Authors:
Edith Maier
1
;
Ulrich Reimer
1
;
Emanuele Laurenzi
1
;
Monika Ridinger
2
and
Tom Ulmer
3
Affiliations:
1
University of Applied Sciences St. Gallen, Switzerland
;
2
University of Regensburg, Germany
;
3
myVitali ag, Switzerland
Keyword(s):
Sensor-based Application, Stress Management, Relapse Prevention, Ambulatory Monitoring, Mobile Health, Data Analysis, User Adaptation, Pattern Recognition.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Cloud Computing
;
Distributed and Mobile Software Systems
;
e-Health
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Mobile Technologies
;
Mobile Technologies for Healthcare Applications
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition and Machine Learning
;
P-Health (Personal Health)
;
Platforms and Applications
;
Sensors-Based Applications
;
Software Engineering
Abstract:
The paper describes the development of a mobile solution based on smartphones and sensors for the early recognition of stress. The solution is based on real-time capture and analysis of vital data such as heart rate variability as well as activity and contextual data such as location and time of day. Individual recognition patterns for stress are derived from combining vital and contextual data by using subjective stress assessments via mood maps as additional input during an initial learning phase. The reliability of stress alerts and therapeutic impact will be tested in a clinic specialised on the treatment of alcoholics since stress tends to cause craving and therefore trigger relapses.