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Sensors vs. human: comparing sensor based state monitoring with questionnaire based self-assessment in bipolar disorder patients.

, , , , , and . ISWC, page 133-134. ACM, (2014)

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UWB Indoor Location for Monitoring Dementia Patients: The Challenges and Perception of a Real-Life Deployment., , , and . IJACI, 5 (4): 45-59 (2013)I see you: How to improve wearable activity recognition by leveraging information from environmental cameras., , , and . PerCom Workshops, page 409-412. IEEE Computer Society, (2013)What Can an Arm Holster Worn Smart Phone Do for Activity Recognition?, , and . ISWC, page 79-82. IEEE Computer Society, (2011)Sensors vs. human: comparing sensor based state monitoring with questionnaire based self-assessment in bipolar disorder patients., , , , , and . ISWC, page 133-134. ACM, (2014)Using Indoor Location to Assess the State of Dementia Patients: Results and Experience Report from a Long Term, Real World Study., , , and . Intelligent Environments, page 32-39. IEEE Computer Society, (2011)Lifelong Learning and Collaboration of Smart Technical Systems in Open-Ended Environments - Opportunistic Collaborative Interactive Learning., , , , , , , , , and . ICAC, page 315-324. IEEE Computer Society, (2016)Can magnetic field sensors replace gyroscopes in wearable sensing applications?, , , and . ISWC, page 1-4. IEEE Computer Society, (2010)Using smart phone mobility traces for the diagnosis of depressive and manic episodes in bipolar patients., , , , , , , and . AH, page 38:1-38:8. ACM, (2014)Ubiquitous Context Aware Monitoring Systems in Psychiatric and Mental Care: Challenges and Issues of Real Life Deployments., , , and . ICCASA, page 105-109. ACM, (2014)Towards a Real-World Simulator for Collaborative Distributed Learning in the Scenario of Urban Mobility., , and . SASO Workshops, page 44-48. IEEE Computer Society, (2014)