Physigrams: Modelling Physical Device Characteristics Interaction

  • Alan Dix
  • Masitah Ghazali
Part of the Human–Computer Interaction Series book series (HCIS)


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.


Wind Turbine Logical State Control Panel Nuclear Power Station Physical Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Early parts of this work were supported by the AHRC/EPSRC funded project DEPtH “Designing for Physicality” ( We are very grateful for insightful comments from the reviewers.


  1. Buxton W (1990) A three-state model of graphical input. In: Proceedings of human–computer interaction—INTERACT’90. Elsevier, Amsterdam, pp 449–456Google Scholar
  2. Cauchi A, Oladimeji P, Niezen G, Thimbleby H (2014) Triangulating empirical and analytic techniques for improving number entry user interfaces. In: Proceedings of the 2014 ACM SIGCHI symposium on engineering interactive computing systems (EICS ‘14), ACM, NY, USA, 243–252. doi: 10.1145/2607023.2607025
  3. Dix A (1991) Formal methods for interactive systems. Academic Press, New York.
  4. Dix A, Abowd G (1996) Modelling status and event behaviour of interactive systems. Softw Eng J 11(6):334–346.
  5. Dix A, Finlay J, Abowd G, Beale R (2004) Human–computer interaction. 3rd edn. Prentice Hall, Englewood Cliffs.
  6. Dix A (2007) Designing for appropriation. In: Proceedings of BCS HCI 2007, People and computers XXI, vol 2. BCS eWiC.
  7. Dix A, Ghazali M, Gill S, Hare J, Ramduny-Ellis S (2009) Physigrams: modelling devices for natural interaction. Formal Aspects Comput Springer 21(6):613–641CrossRefzbMATHGoogle Scholar
  8. Eslambolchilar P (2006) Making sense of interaction using a model-based approach. PhD thesis, Hamilton Institute, National University of Ireland, NUIM, IrelandGoogle Scholar
  9. Gaver W (1991) Technology affordances. Proceedings of the SIGCHI conference on Human factors in computing systems (CHI’91). ACM Press, New York, pp 79–84Google Scholar
  10. Ghazali M (2007) Discovering physical visceral qualities for natural interaction. PhD thesis, Lancaster University, England, UKGoogle Scholar
  11. Ghazali M, Dix A, Gilleade K (2015) The relationship of physicality and its underlying mapping. ARPN J Eng Appl Sci 10(23):18095–18103Google Scholar
  12. Gibson J (1979) The ecological approach to visual perception. Houghton Mifflin Company, USAGoogle Scholar
  13. Green T, Petri M (1996) Usability analysis of visual programming environments: a ‘cognitive dimensions’ framework. J Vis Languages Comput 7:131–174CrossRefGoogle Scholar
  14. Harel D (1987) Statecharts: a visual formalism for complex systems. Sci Comput Program 8(3):231–274. doi: 10.1016/0167-6423(87)90035-9 MathSciNetCrossRefzbMATHGoogle Scholar
  15. Massink M, Duke D, Smith S (1999) Towards hybrid interface specification for virtual environments. In: DSV-IS 1999 design, specification and verification of interactive systems, Springer, Berlin, p 30–51Google Scholar
  16. Norman D (1988) The psychology of everyday things. Basic Books, New York 1988Google Scholar
  17. Norman D (1999) Affordance, conventions, and design. Interactions, vol 6. no. 3:38–43, ACM Press: NYGoogle Scholar
  18. Oladimeji P, Thimbleby H, Cox A (2011) Number entry interfaces and their effects on error detection. In: IFIP conference on human-computer interaction, Springer, HeidelbergGoogle Scholar
  19. Pfaff G, ten Hagen P (eds) (1985) Seeheim workshop on user interface management systems. Springer, BerlinzbMATHGoogle Scholar
  20. Shneiderman B, Plaisant C (2010) Designing the user interface: strategies for effective human-computer interaction, 5th edn. Addison-Wesley, MAGoogle Scholar
  21. Smith S (2006) Exploring the specification of haptic interaction. in Interactive systems: design, specification and verification (DSVIS 2006). Lecture notes in computer science, vol 4323. Springer, Berlin, pp 171–184CrossRefGoogle Scholar
  22. Thimbleby H (2007) Using the fitts law with state transition systems to find optimal task timings. In: Proceedings of second international workshop on formal methods for interactive systems, FMIS2007.
  23. TREL (2016) Tilley, Our turbine. tiree renewable energy limited. 24/4/2016. Accessed 24 Mar 2016
  24. Willans J, Harrison M (2000) Verifying the behaviour of virtual world objects. In: Proceedings of DSV-IS’2000. Springer, Berlin, pp 65–77Google Scholar
  25. Wüthrich C (1999) An analysis and model of 3D interaction methods and devices for virtual reality. In: Proceedings of DSV-IS’99. Springer, Berlin, pp 18–29Google Scholar
  26. Zhou W, Reisinger J, Peer A, Hirche S (2014) Interaction-based dynamic measurement of haptic characteristics of control elements. In: Auvray M, Duriez C (eds) Haptics: neuroscience, devices, modeling, and applications: 9th international conference, EuroHaptics 2014, Versailles, France, June 24–26, 2014, Proceedings, Part I, p 177–184. Springer, Berlin. doi: 10.1007/978-3-662-44193-0_23

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Computer ScienceUniversity of BirminghamBirminghamUK
  2. 2.Talis Ltd. BirminghamBirminghamUK
  3. 3.University of Technology MalaysiaJohorMalaysia

Personalised recommendations