Title Page -- Copyright Page -- Preface -- Introduction -- Table of Contents -- List of authors -- Part I - The evolution and design of service robots in health care: evaluating the role of speech and other modalities in human-robot interaction -- 1  - A critical analysis of speech-based interaction in healthcare robots: making a case for the increased use of speech in medical and assistive robots -- 1.1 Introduction -- 1.2 Background -- 1.2.1 Robots and health care -- 1.2.2 Speech-based interaction with machines -- 1.2.3 Technologies for spoken interaction with machines -- 1.3 Spoken interaction in healthcare robots - a brief review -- 1.3.1 Method -- 1.3.2 Overview of results -- 1.3.3 Findings -- 1.4 Discussion -- 1.4.1 Strengths -- 1.4.2 Weaknesses -- 1.4.3 Opportunities -- 1.4.4 Threats -- 1.5 Charting out a roadmap -- 1.5.1 Future directions: a roadmap -- 1.5.1.1 Evolution of speech and language technologies -- 1.5.1.2 More natural spoken interaction -- 1.5.1.3 Integrate into a multimodal interaction -- 1.5.1.4 Connect robots to services supporting speech interaction -- 1.5.1.5 Interaction design -- 1.5.1.6 Reduce the gap between robotic technology, health care and the users -- 1.5.2 Conclusion -- Acknowledgments -- References -- 2 - Speech-based interaction with service robots: a survey of methods and approaches -- 2.1 Introduction -- 2.2 Methods and approaches -- 2.2.1 Command interpretation -- 2.2.1.1 Speech acts and probabilistic logic -- 2.2.1.2 Semantics and pragmatics of pick-and-place tasks -- 2.2.1.3 Interpretation of location and direction instructions -- 2.2.1.4 Extraction of spatial description clauses from linguistic input -- 2.2.1.5 Passive knowledge rarefication with direct memory access parsing -- 2.2.2 Command disambiguation -- 2.2.2.1 Template-based disambiguation -- 2.2.2.2 Disambiguation through NP grounding.

2.2.2.3 Symbol grounding with probabilistic graphical models -- 2.2.3 Dialogue with the user -- 2.2.3.1 Spatial dialogue with 2D Sonar grid models -- 2.2.3.2 Human-robot interaction through gesture-free spoken dialogue -- 2.3 Talk the walk: robotic NLP vs. human sublanguage acquisition -- 2.3.1 Interaction with bystanders -- 2.3.2 Corpus-based robotics -- 2.3.3 Sublanguage acquisition -- 2.4 Discussion -- 2.4.1 User command disambiguation -- 2.4.2 User command disambiguation -- 2.4.3 Dialogue with the user -- 2.4.4 Sublanguage acquisition -- References -- 3 - Improving patient-robot interaction in health care: service robot feature effects on patient acceptance and emotional responses -- 3.1 Introduction -- 3.1.1 Motivation -- 3.1.2 Current state of PRI in healthcare-related tasks -- 3.1.2.1 Telemedicine/Telepresence -- 3.1.2.2 Intelligent walker -- 3.1.2.3 Cognitive reminder -- 3.1.2.4 Social interaction and therapy -- 3.2 Design requirements and existing system guidelines -- 3.2.1 Role of human emotion in acceptance of robots in healthcare applications -- 3.2.1.1 Design of robot anthropomorphic features and effects on human responses -- 3.2.1.2 Design of robot etiquette and effects on human responses -- 3.2.2 Other constraints on robots in healthcare environments -- 3.3 System evaluation methodologies -- 3.3.1 Task performance -- 3.3.2 User compliance -- 3.3.3 Perceived anthropomorphism -- 3.3.4 Emotional response evaluation -- 3.3.4.1 Perceived emotional responses -- 3.3.4.2 Physiological responses -- 3.3.4.2.1 Cardiovascular activity -- 3.3.4.2.2 Eyeblinks -- 3.3.4.2.3 Neurofeedback -- 3.3.4.2.4 Galvanic skin response (GSR) -- 3.3.4.2.5 Skin temperature -- 3.3.4.2.6 Muscle activity -- 3.3.4.2.7 Respiration -- 3.4 Case studies of robot feature designs on patient psychological experiences -- 3.4.1 Humanoid features in robots for medicine delivery.

