Personalizing haptics : from individuals' sense-making schemas to end-user haptic tools
著者
書誌事項
Personalizing haptics : from individuals' sense-making schemas to end-user haptic tools
（Springer series on touch and haptic systems）
Springer Nature Switzerland AG, 2019
- : hbk
大学図書館所蔵 件 / 全2件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references
内容説明・目次
内容説明
This monograph presents a vision for haptic personalization tools and lays the foundations for achieving it. Effective haptic personalization requires a suite of tools unified by one underlying conceptual model that can easily be incorporated into users' workflows with various applications. Toward this vision, the book introduces three mechanisms for haptic personalization and details development of two of them into: 1) an efficient interface for choosing from a large haptic library, and 2) three emotion controls for adjusting haptic signals. A series of quantitative experiments identifies five schemas (engineering, sensation, emotion, metaphor, and usage examples) for how end-users think and talk about haptic sensations and characterizes them as the underlying model for the personalization tools.
Personalizing Haptics highlights the need for scalable haptic evaluation methodologies and presents two methodologies for large-scale in-lab evaluation and online crowdsourcing of haptics. While the work focuses on vibrotactile signals as the most mature and accessible type of haptic feedback for end-users, the concepts and findings extend to other categories of haptics.
Taking haptics to the crowds will require haptic design practices to go beyond the current one-size-fits-all approach to satisfy users' diverse perceptual, functional, and hedonic needs reported in the literature. This book provides a starting point for students, researchers, and practitioners in academia or industry who aim to adapt their haptic and multisensory designs to the needs and preferences of a wide audience.
目次
Introduction.- Linking Emotion Attributes to Engineering Parameters and Individual Differences.- Characterizing Personalization Mechanisms.- Choosing from a Large Library Using Facets.- Deriving Semantics and Interlinkages of Facets.- Crowdsourcing Haptic Data Collection.- Tuning Vibrations with Emotion Controls.- Conclusion and Future Directions.- Supplemental Fact Analysis.- Supplemantal Materials for Tuning Vibrations.
「Nielsen BookData」 より