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E-raamat: Electronic Skin: Sensors and Systems

Edited by (Lebanese International University, Lebanon and University of Genoa, Italy), Edited by (University of Genoa, Italy)
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This book on electronic skin takes into account not only sensing materials, but it also provides a thorough assessment of the current state of the art at system level. The book addresses embedded electronics and tactile data processing and decoding, techniques for low power embedded computing, and the communication interface.

A considerable amount of effort has been devoted, over recent years, towards the development of electronic skin (e-skin) for many application domains such as prosthetics, robotics, and industrial automation.

Electronic Skin: Sensors and Systems focuses on the main components constituting the e-skin system. The e-skin system is based on: i) sensing materials composing the tactile sensor array; ii) the front end electronics for data acquisition and signal conditioning; iii) the embedded processing unit performing tactile data decoding; and iv) the communication interface in charge of transmitting the sensors data for further computing.

Technical topics discussed in the book include:

  • Tactile sensing material;
  • Electronic Skin systems;
  • Embedded computing and tactile data decoding;
  • Communication systems for tactile data transmission;
  • Relevant applications of e-skin system.
The book takes into account not only sensing materials but it also provides a thorough assessment of the current state of the art at system level. The book addresses embedded electronics and tactile data processing and decoding, techniques for low power embedded computing, and the communication interface.

