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Application for pre-processing and visualization of electrodermal activity wearable data

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Application for pre-processing and visualization of electrodermal activity wearable data, presentation at 12.6.2017 13:15-14:45 Sonaatti 2, Tampere Hall, Tampere, Finland. EMBEC 2017 conference track on Data Based Analytics in Health care: From Sensors to Big Data.

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Application for pre-processing and visualization of electrodermal activity wearable data

  1. 1. Application for pre-processing and visualization of electrodermal activity wearable data Kari Suoja, Jari Liukkonen, Jari Jussila, Henna Salonius, Niina Venho, Virpi Sillanpää, Vilma Vuori & Nina Helander
  2. 2. Electrodermal activity • Electrodermal activity reflects the activity of the sympathetic nervous system and can be measured through the changes in electrical conductance of the skin 12.6.2017 2 0-20 Calm 21-40 Serene 41-60 Active 61-80 Worked up 81-100 Running high Made simple with the EDA wearable
  3. 3. The measurement instrument 12.6.2017 3 - Prototype found valid for field research by the Finnish Institute of Occupational Health in 2015
  4. 4. Case study – Trade fair • EDA measurement data gathered from 10 sales representatives marketing their company and its services to buyers during one day (ca. 8-10 hours) • These sort of events are usually somewhat hectic and require ongoing focus and attention from the sales personnel aiming to present their offerings to a potential customer in a rather short time-slot, which can be presumed to cause arousal to some extent • Recognized need for automatic pre-processing and visualization of the collected data 12.6.2017 4
  5. 5. From individual to group level 12.6.2017 5 MAANANTAI TIISTAI KESKIVIIKKO TORSTAI PERJANTAI LAUANTAI SUNNUNTAI 19.9. 20.9. 21.9. 22.9. 23.9. 24.9. 25.9. 1 2 3 4 5 6
  6. 6. OSS tool for pre-processing and visualization of wearable data 12.6.2017 6
  7. 7. Multiple overlapping polygon visualizations 12.6.2017 7 Trend curve Flower diagram
  8. 8. Data output in Excel 12.6.2017 8
  9. 9. Tool and Source Code Available 12.6.2017 9https://github.com/KariSuoja/MoodmetricDataViz
  10. 10. Thank you 12.6.2017 10 Contact jari.j.jussila@tut.fi

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