Physigrams: Modelling Physical Device Characteristics Interaction

HANDBOOK OF FORMAL METHODS IN HUMAN-COMPUTER INTERACTION(2017)

引用 6|浏览11
暂无评分
摘要
In industrial control rooms, in our living rooms, and in our pockets, the devices that surround us combine physical controls with digital functionality. The use of a device, including its safety, usability and user experience, is a product of the conjoint behaviour of the physical and digital aspects of the device. However, this is often complex; there are multiple feedback pathways, from the look, sound and feel of the physical controls themselves, to digital displays or the effect of computation on physical actuators such as a washing machine or nuclear power station. Physigrams allow us to focus on the first of these, the very direct interaction potential of the controls themselves, initially divorced from any further electronic or digital effects-that is studying the device 'unplugged'. This modelling uses a variant of state transition networks, but customised to deal with physical rather than logical actions. This physical-level model can then be connected to underlying logical action models as are commonly found in formal user interface modelling. This chapter describes the multiple feedback loops between users and systems, highlighting the physical and digital channels and the different effects on the user. It then demonstrates physigrams using a small number of increasingly complex examples. The techniques developed are then applied to the control panel of a wind turbine. Finally, it discusses a number of the open problems in using this kind of framework. This will include practical issues such as level of detail and times when it feels natural to let some of the digital state 'bleed back' into a physigram. It will also include theoretical issues, notably the problem of having a sufficiently rich semantic model to incorporate analogue input/output such as variable finger pressure. The latter connects back to earlier streams of work on status-event analysis.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要