AiCure Makes Code Open Source to Advance Digital Biomarker Development

AiCure’s OpenDBM is a software package that allows for calculation of digital biomarkers of health and functioning from video or audio of an individual’s behavior. It integrates existing tools for measurement of behavioral characteristics such as facial activity, voice, and movement into a single package for measurement of overall behavior. OpenDBM is designed for ease of use, expanding the availability of such tools to the wider scientific community. Our hope is that it encourages researchers to use objective quantification of behavior in their analyses and through individual contributions becomes a central repository of novel methods in digital phenotyping.

By using OpenDBM, the user is able to input video or audio of an individual’s behavior and from it measure visual and auditory biomarkers of their health, functioning, and disease severity. The package will be hosted on Github, along with instructional tutorials and walkthroughs on how it can be applied on any video or audio dataset.

See OpenDBM on Github!

Facial Activity



Learn More About OpenDBM

Watch our recent training!


Galatzer-Levy, I. R., Abbas, A., Ries, A., Homan, S., Koesmahargyo, V., Yadav, V., Colla, M., Scheerer, H., Vetter, S., Seifritz, E., Scholz, U., & Kleim, B. (2020). Validation of Visual and Auditory Digital Markers of Suicidality in Acutely Suicidal Psychiatric In-Patients. MedRxiv.

Galatzer-Levy, I., Abbas, A., Yadav, V., Koesmahargyo, V., Aghjayan, A., Marecki, S., … & Sauder, C. (2020). Remote digital measurement of visual and auditory markers of Major Depressive Disorder severity and treatment response. medRxiv.

Abbas, A., Yadav, V., Smith, E., Ramjas, E., Rutter, S. B., Benavides, C., … & Perez-Rodriguez, M. M. (2020). Computer vision-based assessment of motor functioning in schizophrenia: Use of smartphones for remote measurement of schizophrenia symptomatology. medRxiv.

Abbas, A., Yadav, V., Perez-Rodriguez, M. M., & Galatzer-Levy, I. (2019). P. 267 Using smartphone-recorded facial and verbal features to predict clinical functioning in individuals with neuropsychiatric disorders. European Neuropsychopharmacology, 29, S199.

Levy, I. G., Yadav, V., Abbas, A., Koesmahargyo, V., & Kalali, A. (2019, December). Digital Markers of Motor Activity Captured Over Smartphone is Associated With Negative Symptoms of Schizophrenia: Results From a Pilot Observational Study. In Neuropsychopharmacology (Vol. 44, No. SUPPL 1, pp. 348-349).

Stay updated on OpenDBM: