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E-raamat: Computer Systems for Healthcare and Medicine

Edited by (Warsaw University of Technology, Poland), Edited by (University of Calabria, Italy)
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Computer Systems for Healthcare and MedicineSuurem pilt
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The development of modern civilization leads us to solve new problems which did not exist before. The contemporary world faces a great challenge of aging societies, where increasing numbers of senior citizens require constant medical attention. Advanced technologies must be implemented to ensure the safety and well-being of elderly people, patients in hospitals, and disabled persons. These include both sophisticated data acquisition systems and data processing algorithms aimed at the constant and discreet monitoring of persons whilst raising alarm if immediate attention is required.

Computer Systems for Healthcare and Medicine presents a novel look at the introduced problems, including proposed solutions in the form of automated data acquisition and processing systems, which were tested in various environments. Characteristic features include a wide range of sensors used to monitor the situation of the person, and accurate decision making algorithms, often based on the computational intelligence domain.

Technical topics discussed in the book include the following applications for healthcare:

>> Infrared sensors
>> MEMS
>> Ultra wideband radars
>> Deep learning
>> Decision trees
>> Artificial neural networks
>> Gabor filters
>> Decision support systems
Preface xi
Acknowledgements xiii
List of Contributors xv
List of Figures xix
List of Tables xxv
List of Abbreviations xxvii
1 Ultra-Wide Band Radar Monitoring of Movements in Homes of Elderly and Disabled People: A Health Care Perspective 1(30)
Tobba T. Sudmann
Ingebjorg T. Borsheim
Tomasz Ciamulski
Jakub Wagner
Knut Ovsthus
Frode F. Jacobsen
1.1 The Relevance of Radar Technology and other Assistive Technology for Elderly and Disabled People
2(3)
1.2 Healthy Ageing: Ageing at Home
5(1)
1.3 Definition of Falls and Movement Analysis
6(4)
1.3.1 Activities of Daily Living and Falls
8(1)
1.3.2 Self-Selected Walking Speed: A Vital Sign
9(1)
1.4 Step-by-Step Development of the Radcare Technology
10(3)
1.5 Discussion: Findings and Experiences
13(6)
1.5.1 Detection of Presence at Selected Places
14(1)
1.5.2 Detection of Motion
14(1)
1.5.3 Estimation of Gait Speed
15(1)
1.5.4 Estimation of Movement Direction
16(1)
1.5.5 Estimation of Travelled Distance
16(1)
1.5.6 Estimation of Acceleration
17(1)
1.5.7 Usefulness of Visualisation in Real Time for Health Care Personnel
18(1)
1.6 User Interface and Participatory Design
19(1)
1.7 Concluding Considerations and Suggestions for Future Research
20(2)
Acknowledgements
22(1)
References
22(9)
2 A System for Elderly Persons Behaviour Wireless Monitoring 31(20)
Jerzy Kolakowski
Magdalena Berezowska
Ryszard Michnowski
Karol Radecki
Lukasz Malicki
2.1 Introduction
31(3)
2.2 System For Mobility Investigation
34(4)
2.2.1 System Components
34(2)
2.2.2 System Operation
36(2)
2.3 Test Campaign
38(1)
2.4 Results Analysis
38(10)
2.4.1 Activity Analysis
39(4)
2.4.2 Room Occupancy Determination
43(5)
2.5 Conclusion
48(1)
Acknowledgements
48(1)
References
48(3)
3 Polychromatic LED Device for Measuring the Critical Flicker Fusion Frequency 51(44)
Alexey Lagunov
Ludmila Morozova
Dmitry Fedin
Nadejda Podorojnyak
Vladimir Terehin
Aleksander Volkov
3.1 Introduction
51(2)
3.2 Colour Vision Theories
53(8)
3.3 Physical and Physiological Characteristics of Colour
61(2)
3.4 Colour Influence on the Organism
63(3)
3.5 Basics of CFFF Method
66(2)
3.6 Experiment Methodology
68(1)
3.7 Devices Comparison
69(2)
3.8 LED Unit
71(2)
3.9 Software
73(3)
3.10 Experiment Performing
76(2)
3.10.1 Mathematical and Statistical Processing
78(1)
3.11 Study Results
78(9)
3.12 Conclusion
87(2)
Acknowledgements
89(1)
References
89(6)
4 EIGER Indoor UWB-Positioning System 95(18)
Jerzy Kolakowski
Angelo Consoli
Vitomir Djaja-Josko
Jaouhar Ayadi
Lorenzo Moriggia
Francesco Piazza
4.1 Introduction
95(3)
4.2 UWB-Positioning Subsystem
98(8)
4.2.1 UWB System Architecture
98(1)
4.2.2 Anchor Nodes
99(2)
4.2.3 UWB Radio Interface
101(1)
4.2.4 Transmission Scheme
102(3)
4.2.4.1 Transmission scheme
103(1)
