Author

Agnes Grünerbl, Gernot Bahle, Raphaela Banzer, Stefan Öhler, Christian Haring, Paul Lukowicz

Abstract

We compare the performance of a smart phone based state and state change detection system to self-assessment and show that the automatic detection is much closer to the objective psychiatric diagnosis. Our work is based on a large, real life dataset collected with 9 real patients with a total of 800 days of data. It consists of smart phone sensor data, a daily self-assessment questionnaire filled out by the patients and is validated by standardized psychiatric scale tests.

BibTex

@inproceedings {Grünerbl:Sensor:2014:7400,
	number = {}, 
	month = {9}, 
	year = {2014}, 
	title = {Sensor vs. Human: Comparing Sensor Based State Monitoring with Questionnaire Based Self-Assessment in Bipolar Disorder Patients}, 
	journal = {}, 
	volume = {}, 
	pages = {}, 
	publisher = {ACM}, 
	author = {Agnes Grünerbl, Gernot Bahle, Raphaela Banzer, Stefan Öhler, Christian Haring, Paul Lukowicz}, 
	keywords = {Smartphone, Context Applications, Emotion Recognition, Health, Mobile Sensing, Sensors}
}