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Article

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

Journal of medical Internet research - 20 Jul 2018

Zulueta John, Piscitello Andrea, Rasic Mladen, Easter Rebecca, Babu Pallavi, Langenecker Scott A, McInnis Melvin, Ajilore Olusola, Nelson Peter C, Ryan Kelly, Leow Alex

Abstract excerpt

BACKGROUND: 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. OBJECTIVE: The...

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Identifiers

PMID: 30030209
DOI: 10.2196/jmir.9775
PMCID: PMC6076371

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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