Interventions and Contextual Understanding for Low Back Pain Research

ICON

Interventions and Contextual Understanding for Low Back Pain Research (ICON) is aimed at scientific renewal of Low Back Pain research. We combine existing data sources with novel mobile data collection modalities and custom-built crowdsourcing setups to develop an Artificial Intelligence -based solution capable of suggesting just-in-time treatment interventions.

Project information

Project duration

-

Funded by

Multiple sources (Focus area spearhead projects)

Project coordinator

University of Oulu

Contact information

Contact person

  • Simo Hosio

    Associate Professor
    Simo
    Hosio
    simo.hosio@oulu.fi
    +358 294 482522
  • Denzil Ferreira

    Associate Professor
    Denzil
    Ferreira
    denzil.ferreira@oulu.fi
    +358 40 9675202

Researchers

Project description

Interventions and Contextual Understanding for Low Back Pain Research (ICON) is aimed at scientific renewal of Low Back Pain research. We combine existing data sources with novel mobile data collection modalities and custom-built crowdsourcing setups to develop an Artificial Intelligence -based solution capable of suggesting just-in-time treatment interventions. By combining the expertise of the PRIMO research group at the Center for Lifelong Health Research with the vast technological expertise of the Center for Ubiquitous Computing, ICON is a multidisciplinary project with potential to contribute to both fields: medical and computational science.

Selected publications:

Hosio S, Karppinen J, van Berkel N, Oppenlaender J & Goncalves J (2018); Mobile Decision Support and Data Provisioning for Low Back Pain; IEEE Computer, 51(8).

Hosio S, Karppinen J, Takala EP, Takatalo J, Goncalves J, van Berkel N, Konomi S, Kostakos V (2018); Crowdsourcing Treatments for Low Back Pain; Proc. ACM SIGCHI Conference on Human Factors in Computing Systems (CHI 2018).

Ferreira D, Kostakos V, Dey AK (2015): AWARE: mobile context instrumentation framework; Frontiers in ICT 2, 6.

van Berkel N, Ferreira D, Kostakos V (2017); The experience sampling method on mobile devices; ACM Computing Surveys (CSUR) 50 (6), 1-40.

 

Links