Abstract

Abstract: This year it is ten years since smartphones became widely available as an open platform and have since then been used for creating novel personalised health applications. From the very beginning, there has been an interest in exploiting the advantages of mobile and wearable technologies in mental health to unobtrusively sense and analyse human behaviour, assess and predict mental health status, and to deliver feedback and intervention when needed.

In this talk, I look back on the last decade of Ubicomp research in mental health and use this as an stepping stone for discussing current and future research opportunities. The historical review is based on two recent surveys that I’ve been part of. The first survey presents a review of 45 systems presented over the years and investigate which mental health disease they are designed for, as well as their technical features in terms of sensing, prediction, intervention, and clinical assessment [1]. The second survey investigate whether changes in depressive symptoms can be detected by monitoring the patient’s behaviour using mobile and wearable technology – a core research goal in early research. We reviewed 46 studies, collection more than 17 different features and investigated whether these many studies agree on the relationship between depressive symptoms and patient behaviour collected from mobile and wearable devices. The review shows agreement across studies that some behaviour is strongly correlated to changes in depressive symptoms, while others show no or conflicting correlation [2].

Based on these two surveys, I will discuss current opportunities for research in ubicomp and mental health. In particular I will provide an example of moving from sensing to intervention technology and will present our current technological work in supporting this.

1. Bardram JE, Matic A. A Decade of Ubiquitous Computing Research in Mental Health. Unpublished manuscript. 2019.

2. Rohani DA, Faurholt-Jepsen M, Kessing LV, Bardram JE. Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review. JMIR Mhealth Uhealth 2018;6(8):e165. DOI : 10.2196/mhealth.9691. PMID : 30104184

Bio: Jakob E. Bardram, PhD, is a professor in computer science at the Technical University of Denmark [www.dtu.dk], adjunct professor in public health at the Faculty of Health and Medical Sciences at the University of Copenhagen [www.sund.ku.dk], and the director of the Copehagen Center for Health Technology [www.cachet.dk]. He is the co-founder of Cetrea and Monsenso [monsenso.com], where he is serving as board member and chief scientific officer. His main research areas are software architecture, mobile & ubiquitous computing, and user interface software technology with a focus on healthcare, ranging from activity-based software architectures for electronic medical records, to interactive displays for clinical logistics in hospitals, and to personal health technology for mental health. Read more on his home page [www.bardram.net] and google scholar [scholar.google.dk/citations?user=pRriaUQAAAAJ].