Heli Koskimäki, Henna Mönttinen, Pekka Siirtola, Hanna-Leena Huttunen, Raija Halonen, and Juha Röning. 2017. 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 (UbiComp '17). ACM, New York, NY, USA, 506-511. DOI: https://doi.org/10.1145/3123024.3124434
Early detection of migraine attacks based on wearable sensors : experiences of data collection using Empatica E4
|Author:||Koskimäki, Heli1; Mönttinen, Henna1; Siirtola, Pekka1;|
1University of Oulu, PO Box 4500, 90014 University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2017101750117
Association for Computing Machinery,
|Publish Date:|| 2017-10-17
The migraine is a chronic, incapacitating neurovascular disorder, characterized by attacks of severe headache and autonomic nervous system dysfunction, concerning 15% of people in developed countries. It is one of the most understated and incapacitating diseases in the world and costing yearly 111 Billion Euros in Europe only. In our study, we discarded the mechanisms affecting to the migraine but instead the focus was on early detection of the attacks by using human measured biosignals. By using a single, easy and comfortable wearable sensor device the aim was to develop a model that assists individuals to take their medication on time and hence help to avoid the pain in migraine. In this paper, a preliminary study concept is presented as well as the experiences of the data collection using Empatica E4 device is carried out. The experiences are introduced from the point of view of the researchers themselves but also the volunteers actually using the device answered to a short survey about the usability issues as well as gave opinions of the future migraine detection device itself.
|Pages:||506 - 511|
Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
The authors would like to thank the Finnish Funding Agency for Technology and Innovation and Infotech of Oulu for funding this work.
© Koskimäki et al. 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published inProceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (UbiComp '17), https://doi.org/10.1145/3123024.3124434.