3.4.2 Combined humanoid features in robots for medicine delivery -- 3.4.3 Linguistic etiquette strategies in PRI -- 3.5 Summary of system design recommendations and an integrated design approach -- 3.5.1 Design recommendations on humanoid features in robot design -- 3.5.2 Design recommendations on robot etiquette strategies -- 3.5.3 Design recommendations on robot hardware and functions -- 3.5.4 Integrated design recommendations -- 3.6 Conclusion -- References -- 4 - Designing embodied and virtual agents for the operating room: taking a closer look at multimodal medical-service robots and other cyber-physical systems -- 4.1 Introduction -- 4.2 Background -- 4.3 Design of surgical robots -- 4.3.1 Types of surgical robots -- 4.3.2 Challenges and solutions -- 4.4 Conceptual modeling as a way to determine modalities of communication -- 4.4.1 Definition and terminology -- 4.4.2 A visual example -- 4.5 Importance of embodiment in human-machine interaction -- 4.6 Analyzing the performance of three cyber-physical systems designed for the operating room -- 4.6.1 Gestix -- 4.6.2 Gestonurse -- 4.6.3 Telementoring -- 4.7 Discussion and conclusions -- Acknowledgments -- References -- Part II - Design and usability of medical and assistive robots in elder care: reporting on case studies and pilot test results -- 5  - The emerging role of robotics for personal health management in the older-adult population -- 5.1 Introduction -- 5.2 Review of literature: robots and elder care -- 5.2.1 Telehome health -- 5.2.2 Socially assistive robots for treating dementia in the elderly -- 5.2.3 Using robots for elder care: ethical considerations -- 5.2.4 Using robots for elder care: acceptance -- 5.2.5 Using robots for elder care: effectiveness -- 5.2.6 Design of robotic systems for elder care -- 5.3 Our exploratory study with users of eldercare robots -- 5.3.1 Study design.

5.3.2 Study subjects -- 5.3.3 Study results -- 5.4 Conclusions -- References -- 6 - Enabling older adults to interact with robots: why input methods are critical for usability -- 6.1 Introduction -- 6.2 Considerations for choosing which input method to use -- 6.3 Defining older adult capabilities and limitations -- 6.3.1 Vision limitations -- 6.3.2 Auditory limitations -- 6.3.3 Motor limitations -- 6.4 Task requirements: how robots can help older adults -- 6.5 Robot capability and design -- 6.6 Choosing the right input methods -- 6.7 Conclusion -- Acknowledgments -- References -- 7 - Human-robot interaction for assistance with activities of daily living: a case study of the socially and cognitively engaging Brian 2.1 in the long-term care setting -- 7.1 Introduction -- 7.2 Background -- 7.3 Brian 2.1 -- 7.3.1 Socially assistive behaviors of Brian 2.1 -- 7.3.1.1 Memory card game -- 7.3.1.2 Meal-eating activity -- 7.4 Experiments -- 7.4.1 Memory game user study -- 7.4.1.1 Methods and participants -- 7.4.1.2 Results -- 7.4.2 One-on-one meal-eating activity -- 7.4.2.1 Methods and participants -- 7.4.2.2 Results -- 7.5 Discussion -- 7.6 Conclusion -- References -- Part III - Speech-driven companion robots for children with medical and neurodevelopmental disorders: presenting empirical findings of EU-sponsored projects and prototypes -- 8 - Voice-enabled assistive robots for handling autism spectrum conditions: an examination of the role of prosody -- 8.1 Introduction -- 8.2 Background: the role of information communication technology for diagnosing and treating ASC -- 8.3 Anthropomorphic, non-anthropomorphic, and non-biomimetic assistive robots -- 8.4 Adding prosody to socially assistive robots: challenges and solutions -- 8.4.1 Automatic recognition of intonation contour in atypical children's voice using static and dynamic machine learning algorithms.

8.4.2 Automatic recognition of emotions in atypical children's voice -- 8.4.3 Automatic diagnosis of atypical children's voice -- 8.4.4 The acoustics of eye contact -- 8.5 Limitations -- 8.6 Conclusions -- Acknowledgments -- References -- 9 - ASR and TTS for voice controlled child-robot interactions in Italian: empirical study findings on the Aliz-e project for treating children with metabolic disorders in the hospital setting -- 9.1 Aliz-e Project -- 9.1.1 Description of the Quiz Game -- 9.1.2 The Aliz-e integrated system -- 9.1.3 Speech technology in Aliz-e -- 9.2 Automatic speech recognition -- 9.2.1 Children's speech recognition -- 9.2.2 Data collection -- 9.2.3 Julius -- 9.2.4 ASR component -- 9.2.5 Acoustic model -- 9.2.6 Language model -- 9.2.7 Adaptation -- 9.2.8 ASR results -- 9.3 Text-to-speech synthesis -- 9.3.1 Italian MaryTTS NLP modules -- 9.3.2 Italian corpus based HMM voice -- 9.3.3 Signal-driven TTS training -- 9.3.4 Integration in the robotic environment -- 9.3.5 Flexible TTS for Aliz-e -- 9.4 Conclusion -- Acknowledgment -- References -- Editor's biography.