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Preferred Biosignals to Predict Migraine Attack

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Well-Being in the Information Society. Fighting Inequalities (WIS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 907))

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Abstract

Migraine is classified to two classes, with aura and without aura, and migraine seizures last usually several hours. The goal of this study was to identify the most important symptoms of migraine to be monitored by wearable sensors to predict the migraine attack. The purpose of wearable sensors is to guide patients to take the migraine medication in time, and to support their own care. Self-measurement is a growing trend worldwide and sensor technology has been used for several years in activity wristbands, smartphones, rings, mobile phones, and mobile applications. The study was conducted as an operational study, randomised for those who had been diagnosed with migraine by a doctor. The study was divided into two parts, at first a questionnaire was sent to 17 people in social media. On the basis of the questionnaire, a qualitative interview was conducted for 12 persons with migraine. Responses to the questionnaire were compared to the results of the interview, and the answers to the research questions were sought. Migraine patients considered important that device reports quality of sleep, pulse, blood pressure, stress levels, sleep apnea, and energy consumption.

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References

  1. Koskimäki, H., Mönttinen, H., Siirtola, P., Huttunen, H.L., Halonen, R., Röning, J.: Early detection of migraine attacks based on wearable sensors: experiences of data collection using Empatica E4. In: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, pp. 506–511. ACM, September 2017

    Google Scholar 

  2. Na, H.S., Choi, Y.S., Park, T.S.: Mobile robot for personal exercise training in ubiquitous healthcare environment. In: Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human, pp. 742–744. ACM, November 2009

    Google Scholar 

  3. Klasnja, P., Pratt, W.: Managing health with mobile technology. Interactions 21(1), 66–69 (2014). ISSN 1072-5520

    Article  Google Scholar 

  4. Pietrobon, D., Striessnig, J.: Neurobiology of migraine. Nat. Rev. Neurosci. 4(5), 386–398 (2003)

    Article  Google Scholar 

  5. Kaattari, A., Tiirinki, H., Paasivaara, L., Nordstrom, T., Taanila, A.: Major user of primary health care services in Northern Finland birth cohort. Soc. Medicat. Mag. 52(3), 199–200 (2015)

    Google Scholar 

  6. Kallela, M.: What’s new in migraine pathophysiology and genetics. Duodecim 121(6), 665–674 (2005)

    Google Scholar 

  7. Chan, M., Campo, E., Estève, D., Fourniols, J.Y.: Smart homes-current features and future perspectives. Maturitas 64(2), 90–97 (2009)

    Article  Google Scholar 

  8. Linde, M., et al.: The cost of headache disorders in Europe: the Euro-Light project. Eur. J. Neurol. 19(5), 703–711 (2012)

    Article  Google Scholar 

  9. Burstein, R., Collins, B., Jakubowski, M.: Defeating migraine pain with triptans: a race against the development of cutaneous allodynia. Ann. Neurol. 55(1), 19–26 (2004)

    Article  Google Scholar 

  10. Olesen, J., Gustavsson, A., Svensson, M., Wittchen, H.U., Jönsson, B.: The economic cost of brain disorders in Europe. Eur. J. Neurol. 19(1), 155–162 (2012)

    Article  Google Scholar 

  11. Ko, J., Lu, C., Srivastava, M.B., Stankovic, J.A., Terzis, A., Welsh, M.: Wireless sensor networks for healthcare. Proc. IEEE 98(11), 1947–1960 (2010)

    Article  Google Scholar 

  12. Choe, E., Lee, N., Lee, B., Pratt, W., Kientz, J.: Understanding quantified-selfers’ practices in collecting and exploring personal data. In: Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems (CHI 2014), pp. 1143–1152 (2014)

    Google Scholar 

  13. Swan, M.: The quantified self: fundamental disruption in big data science and biological discovery. Big Data 1(2), 85–99 (2013)

    Article  Google Scholar 

  14. Lupton, D.: The diverse domains of quantified selves: self-tracking modes and dataveillance. Econ. Soc. 25(1), 101–1229 (2016)

    Article  Google Scholar 

  15. Rettberg, J.W.: Seeing Ourselves Through Technology: How We Use Selfies, Blogs and Wearable Devices to See and Shape Ourselves. Palgrave Macmillan, London (2014)

    Book  Google Scholar 

  16. Pantzar, M., Ruckenstein, M.: The heart of everyday analytics: emotional, material and practical extensions in self-tracking market. Consum. Mark. Cult. 18(1), 92–109 (2014)