Electronic Skin: Sensors and Systems is ideal for researchers, Ph.D. students, academic staff and Masters/research students in sensors/sensing systems, embedded systems, data processing and decoding, and communication systems.
Preface xi
Acknowledgement xv
List of Contributors
xvii
List of Figures
xxi
List of Tables
xxix
List of Abbreviations
xxxi
1 Electronic Skin Systems
1(12)
Ali Ibrahim
Maurizio Valle
1.1 Introduction
1(2)
1.2 Integration of E-skin in iCub Robot
3(3)
1.2.1 E-skin on iCub Fingertips
3(1)
1.2.2 E-skin on iCub Palm
4(1)
1.2.3 E-skin on the iCub Forearm
4(2)
1.3 E-skin in Telemanipulation: Of the EU2020 TACTILITY Project
6(1)
1.4 E-skin in Upper Limb Prostheses
7(3)
1.4.1 Piezoelectric-Based E-Skin
8(1)
1.4.2 Piezoresistive-Based E-Skin
8(2)
1.5 Conclusion
10(3)
References
10(3)
2 Artificial Tactile Sensing and Electronic-Skin Technologies
13(34)
Hoda Fares
Maurizio Valle
2.1 Introduction
14(1)
2.2 SENSE of Touch
14(1)
2.3 Artificial Skin: Concept and Evolution
15(9)
2.3.1 Understanding the Human Skin Physiology
15(5)
2.3.2 Artificial Skins
20(4)
2.4 E-Skin Systems
24(9)
2.4.1 Transduction Mechanisms
26(4)
2.4.2 Tactile Sensing Applications: Robotic and Prosthetic Hands
30(1)
2.4.2.1 Tactile sensors in commercial robotic hands
30(2)
2.4.2.2 Tactile sensory systems in prosthetics hands
32(1)
2.5 Requirements and Challenges
33(1)
2.6 Conclusion and Perspectives
34(13)
References
35(12)
3 Tactile Sensors for Smart Human-Object Interactions: Devices and Technologies
47(26)
Andrea Adami
Leandro Lorenzelli
3.1 Introduction
47(4)
3.2 Technologies and Devices
51(14)
3.2.1 Fabrication Technologies
51(3)
3.2.2 Tactile Sensor Devices
54(1)
3.2.2.1 Piezoresistive and resistive MEMS
54(3)
3.2.2.2 Capacitive
57(3)
3.2.2.3 Piezoelectric
60(2)
3.2.2.4 Other sensing techniques
62(1)
3.2.2.5 Recent trends
63(2)
3.3 Conclusions
65(8)
Acknowledgements
65(1)
References
65(8)
4 Optical-based Technologies for Artificial Soft Tactile Sensing
73(28)
Matteo Lo Preti
Massimo Totaro
Egidio Falotico
Lucia Beccai
4.1 Introduction
74(1)
4.2 Optical-based Tactile Sensors
75(5)
4.2.1 Basic Optical Principles
76(1)
4.2.2 Pressure and Strain Optical Sensing
77(3)
4.3 Examples of Optical-based Tactile Sensors
80(5)
4.3.1 Single Optical Waveguide Sensor
80(2)
4.3.2 Bundle Optical Waveguide System
82(2)
4.3.3 Continuum Optical Waveguide Skin
84(1)
4.4 Signal Processing Approaches for Continuum Optical Waveguide Skins
85(9)
4.4.1 Analytical Methods
86(1)
4.4.2 Machine Learning Methods
87(4)
4.4.3 Case Study: Distributed Mechanical Sensing in a Soft Optical Skin
91(3)
4.5 Conclusion
94(7)
References
96(5)
5 Physical Contact Localization with Artificial Intelligence and Large-Area Fiber Bragg Grating Tactile Sensors for Collaborative Biorobotics
101(12)
Tamas Czimmermann
Luca Massari
Jessica D'Abbraccio
Giuseppe Terruso
Martina Zaltieri
Giulia Fransvea
Andrea Aliperta
Eduardo Palermo
Emiliano Schena
Edoardo Sinibaldi
Calogero Maria Oddo
5.1 Introduction
102(1)
5.2 Materials and Methods
102(6)
5.2.1 FBG-based Sensing Skin
103(1)
5.2.2 Experimental Platform and Datasets
104(3)
5.2.3 Neural Network Structures
107(1)
5.3 Results
108(2)
5.4 Discussion and Conclusion
110(3)
References
111(2)
6 Efficient Algorithms for Embedded Tactile Data Processing
113(26)
Hamoud Younes
Mohamad Alameh
Ali Ibrahim
Mostafa Rizk
Maurizio Valle
6.1 Introduction
113(2)
6.2 Tactile Data Processing Algorithms
115(9)
6.2.1 Data Preprocessing
115(2)
6.2.2 Classification and Regression
117(1)
6.2.2.1 Machine learning
117(6)
6.2.2.2 Deep learning
123(1)
6.3 Embedded Processing System
124(4)
6.3.1 Hardware Platforms
124(4)
6.4 Case Study: Touch Modality Classification
128(3)
6.4.1 Experimental Setup
129(1)
6.4.2 Implementation Details
130(1)
6.5 Conclusion
131(8)
References
132(7)
7 Approximate Arithmetic Circuits for Energy Efficient Data Processing in Electronic Skin
139(24)
Mario Osta
Ali Ibrahim
Maurizio Valle
7.1 Introduction
139(2)
7.2 Approximate Computing for Low-Pass Fir Filters
141(2)
7.3 Approximate Filters for E-skin
143(1)
7.4 Approximate Computing for Embedded Machine Learning
144(3)
7.4.1 Approximate Arithmetic Circuits
144(2)
7.4.2 Approximate Memory
146(1)
7.4.3 Quantization
147(1)
7.5 Approximate Embedded Machine Learning for E-skin
147(7)
7.5.1 Tensorial Kernel Approach
148(1)
7.5.2 Coordinate Rotational Digital Computer Circuits
148(1)
7.5.2.1 CORDIC algorithm
149(1)
7.5.2.2 Approximate CORDIC implementation
149(2)
7.5.3 Singular Value Decomposition
151(1)
7.5.3.1 SVD algorithm
151(1)
7.5.3.2 Approximate SVD
152(2)
7.6 Discussion and Conclusion
154(9)
References
155(8)
8 Optical Links for Sensor Data Communication Systems
163(34)
Andrea De Marcellis
Elia Palange
Guido Di Patrizio Stanchieri
Marco Faccio
8.1 Introduction
164(3)
8.2 The Optical Communication Link: Principles, Data Coding, Architectures, and Devices
167(2)
8.3 Technical Solutions and Implementations of Optical Links
169(10)
8.3.1 Description of the Digital Architectures for the Coding and Decoding Processes of the Sensor Data
170(6)
8.3.2 Description of the Analogue Circuits for Sensor Signal Conditioning
176(3)
8.4 Examples of Applications of Optical Communication Links for Sensory Systems
179(8)
8.4.1 Optical Fiber Link for Prosthetics Developed by Discrete Commercial Components and Devices
179(3)
8.4.2 Optical Wireless Communication Integrated System for Implanted Biotelemetry Applications
182(5)
8.5 Conclusion
187(10)
References
188(9)
9 Artificial Skin and Electrotactile Stimulation for Advanced Tactile Feedback in Myoelectric Prostheses
197(40)
Lucia Seminara
Matija Strbac
Youssef Amin
Maurizio Valle
Strahinja Dosen
9.1 Introduction
198(2)
9.2 High-Density Sensing and Stimulation
200(3)
9.3 Electronic Skin Systems for Prosthetics
203(16)
9.3.1 Biomimetic e-skins for Prosthetic Systems
203(9)
9.3.2 Sense of Touch in Prosthetics: Case Studies
212(6)
9.3.3 Conclusive Remarks
218(1)
9.4 Electrotactile Stimulation for Sensory Feedback
219(5)
9.4.1 Electrotactile Stimulation Hardware
219(2)
9.4.2 Multiarray Electrodes and Electrode/Skin Interface
221(1)
9.4.3 Electrotactile Feedback From Myoelectric Prostheses
222(2)
9.5 Discussion
224(3)
9.6 Conclusions
227(10)
References
228(9)
Index 237(2)
About the Editors 239
Ali Ibrahim received the M.S. degree in Industrial Control from the Doctoral School of Sciences and Technologies, Lebanese University, in 2009, and the Ph.D. degree in electronic and computer engineering and robotics and telecommunications from the University of Genoa-Italy in 2016. From 2009 to 2013, he was a Project Designer in electronics in Beirut. He is currently an assistant professor at the Lebanese International University, and an associate researcher with the Department of Electric, Electronic, Telecommunication Engineering and Naval Architecture, University of Genoa. His research interests involve embedded electronic systems, FPGA implementation, digital data processing, interface electronics for electronic skin systems, embedded machine learning, approximate computing, and techniques and methods for energy efficient embedded computing.



Maurizio Valle (MV) received the M.S. degree in Electronic Engineering in 1985 and the Ph.D. degree in Electronics and Computer Science in 1990 from the University of Genova, Italy. In 1992 he joined the University of Genova, first as an assistant and in 2007 as an associate professor. From December 2019, MV is full professor at the Department of Electrical, Electronic and Telecommunications Engineering and Naval Architecture, University of Genova; MV leads the Connected Objects, Smart Materials, Integrated Circuits COSMIC laboratory. MV has been and is in charge of many research contracts and projects funded at local, national and European levels and by Italian and foreign companies. Professor Valle is co-author of more than 200 papers on international scientific journals and conference proceedings and of the book: Robotic Tactile Sensing Technologies and System, Springer Science+Business Media, Dordrecht, pp. 1248, 2013 (ISBN: 978-94007-0578-4). His research interests include electronic and microelectronic systems, material integrated sensing systems, tactile sensors and electronic-skin systems. He is IEEE senior member and member of the IEEE CAS Society.
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