research-article

CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia

Authors:

Min S. H. Aung,

Saeed Abdullah,

Andrew T. Campbell,

Tanzeem Choudhury,

Michael Merrill,

Emily A. Scherer,

Vincent W. S. Tseng, and

Dror Ben-ZeevAuthors Info & Claims

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 2016

Pages 886 - 897

https://doi.org/10.1145/2971648.2971740

Published: 12 September 2016 Publication History

Abstract

Early detection of mental health changes in individuals with serious mental illness is critical for effective intervention. CrossCheck is the first step towards the passive monitoring of mental health indicators in patients with schizophrenia and paves the way towards relapse prediction and early intervention. In this paper, we present initial results from an ongoing randomized control trial, where passive smartphone sensor data is collected from 21 outpatients with schizophrenia recently discharged from hospital over a period ranging from 2-8.5 months. Our results indicate that there are statistically significant associations between automatically tracked behavioral features related to sleep, mobility, conversations, smart-phone usage and self-reported indicators of mental health in schizophrenia. Using these features we build inference models capable of accurately predicting aggregated scores of mental health indicators in schizophrenia with a mean error of 7.6% of the score range. Finally, we discuss results on the level of personalization that is needed to account for the known variations within people. We show that by leveraging knowledge from a population with schizophrenia, it is possible to train accurate personalized models that require fewer individual-specific data to quickly adapt to new users.

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Index Terms

CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia
1. Applied computing
  1. Law, social and behavioral sciences
2. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 2016

1288 pages

ISBN:9781450344616

DOI:10.1145/2971648

General Chairs:
Paul Lukowicz
DFKI and University of Kaiserslautern
,
Antonio Krüger
DFKI and Saarland University
,
Program Chairs:
Andreas Bulling
Max Planck Institute for Informatics
,
Youn-Kyung Lim
KAIST
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Shwetak N. Patel
University of Washington

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Published: 12 September 2016

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September 12 - 16, 2016

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UbiComp '16 Paper Acceptance Rate 101 of 389 submissions, 26%;

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https://doi.org/10.3390/s24030722
Khoo LLim MChong CMcNaney R(2024)Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing ApproachesSensors10.3390/s2402034824:2(348)Online publication date: 6-Jan-2024
https://doi.org/10.3390/s24020348
Yin HZhu HGu JQin HDing WGuo NFu JYang Y(2024)Mobile-based ecological momentary assessment and intervention: bibliometric analysisFrontiers in Psychiatry10.3389/fpsyt.2024.130073915Online publication date: 26-Feb-2024
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Mullick TShaaban SRadovic ADoryab A(2024)Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic and Personalized ModelingJMIR AI10.2196/478053(e47805)Online publication date: 20-May-2024
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