@inproceedings {26860,
	title = {One-Dimensional Convolutional Neural Networks on Motor Activity Measurements in Detection of Depression},
	journal = {Proceedings of the 4th International Workshop on Multimedia for Personal Health \& Health Care  - HealthMedia {\textquoteright}19},
	year = {2019},
	month = {10/2019},
	pages = {9-15},
	publisher = {ACM Press},
	address = {New York, NY, USA},
	abstract = {Nowadays, it has become possible to measure different human activities using wearable devices. Besides measuring the number of daily steps or calories burned, these datasets have much more potential since different activity levels are also collected. Such data would be helpful in the field of psychology because it can relate to various mental health issues such as changes in mood and stress. In this paper, we present a machine learning approach to detect depression using a dataset with motor activity recordings of one group of people with depression and one group without, i.e., the condition group includes 23 unipolar and bipolar persons, and the control group includes 32 persons without depression. We use convolutional neural networks to classify the depressed and nondepressed patients. Moreover, different levels of depression were classified. Finally, we trained a model that predicts Montgomery{\r A}sberg Depression Rating Scale scores. We achieved an average F1-score of 0.70 for detecting the control and condition groups. The mean squared error for score prediction was approximately 4.0.\&nbsp;},
	isbn = {9781450369145},
	doi = {10.1145/334744410.1145/3347444.3356238},
	url = {http://dl.acm.org/citation.cfm?doid=3347444http://dl.acm.org/citation.cfm?doid=3347444.3356238http://dl.acm.org/ft_gateway.cfm?id=3356238\&ftid=2091091\&dwn=1},
	author = {Joakim Ihle {Frogner} and Farzan Majeed {Noori} and Halvorsen, P{\r a}l and Hicks, Steven and Garcia-Ceja, Enrique and Torresen, Jim and Riegler, Michael},
	editor = {Boll, Susanne and Lee, Jeannie and Meyer, Jochen and Nag, Nitish and Noel E. {O{\textquoteright}Connor}}
}
@inproceedings {26178,
	title = {Medical Multimedia Information Systems (MMIS)},
	journal = {the 2017 ACMProceedings of the 2017 ACM on Multimedia Conference  - MM {\textquoteright}17},
	year = {2017},
	publisher = {ACM Press},
	address = {Mountain View, California, USANew York, New York, USA},
	isbn = {9781450349062},
	doi = {10.1145/312326610.1145/3123266.3130142},
	url = {http://dl.acm.org/citation.cfm?doid=3123266http://dl.acm.org/citation.cfm?doid=3123266.3130142http://dl.acm.org/ft_gateway.cfm?id=3130142\&ftid=1915055\&dwn=1},
	author = {Schoeffmann, Klaus and M{\"u}nzer, Bernd and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Liu, Qiong and Lienhart, Rainer and Wang, Haohong and Sheng-Wei "Kuan-Ta" {Chen} and Boll, Susanne and Chen, Phoebe and Friedland, Gerald and Li, Jia and Yan, Shuicheng}
}
