signals.
(2) The IR sensor has been used widely in measuring distance, avoid collision
and to detect any obstacles located in front the device. The application of IR
to reconstruct the 3D image of a lower-limb prosthetic design has not yet
been reported. Data from the sensor could be used to reconstruct the
prosthetic lower limb with an accurate measurement. The accuracy is
calculated based on the diameter of the prosthetic model itself.
(3) A device installed with IR sensors to collect data of a prosthetic model was
introduced. Experimental investigation was conducted to the device, and the
results were used in the image reconstruction.
1.6 Thesis Overview
A review of a lower limb prosthetic socket development with the present
study is given in Chapter 2, including the application of IR sensors in measuring the
distance of an object’s surface. Then, in Chapter 3, the conceptual design of a shape
detector device is illustrated with the experimental investigation on the infrared
sensor characteristics, working principle of the control board design, sensor array
7
model, and the hardware device of the system. Meanwhile, Chapter 4 described the
shape detector device tested with various shapes of polygon models, detailed
explanation on the size of the polygon model used in the experiment, equation used
to convert the sensor value to the distance in a centimeter (cm), and the results of the
3D image reconstruction of the polygon shape are also shown. The repeatability
results of the object are discussed, and the accuracy proved the effectiveness of the
device. Next, the application on the lower limb prosthetic socket is tested in Chapter
5. Details on the prosthetic model used in the experiment are explained, image
analysis of the prosthetic with the percentage of accuracy is also shown. The same
concept is applied to a chicken drumstick to measure the accuracy of the device.
Finally, the thesis concludes in Chapter 6 with an outlook on future project
development.
97
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Residual Limb for Customizing The Design of A Prosthetic Socket. Medical
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