Description | Limited personnel resources and costs have a negative impact on the health supply in mental health therapy and intervention programs. People with mental disorders such as dementia, major depression, substance abuse or mental retardation experience serious health-related consequences. For example, depression alone accounts for 4.3% of the global burden of disease and is among the largest single cause of disability worldwide (WHO 2013). As an economic consequence, the increasing prevalence of non-communicable diseases (i.e. non-infectious and non-transmissible among people) to which mental disorders contribute a major extent, is expected to account for a loss of US$ 47 trillion in 2030, i.e. approximately 75% of the global gross domestic product in 2010. A range of web-based mental health interventions emerged over the last couple of years to tackle the problem of health supply shortage. Unfortunately to date, if no extra personal guidance is utilized, they fail to deliver tailored and context sensitive support and therefore have limited potential. With MOSS we try to fill this gap. Using off the shelve smartphone sensors and state of the art machine learning techniques we aim at inferring a users mental state in order to deliver best practices that maximize intervention success. |
Additional Informations | unspecified |
Commencement Date | 1 April 2014 |
Contributors |
Fleisch, Elgar (Project Manager); Kowatsch, Tobias (Project Manager); Wahle, Fabian (Project Worker); Hanulova, Anna (Project Worker); Hörni, Anja (Project Worker) & Schweinfurther, Jost (Project Worker) |
Datestamp |
16 Sep 2022 10:58 |
Completion Date |
31 October 2015 |
HSG Profile Area |
SoM - Business Innovation |
Keywords |
mobile Health, depression, mental health, sensing and support, machine learning |
Methods |
machine learning, data mining, survey |
Funders |
KTI EUREKA |
Partners |
Universitätsspital Zürich, ETH Zürich, makora AG |
Id |
240002 |
Project Range |
HSG Internal |
Project Status |
ongoing |
Subjects |
other research area |
Topics |
mobile Health, depression, mental health, sensing and support, machine learning |
Project Type |
applied research project |
URI |
http://www.health-is.ch/lab/projects/kti-moss/ |