    Article  Google Scholar 

  17. Fritz, T., Huang, E.M., Murphy, G.C., Zimmermann, T.: Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 487–496 (2014)

    Google Scholar 

  18. Yang, H., Yu, J., Zo, H., Choi, M.: User acceptance of wearable devices: an extended perspective of perceived value. Telemat. Inform. 33(2), 256–269 (2016)

    Article  Google Scholar 

  19. Crawford, K., Lingel, J., Karppi, T.: Our metrics, ourselves: a hundred years of self-tracking from the weight scale to the wrist wearable device. Eur. J. Cult. Stud. 18(4–5), 479–496 (2015)

    Article  Google Scholar 

  20. Parviainen, J.: Quantified bodies in the checking loop: analyzing the choreographies of biomonitoring and generating big data. Hum. Technol. 12(1), 56–73 (2016)

    Article  Google Scholar 

  21. Pagán, J., et al.: Robust and accurate modeling approaches for migraine per-patient prediction from ambulatory data. Sensors 15(7), 15419–15442 (2015)

    Article  Google Scholar 

  22. Pagán, J., Risco-Martín, J.L., Moya, J.M., Ayala, J.L.: Grammatical evolutionary techniques for prompt migraine prediction. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 973–980. ACM, July 2016

    Google Scholar 

  23. Huttunen, H.L., Halonen, R., Koskimäki, H.: Exploring use of wearable sensors to identify early symptoms of migraine attack. In: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, pp. 500–505. ACM, September 2017

    Google Scholar 

  24. Krishnamachari, B.: Networking Wireless Sensors. Cambridge University Press, Cambridge (2005)

    Book  Google Scholar 

  25. Bentley, F., et al.: Health mashups: presenting statistical patterns between wellbeing data and context in natural language to promote behavior change. ACM Trans. Comput. Hum. Interact. 20(5), 27 (2013). Article 30. https://doi.org/10.1145/2503823

  26. Mönttinen, H., Koskimäki, H., Siirtola, P., Röning, J.: Electrodermal activity asymmetry in sleep - a case study for migraine detection. In: Eskola, H., Väisänen, O., Viik, J., Hyttinen, J. (eds.) EMBEC & NBC 2017, vol. 65, pp. 835–838. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-5122-7_209

    Chapter  Google Scholar 

  27. Myers, M.D., Newman, M.: The qualitative interview in IS research: examining the craft. Inf. Organ. 17(1), 2–26 (2007)

    Article  Google Scholar 

  28. Gable, G.G.: Integrating case study and survey research methods: an example in information systems. Eur. J. Inf. Syst. 3(2), 112–126 (1994)

    Article  Google Scholar 

  29. Baskerville, R.L.: Investigating information systems with action research. Commun. AIS 2(3es), 4 (1999)

    Google Scholar 

  30. Thiyagaraja, S., Dantu, R.: Finger blood flow monitoring using smart phones. In: Proceedings of the 8th International Conference on Body Area Networks, BodyNets 2013, pp. 237–239, ICST, Brussels, Belgium (2013). ISBN 978-1-936968-89-3


    Google Scholar 

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Authors and Affiliations

  1. University of Oulu, P.O. Box 4500, 90014, Oulu, Finland

    Hanna-Leena Huttunen & Raija Halonen

Authors
  1. Hanna-Leena Huttunen
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  2. Raija Halonen
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Corresponding author

Correspondence to Hanna-Leena Huttunen .

Editor information

Editors and Affiliations

  1. Tampere University of Technology, Tampere, Finland

    Hongxiu Li

  2. University of Iceland, Reykjavik, Iceland

    Ágústa Pálsdóttir

  3. Fachhochschule Flensburg, Flensburg, Schleswig-Holstein, Germany

    Roland Trill

  4. University of Turku, Turku, Finland

    Reima Suomi

  5. Åbo Akademi University, Turku, Finland

    Yevgeniya Amelina

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Huttunen, HL., Halonen, R. (2018). Preferred Biosignals to Predict Migraine Attack. In: Li, H., Pálsdóttir, Á., Trill, R., Suomi, R., Amelina, Y. (eds) Well-Being in the Information Society. Fighting Inequalities. WIS 2018. Communications in Computer and Information Science, vol 907. Springer, Cham. https://doi.org/10.1007/978-3-319-97931-1_16

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  • DOI: https://doi.org/10.1007/978-3-319-97931-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97930-4

  • Online ISBN: 978-3-319-97931-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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