Paper Info
Title
Mental Health Decline Prediction A Smart Sensor For Day To Day Activity Recognition
Abstract
The ambulatory activity of a person may be used as one component within an overall wearable sensor system that predicts the onset of mental health problems. Ergonomic smart sensors that can determine the total energy expenditure and type of ambulation may provide unique insights to the coping behaviour of stressed people. Rather than relying on wearable computers, a single smart miniature sensor that is worn 24/7 should perform the complex embedded recognition tasks while meeting difficult battery life, wireless communications and ergonomic constraints. The development and testing of such a smart sensor is described which takes into account action timeline variations, as well as action variations both intra individual and inter individual.
Year
Venue
Keywords
2011
HEALTHINF 2011: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON HEALTH INFORMATICS
Mental health, Depression, Activity sensing, Wearable Smart sensor
Field
DocType
Citations 
Total energy expenditure,Wireless,Activity recognition,Wearable computer,Simulation,Computer science,Knowledge management,Timeline,Human–computer interaction,Sensor system,Mental health,Coping behaviour
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Thomas Kaegi-Trachsel100.68
Jürg Gutknecht213732.23
Dennis Majoe36810.20