Citation

Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study

Author:
Zulueta, John; Piscitello, Andrea; Rasic, Mladen; Easter, Rebecca; Babu, Pallavi; Langenecker, Scott A.; McInnis, Melvin; Ajilore, Olusola; Nelson, Peter C.; Ryan, Kelly; Leow, Alex
Publication:
Journal of Medical Internet Research
Year:
2018

Mood disorders are common and associated with significant morbidity and mortality. Better tools are needed for their diagnosis and treatment. Deeper phenotypic understanding of these disorders is integral to the development of such tools. This study is the first effort to use passively collected mobile phone keyboard activity to build deep digital phenotypes of depression and mania.