vi
Contents
1 Introduction 1
1.1 Conventions Used in the Dissertation . . . 1
1.2 Background . . . 2
1.3 Motivation . . . 3
2 Aims, Objectives, and Scope 5 2.1 General Goals . . . 5
2.2 Thesis Statement . . . 5
2.3 Dissertation Structure . . . 5
3 State of the Art 7 3.1 Diabetes and Diabetic Foot . . . 7
3.1.1 Diabetes and Its Types . . . 7
3.1.2 Anthropometric Parameters Associated with Diabetes . . . 8
3.1.3 Diabetic Foot and Related Conditions . . . 10
3.2 Pedobarography—the Past and Today . . . 12
3.3 Plantar Pressure Distribution Images . . . 13
3.4 Plantar Pressure Measurement Systems . . . 14
3.5 Pedobarographic Platforms . . . 15
3.5.1 Comparison of the Platforms . . . 22
3.6 Plantar Pressure Analysis Software . . . 24
3.7 Applications of Pedobarography . . . 31
3.7.1 Neuropathy Detection . . . 31
4 Data Acquisition 33 4.1 Group of Examined Patients . . . 33
4.2 Clinical Control Group . . . 34
4.3 Examination Procedure . . . 37
5 Data Analysis 39 5.1 Image Data Preprocessing . . . 39
5.1.1 Conversion to Grayscale . . . 40
5.1.2 Footprint Normalization . . . 42
5.1.3 Foot Division into Plantar Regions . . . 43
5.2 Two-Dimensional Discrete Fourier Transform . . . 44
5.3 Two-Dimensional Discrete Cosine Transform . . . 46
5.4 Pearson Correlation Coefficient . . . 51
5.5 Convolutional Neural Networks with Haar-Based Pooling . . . 54
5.5.1 Artificial Neural Networks . . . 54
5.5.2 Convolutional Neural Networks . . . 55
vii
5.5.4 Two-Dimensional Discrete Convolution . . . 59
5.5.5 Activation Functions . . . 65
5.5.6 Feature Pooling . . . 74
5.5.7 Dropout . . . 77
5.5.8 Fully Connected Layers . . . 79
5.5.9 Hidden Layers . . . 80
5.5.10 Classification . . . 80
5.5.11 Backpropagation in CNNs . . . 81
5.5.12 Actual Model . . . 84
5.5.13 Final Data Preparation . . . 87
5.6 Foot Pressure Diagnostic Toolbox . . . 88
5.6.1 Tools and Utilities . . . 89
5.6.2 Analysis Toolbox . . . 91
5.7 Foot Pressure Measurement Format (FPMF) . . . 93
5.8 NeuralNET . . . 95
5.8.1 The Matrix Class . . . 95
5.8.2 The Volume Class . . . 99
5.8.3 The Functions Class . . . 101
5.8.4 The ImageTools Class . . . 102
5.8.5 Other Classes . . . 102
6 Results and Discussion 104 6.1 DFT-Based Methods . . . 104
6.2 Pearson Correlation Coefficient . . . 104
6.3 Convolutional Neural Networks . . . 108
6.4 Recommended Diagnostic Procedure . . . 110
7 Conclusions 112
Bibliography: Books and Papers 114
Bibliography: Online Sources 120
