Intelligent Computing for Interactive System Design

Statistics, Digital Signal Processing and Machine Learning in Practice

Parisa Eslambolchilar, Mark Dunlop, Andreas Komninos

• Publisher: ACM Books
• Year: 2021
• eBook ISBN: 9781450390286
• Topic: Computer Science
• Subtopic: Data Mining
• Index: Computer Science

Intelligent Computing for Interactive System Design provides a comprehensive resource on what has become the dominant paradigm in designing novel interaction methods, involving gestures, speech, text, touch and brain-controlled interaction, embedded in innovative and emerging human-computer interfaces. These interfaces support ubiquitous interaction with applications and services running on smartphones, wearables, in-vehicle systems, virtual and augmented reality, robotic systems, the Internet of Things (IoT), and many other domains that are now highly competitive, both in commercial and in research contexts.

This book presents the crucial theoretical foundations needed by any student, researcher, or practitioner working on novel interface design, with chapters on statistical methods, digital signal processing (DSP), and machine learning (ML). These foundations are followed by chapters that discuss case studies on smart cities, brain-computer interfaces, probabilistic mobile text entry, secure gestures, personal context from mobile phones, adaptive touch interfaces, and automotive user interfaces. The case studies chapters also highlight an in-depth look at the practical application of DSP and ML methods used for processing of touch, gesture, biometric, or embedded sensor inputs. A common theme throughout the case studies is ubiquitous support for humans in their daily professional or personal activities.

In addition, the book provides walk-through examples of different DSP and ML techniques and their use in interactive systems. Common terms are defined, and information on practical resources is provided (e.g., software tools, data resources) for hands-on project work to develop and evaluate multimodal and multi-sensor systems. In a series of in-chapter commentary boxes, an expert on the legal and ethical issues explores the emergent deep concerns of the professional community, on how DSP and ML should be adopted and used in socially appropriate ways, to most effectively advance human performance during ubiquitous interaction with omnipresent computers.

This carefully edited collection is written by international experts and pioneers in the fields of DSP and ML. It provides a textbook for students and a reference and technology roadmap for developers and professionals working on interaction design on emerging platforms.

Table of contents

• Cover
• Halftitle
• Title Page
• Copyright Page
• Contents
• Preface
• Introduction
• Ethical Issues in Digital Signal Processing and Machine Learning
• Chapter 1 Internet of Everything
• Chapter 1E The Internet of Everything—Introducing Privacy
• Chapter 2 Statistical Grounding
• Chapter 2E Ethics and Statistics
• Chapter 3 DSP Basics
• Chapter 3E Ethical Issues of Digital Signal Processing
• Chapter 4 Machine Learning Basics
• Chapter 4E Ethical Issues in Machine Learning
• Chapter 5 Combining Infrastructure Sensor and Tourism Market Data in a Smart City Project—Case Study 1
• Chapter 5E Ethics and Smart Cities
• Chapter 6 Brain–Computer Interfacing with Interactive Systems—Case Study 2
• Chapter 6E Ethical Issues in Brain–Computer Interfaces
• Chapter 7 Probabilistic Text Entry—Case Study 3
• Chapter 7E Ethical Issues in Probabilistic Text Entry
• Chapter 8 Secure Gestures—Case Study 4
• Chapter 8E Ethics and Secure Gestures
• Chapter 9 Personal Context from Mobile Phones—Case Study 5
• Chapter 9E Ethics and Personal Context
• Chapter 10 Building Adaptive Touch Interfaces—Case Study 6
• Chapter 10E Ethics and Adaptive Touch Interfaces
• Chapter 11 Driver Cognitive Load Classification Based on Physiological Data—Case Study 7
• Chapter 11E Ethics in Automotive User Interface
• Authors’ Biographies
• Index