Call for Papers: 1st Workshop on Digital Biomarkers

Papers are now being accepted for the 1st Workshop on Digital Biomarkers, collocated with MobiSys 2017 in Niagara Falls, New York. The workshop offers a unified forum that brings academics, industry researchers and medical practitioners together and seeks novel, innovative and exciting submissions broadly related to the modeling, testing, and validation of new digital biomarkers for predicting incidence of diseases, health conditions, effects of treatments, and interventions. It also aims to start a systematic discussion among experts from different knowledge domains including mobile sensing, systems, machine learning, medicine and health sciences in order to:

  1. Identify new digital biomarkers capturing behavioral health, chronic and degenerative diseases.
  2. Identify the key shortcomings of the existing mobile and wearable sensor systems, and research study software platforms (e.g., ResearchKit and ResearchStack) for digital biomarker inference in terms of scalability, customizability, and sensing affordances.
  3. Find realistic solutions towards building new digital biomarker evidence engine leveraging sensor data from a variety of mobile systems (e.g., smartphones, wearables, IoT devices, or any novel sensor systems).
  4. Identify key data collection, labeling, testing and validation methodologies of the new biomarker evidence engine.

Topics of interest (NOT an exhaustive list):

  • Predicting the incidence of disease, health conditions, effects of treatments, and interventions with digital biomarkers.
  • Design and implementation of the mobile phone, wearable and/or novel embedded systems based computational platforms.
  • Integration of multimodal data from different sensor streams for digital biomarker modeling.
  • Using existing IoT infrastructure for new digital biomarker modeling.
  • Improved data collection, labeling, testing and Validation methodologies for digital biomarker modeling.
  • Novel signal processing or machine learning techniques for digital biomarker modeling.
  • Developing robust biomarker models that can handle data sparsity and mislabeling issues.
  • Energy and resource efficient implementation of biomarker models.
  • Designing and implementing data feedback and visualization for both participants and caregivers.
  • Development of smartphone based automated health interventions with digital biomarkers.

Submission Guidelines
All submissions must be original work not under review at any other workshop, conference, or journal. In addition to complete work, the workshop also encourages innovative work-in-progress submissions. Submissions must be no greater than 6 pages in length and must be a PDF file. Submissions must follow the formatting guidelines at