Digital biomarkers are the user generated physiological and behavioral measures collected via connected digital devices or wearable and mobile computing systems that can be used to explain, influence or predict the health related outcomes. The design and development of digital biomarkers leverages novel hardware or software by rethinking traditional biomarker computing medical instruments. Examples of digital biomarkers include everything from geolocation and physical activity traces to internal physiological processes like vital signs collected by IoT devices, smartphones or novel computational platforms.
A set of accurately and reproducibly measurable digital biomarkers can be used to predict various health conditions, outcomes, and to generate actionable insights. The rich data collected with the built-in sensors and processing units of our smartphones and wearable devices have already shown a lot of promise for passive and continuous measurement of several health biomarkers which can be used to develop all sorts of new health sensing apps and interventions. The workshop aims to advance the science of digital biomarkers by bringing in key technological innovations from the areas of mobile computing, machine learning, health sciences and medicine.
The Workshop on the Future of Digital Biomarkers will offer a unified forum that brings academics, industry researchers and medical practitioners together to explore the role of existing and future mobile technology for modeling, testing, and validating new digital biomarkers. The workshop aims to facilitate a systematic discussion among experts from different knowledge domains including mobile sensing, systems, machine learning, medicine, and health sciences. The workshop aims to (i) identify new digital biomarkers for capturing different physiological and behavioral health conditions and diseases, (ii) identify the key shortcomings of the existing research in terms of scalability, customizability, and sensing affordances, (iii) find realistic solutions by leveraging sensor data from a variety of mobile systems (e.g., smartphones, wearables, and IoT devices), (iv) identify key methodologies for validation and testing of the new biomarker evidence engine.
Predicting the incidence of disease, health conditions, effects of treatments, and interventions with digital biomarkers.
Design and implementation of 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 mis-labeling 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 deadline: May 22, 2021 at 11:59 PM (EDT)
Notification deadline: June 1, 2021
Camera-ready workshop papers due: June 15, 2021
Workshop Dates: June 25, 2021
Registrations for MobiSys 2021 are now open. Please use the following link for more details.
Full research (up to 6 pages) or Industry demo (up to 3 pages) or Position (up to 3 pages) paper using Mobisys format. Papers should be in PDF format.
Keynote: Digital Epidemiology and the COVID-19 Pandemic
Chief Innovation Officer
Harvard Medical School
|9:15-10:30||Social Media Derived Biomarkers of Mental Health: Opportunities, Pitfalls, and the Next Frontier by Munmun De Choudhury|
|10:45-12:00||Full Papers Presentations
|12:00-13:00||Industry and Position Papers Presentations
|13:30-14:45||Digital Epidemiology and the COVID-19 Pandemic by John Brownstein|
|15:00-16:30|| Startup Panel
|16:30-17:15||The Role of Science Policy in Developing Digital Biomarkers by Wendy Nilsen|