4.2.4.2 TDOA calculation
104(1)
4.2.5 Positioning Algorithm
105(1)
4.3 System Investigation
106(4)
4.3.1 Test Scenarios
106(2)
4.3.2 System Tests in Static Conditions
108(1)
4.3.3 Localisation of Moving Objects
108(2)
4.4 Conclusions
110(1)
Acknowledgements
110(1)
References
110(3)
5 On Detection and Estimation of Breath Parameters Using Ultrawide Band Radar 113(16)
Jan Jakub Szczyrek
Wieslaw Winiecki
5.1 Introduction
113(2)
5.2 Data Acquisition and Preprocessing from UWB Radar
115(2)
5.2.1 Signal Reprezentation
115(2)
5.2.2 Preprocessing
117(1)
5.3 Off-Line Development
117(3)
5.3.1 Trace Selection
117(1)
5.3.2 Trace Processing
118(2)
5.4 Breath Detection in Real-Time System
120(6)
5.4.1 Sofware Architecture
121(1)
5.4.2 Movement Positioning
122(2)
5.4.3 Suplementary Considerations
124(2)
5.5 Summary
126(1)
Acknowledgement
127(1)
References
127(2)
6 Gabor-Filter-based Longitudinal Strain Estimation from Tagged MRI 129(12)
Lukasz Blaszczyk
Konrad Werys
Agata Kubik
Piotr Bogorodzki
6.1 Theoretical Background
129(4)
6.1.1 Tagged Magnetic Resonance Imaging (tMRI)
130(2)
6.1.2 Cardiac Strain
132(1)
6.2 Materials and Methods
133(3)
6.2.1 MRI Sequence
133(1)
6.2.2 Patient Data
133(1)
6.2.3 Longitudinal Strain Estimation Using Gabor Filter Bank
133(3)
6.3 Results
136(1)
6.4 Discussion
137(1)
6.5 Conclusion
138(1)
References
138(3)
7 A Decision Support System for Localisation and Inventory Management in Healthcare 141(28)
Francesca Guerriero
Giovanna Miglionico
Filomena Olivito
7.1 Introduction
142(2)
7.2 Methods
144(2)
7.3 The DSS Optimisation Models
146(2)
7.4 The "No-Expert Users" Functionalities of the DSS
148(7)
7.5 The "Expert Users" Functionalities of the DSS
155(11)
7.6 Conclusions
166(1)
Acknowledgements
166(1)
References
166(3)
8 Deep Learning Classifier for Fall Detection Based on IR Distance Sensor Data 169(24)
Stanislaw Jankowski
Zbigniew Szymanski
Uladzimir Dziomin
Pawel Mazurek
Jakub Wagner
8.1 Introduction
169(1)
8.2 Statistical Classification
170(4)
8.2.1 Selection of Statistical Learning Algorithm
171(1)
8.2.2 Multilayer Perceptron as Discriminative Classifier
172(1)
8.2.3 Preprocessing and Variable Selection
173(1)
8.2.4 Generalisation and Quality Prediction
174(1)
8.3 Methodology of Data Generation
174(4)
8.3.1 Data Acquisition
174(1)
8.3.2 Data Preprocessing
175(3)
8.4 Deep Learning Classifier
178(10)
8.4.1 The Data Set
178(1)
8.4.2 Data Filtration
179(2)
8.4.3 Feature Extraction
181(1)
8.4.4 Feature Selection
181(3)
8.4.5 NPCA
184(4)
8.5 Results
188(1)
8.5.1 Neural Network Enhanced by Feature Selection
188(1)
8.5.2 Deep Learning System
188(1)
8.6 Conclusions
189(1)
References
190(3)
9 Decision Trees Implementation in Monitoring of Elderly Persons Based on the Depth Sensors Data 193(20)
Piotr Bilski
Pawel Mazurek
Jakub Wagner
Wieslaw Winiecki
9.1 Introduction
193(2)
9.2 Related Works
195(1)
9.3 Architecture of the Monitoring System
196(2)
9.4 Characteristics of the Acquired Data
198(2)
9.4.1 Data Acquisition Technique
198(1)
9.4.2 Data Preprocessing
199(1)
9.5 Extraction of Features
200(2)
9.6 Decision Trees
202(4)
9.6.1 Tree Structure and Construction Algorithm
203(2)
9.6.2 Tree Modification to Maximise Accuracy
205(1)
9.7 Experimental Results
206(2)
9.8 Conclusion
208(1)
Acknowledgment
209(1)
References
209(4)
10 Recurrent Approximation in the Tasks of the Neural Network Synthesis for the Control of Process of Phototherapy 213(36)
Alexander Trunov
10.1 Introduction
214(1)
10.2 Pointing the Task of Interaction between an Electron of Radical and Photon into Magnetic Field
215(4)
10.3 Encoding and Decoding
219(3)
10.4 Specific Features of Dose Calculation and Formation of the Spectral Composition of Radiation
222(8)
10.4.1 Application of Data Mining for Decomposition of Scalar- or Vector-Function of Vector
223(2)
10.4.2 Application of RANN and Problem of Analytic Learning for Neural Network
225(1)
10.4.3 Modeling and Convergence of a Sequence of Synaptic Weight Coefficients (SWC)
226(4)
10.5 Statement and Solution of the Control Efficiency Problem During Physiotherapy Process
230(10)
10.5.1 Pointing the Problem of Minimizing the Objective Function
231(9)
10.6 Modeling and Convergence of a Sequence of SWC
240(3)
10.7 Conclusions
243(1)
References
244(5)
Index 249(2)
About the Editors 251(2)
About the Authors 253
Piotr Bilski, Francesca Guerriero
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