Emotions as a System Regulator for Sustainability: Designing a Tangible Device Capable to Enable Connections

  • Flavio MontagnerEmail author
  • Paolo Tamborrini
  • Andrea Di Salvo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 824)


The research refers to two different initial topics of interest. On the one hand the large-scale diffusion of tracking devices and the growing interest to-wards the movement for the personal quantification, led us to the hypothesis that devices could autonomously analyze not only physical field related data, but also those related to emotions. On the other hand, the development of an intangible and interface-free system that aims to shape the environment around us according to our needs, hypothetically doesn’t require our direct intervention. A so called zero user interface system. In this scenario, the presence of data related to our emotional state, generally referred as mood, could be useful to regulate a system otherwise based on a single automated collection of exogenous values. In this paper we will focus on both on how this theoretical system will work and impact on the sustainability, and how to collect this data in a ideal way.


Wearables Sustainability Zero UI 


  1. 1.
    Bistagnino L (2011) Design sistemico: progettare la sostenibilità produttiva e ambientale. Slow Food, BraGoogle Scholar
  2. 2.
    Germak C (2008) Uomo al centro del progetto: design per un nuovo umanesimo. Allemandi & C, TorinoGoogle Scholar
  3. 3.
    Celaschi F, De Moraes D (2013) Future, well-being, interdependence: keywords for contemporaneous design: Humanismo. Editora da Universidade do Estado de Minas Gerais, Belo Horizonte, Cadernos de Estudos Avançados em DesignGoogle Scholar
  4. 4.
    Tamborrini PM (2009) Design sostenibile. Oggetti, sistemi e comportamenti. Mondadori Electa, MilanoGoogle Scholar
  5. 5.
    Wade J (2017, November 14) Wearable technology statistics and trends 2018.
  6. 6.
    Paterson HM (2002) The perception and cognition of emotion from motion. Doctoral dissertation, University of GlasgowGoogle Scholar
  7. 7.
  8. 8.
  9. 9.
    Berglund ME, Duvall J, Dunne LE (2016) A survey of the historical scope and current trends of wearable technology applications. In: Proceedings of the 2016 ACM international symposium on wearable computers. ACM, pp 40–43Google Scholar
  10. 10.
    IDC report (2017) Worldwide quarterly wearable device trackerGoogle Scholar
  11. 11.
  12. 12.
  13. 13.
  14. 14.
    Googlel Project Jaquard.
  15. 15.
    Zephyr Performance Systems.
  16. 16.
  17. 17.
  18. 18.
    Donald N (2004) Emotional design. Apogeo EditoreGoogle Scholar
  19. 19.
    Jeffs M (2018, April 25) Voice search - growth statistics & how trends in voice search affect SEO.
  20. 20.
    AA. VV. Zero UI (n.d.) Designing invisible interfaces.
  21. 21.
    Marzano S (2014, February 6) Un modo di produrre valore.
  22. 22.
    Rinaldi A (2014) Design innovazione e tecnologie smart per il benessere e la salute”. Doctoral dissertation, Università degli studi di FirenzeGoogle Scholar
  23. 23.
    Weiser M (1991) The computer for the 21st century. Sci Am 265(3):94–105CrossRefGoogle Scholar
  24. 24.
    Ratti C, Claudel M (2015) Futurecra: tomorrow by design. TECHNE-J Technol Arch Environ 10:28–33Google Scholar
  25. 25.
    Ragot M, Martin N, Em S, Pallamin N, Diverrez J-M (2018) Emotion recognition using physiological signals: laboratory vs. wearable sensors. In: Ahram T, Falcão C (eds) AHFE 2017, vol 608. AISC. Springer, Cham, pp 15–22. Scholar
  26. 26.
    Amaya K, Bruderlin A, Calvert T (1996, May) Emotion from motion. In: Graphics interface, vol 96, pp 222–229Google Scholar
  27. 27.
    Ma Y, Paterson HM, Pollick FE (2006) A motion capture library for the study of identity, gender, and emotion perception from biological motion. Behav Res Methods 38(1):134–141CrossRefGoogle Scholar
  28. 28.
    Bernhardt D (2010) Emotion inference from human body motion. Doctoral dissertation, University of CambridgeGoogle Scholar
  29. 29.
    Piana S, Stagliano A, Odone F, Verri A, Camurri A (2014) Real-time automatic emotion recognition from body gestures. arXiv preprint arXiv:1402.5047
  30. 30.
    Buenaflor C, Kim HC (2013) Six human factors to acceptability of wearable computersGoogle Scholar
  31. 31.
    Zeagler C (2017) Where to wear it: functional, technical, and social considerations in on-body location for wearable technology 20 years of designing for wearability. In: Proceedings of the 2017 ACM international symposium on wearable computers. ACMGoogle Scholar
  32. 32.
    Fletcher RR, Kulkarni S (2010, August) Clip-on wireless wearable microwave sensor for ambulatory cardiac monitoring. In: 2010 annual international conference of the IEEE engineering in medicine and biology society (EMBC), IEEE, pp 365–369Google Scholar
  33. 33.
    Zhao M, Adib F, Katabi D (2016, October) Emotion recognition using wireless signals. In: Proceedings of the 22nd annual international conference on mobile computing and networking. ACM, pp 95–108Google Scholar
  34. 34.
    Liu D, Ulrich M (2014) Listen to your heart: stress prediction using consumer heart rate sensorsGoogle Scholar
  35. 35.
    Google Project Soli.
  36. 36.
    Wang S, Song J, Lien J, Poupyrev I, Hilliges O (2016, October) Interacting with soli: exploring fine-grained dynamic gesture recognition in the radio-frequency spectrum. In: Proceedings of the 29th annual symposium on user interface software and technology. ACM, pp 851–860Google Scholar
  37. 37.
    Sterley TL et al (2018) Social transmission and buffering of synaptic changes after stress. Nat Neurosci 1Google Scholar
  38. 38.
  39. 39.
    SparkFun single lead heart rate monitor - AD8232.
  40. 40.
  41. 41.
  42. 42.
  43. 43.
    Diaz J (2018, April 09) Leap motion’s “virtual wearables” may be the future of computing.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.DAD Department of Architecture and DesignPolitecnico di TorinoTurinItaly

Personalised recommendations