Intelligent wearable interfaces

As mobile computing, sensing technology, and artificial intelligence become more advanced and their applications more widespread, the area of intelligent wearable interfaces is growing in importance. This emerging form of human-machine interaction has infinite possibilities for enhancing humans' capabilities in communications, actions, monitoring, and control.

Intelligent Wearable Interfaces is a collection of the efforts the authors have made in this area at The Chinese University of Hong Kong. They introduce methodologies to develop a variety of intelligent wearable interfaces and cover practical implementations of systems for real-life applications. A number of novel intelligent wearable interface systems are examined, including:

Network architecture for wearable robots

Wearable interface for automatic language translation

Intelligent cap interface for wheelchair control

Intelligent shoes for human-computer interface

Fingertip human-computer interface

Ubiquitous 3D digital writing instrument

Intelligent mobile human airbag system

This book is a valuable reference for researchers, designers, engineers, and upper-level undergraduate and graduate students in the fields of human-machine interactions,rehabilitation engineering, robotics, and artificial intelligence.

Author Notes

Wen Jung is a Professor in the Department of Mechanical and Automation Engineering and the Director of the Centre for Micro and Nano Systems at The Chinese University of Hong Kong (CUHK).

List of Figures	p. xi
List of Tables	p. xvii
Preface	p. xix
1 Introduction	p. 1
1.1 The Intelligent Wearable Interface	p. 1
1.2 Learning from Demonstration	p. 2
2 Network Architecture for Wearable Robots	p. 5
2.1 Introduction	p. 5
2.2 Wearable Robots and Interactions	p. 7
2.3 Wearable Robot Design	p. 8
2.4 Distributed Service-Based Architecture	p. 10
2.4.1 Extension to the Jini Model	p. 12
2.4.2 The Matching Service	p. 17
2.5 Application Scenario	p. 21
2.6 Related Works	p. 25
2.7 Conclusion	p. 27
3 Wearable Interface for Automatic Language Translation	p. 31
3.1 Introduction	p. 31
3.2 System Architecture	p. 33
3.3 Text Detection Algorithm	p. 34
3.3.1 Demands of Text Detection Algorithm	p. 34
3.3.2 Intrinsic Characteristic of a Character	p. 35
3.3.3 CIC-Based Text Detection Algorithm	p. 35
3.3.4 Combine Line Segments into a Character	p. 38
3.4 Image Cutting, Rotation, and Binarization	p. 39
3.4.1 Image Cutting and Rotation	p. 39
3.4.2 Image Binarization	p. 39
3.5 Real-ime Translation	p. 41
3.6 Conclusion	p. 41
4 Intelligent Cap Interface for Wheelchair Control	p. 43
4.1 Introduction	p. 43
4.2 Electromyography and Electrooculography	p. 45
4.3 Approach	p. 45
4.4 Interface	p. 47
4.4.1 Hardware	p. 47
4.4.2 Implementation	p. 49
4.5 Experimental Study	p. 51
4.5.1 Doorways (A-B)	p. 52
4.5.2 U-turning (B-C-B)	p. 53
4.5.3 General Path (C-D)	p. 53
4.6 Conclusion	p. 54
5 Intelligent Shoes for Human-Computer Interface	p. 56
5.1 Introduction	p. 56
5.2 Hardware Design	p. 58
5.2.1 Sensing the Parameters Inside the Shoe	p. 59
5.2.2 Gathering Information from the Sensors	p. 60
5.2.3 Wireless Communication	p. 60
5.2.4 Data Visualization	p. 61
5.3 Three Applications of the Intelligent Shoes	p. 61
5.3.1 Intelligent Shoes for Human-Computer Interface: Shoe-Mouse	p. 61
5.3.2 Intelligent Shoes for Pressure Measurement	p. 66
5.3.3 Intelligent Shoes for Human Identification	p. 75
5.4 Conclusion	p. 84
6 Fingertip Human-Computer Interface	p. 88
6.1 Introduction	p. 88
6.2 Hardware Design	p. 90
6.2.1 MEMS Accelerator for Motion Detection	p. 91
6.2.2 Signal Processing and Analysis	p. 95
6.2.3 Radio-Frequency (RF) Wireless System	p. 98
6.2.4 System Evaluation	p. 99
6.3 Specific Applications	p. 103
6.3.1 Human-Robotic-Hand Interaction Using MIDS	p. 103
6.3.2 Computer Mouse on a Fingertip (MIDS-VM)	p. 109
6.3.3 Computer Game Interaction Using MIDS	p. 121
6.3.4 MIDS for PDA Interaction (Embedded-MIDS: E-IDS)	p. 126
6.4 Conclusion	p. 136
7 Ubiquitous 3D Digital Writing Instrument	p. 139
7.1 Introduction	p. 139
7.2 Hardware Design	p. 141
7.3 Signal Processing and Analysis	p. 142
7.3.1 Kalman Filtering for MEMS Sensors	p. 145
7.3.2 Time Update Model	p. 147
7.3.3 Error Model for Time Update	p. 147
7.4 Measurement Update Model	p. 148
7.5 Testing	p. 150
7.5.1 Simulation Test	p. 150
7.5.2 Experiment Test	p. 151
7.6 Writing Application Based on Attitude EKF Compensation	p. 152
7.7 Experimental Results of an Integrated System	p. 157
7.8 Conclusion	p. 166
8 Intelligent Mobile Human Airbag System	p. 169
8.1 Introduction	p. 169
8.2 Hardware Design	p. 171
8.2.1 [mu]IMU System Design	p. 172
8.2.2 Mechanical Release Mechanism	p. 172
8.2.3 Minimization of Airbag Inflation Time	p. 174
8.2.4 The Punch Test for the Second Mechanism	p. 175
8.2.5 System Integration	p. 178
8.3 Support Vector Machine for Human Motion Determination	p. 181
8.3.1 Principal Component Analysis for Feature Generation	p. 181
8.3.2 Support Vector Machine Classifier	p. 183
8.4 Experimental Results	p. 185
8.4.1 Motion Detection Experiments and Database Forming	p. 185
8.4.2 SVM Training and Falling-Down Recognition	p. 188
8.5 Conclusion	p. 189
Index	p. 191

Available:*

On Order

Summary

Summary

Author Notes

Table of Contents