Orhan Konak, M.Sc.

Research Assistant, PhD Candidate

	Phone:	+49 (331) 5509-4826
	Fax:	+49 (331) 5509-163
	Mail:	orhan.konak(at)hpi.de
	Room:	G-2.2.16 (Campus III)
	Profiles:

Research Topics

Machine Learning - Data Augmentation for Human Activity Recognition
Nursing Activity Recognition
Nursing Documentation

Projects

NutriAct

Teaching

Winter 2018/19
- Lecture: Data Management for Digital Health
Summer 2019
- Lecture: Mathematics in Machine Learning
- Seminar: Applied Machine Learning for Digital Health
Winter 2019/20
- Lecture: Data Management for Digital Health
Summer 2020
- Seminar: Applied Machine Learning for Digital Health

Publications

Konak, O., Wegner, P., Arnrich, B.: IMU-Based Movement Trajectory Heatmaps for Human Activity Recognition.Sensors (Switzerland).20,1--15 (2020).
[ BibTeX ]

@article{Konak2020, abstract = {Recent trends in ubiquitous computing have led to a proliferation of studies that focus on human activity recognition (HAR) utilizing inertial sensor data that consist of acceleration, orientation and angular velocity. However, the performances of such approaches are limited by the amount of annotated training data, especially in fields where annotating data is highly time-consuming and requires specialized professionals, such as in healthcare. In image classification, this limitation has been mitigated by powerful oversampling techniques such as data augmentation. Using this technique, this work evaluates to what extent transforming inertial sensor data into movement trajectories and into 2D heatmap images can be advantageous for HAR when data are scarce. A convolutional long short-term memory (ConvLSTM) network that incorporates spatiotemporal correlations was used to classify the heatmap images. Evaluation was carried out on Deep Inertial Poser (DIP), a known dataset composed of inertial sensor data. The results obtained suggest that for datasets with large numbers of subjects, using state-of-the-art methods remains the best alternative. However, a performance advantage was achieved for small datasets, which is usually the case in healthcare. Moreover, movement trajectories provide a visual representation of human activities, which can help researchers to better interpret and analyze motion patterns.}, author = {Konak, Orhan and Wegner, Pit and Arnrich, Bert}, journal = {Sensors (Switzerland)}, keywords = {bertarnrich}, number = 24, pages = {1--15}, title = {IMU-Based Movement Trajectory Heatmaps for Human Activity Recognition}, volume = 20, year = 2020 }
Konak, O., Wegner, P., Arnrich, B.: IMU-Based Movement Trajectory Heatmaps for Human Activity Recognition.Sensors.20,7179 (2020).
[ BibTeX ]

@article{Konak2020, author = {Konak, Orhan and Wegner, Pit and Arnrich, Bert}, journal = {Sensors}, keywords = {arnrich connectedhealth myown sys:relevantfor:dhc bert fb-boettinger}, month = {dec}, number = 24, pages = 7179, publisher = {{MDPI} {AG}}, title = {{IMU}-Based Movement Trajectory Heatmaps for Human Activity Recognition}, volume = 20, year = 2020 }
Freitas da Cruz, H., Bergner, B., Konak, O., Schneider, F., Bode, P., Lempert, C., Schapranow, M.-P.: MORPHER – A Platform to Support Modeling of Outcome and Risk Prediction in Health Research.Proceedings of the 19th IEEE International Conference on Bioinformatics and Biomedicine. , Athens, Greece (2019).
[ BibTeX ]

@conference{freitasdacruz2019morpher, author = {Freitas da Cruz, Harry and Bergner, Benjamin and Konak, Orhan and Schneider, Frederic and Bode, Philipp and Lempert, Conrad and Schapranow, Matthieu-P.}, booktitle = {Proceedings of the 19th IEEE International Conference on Bioinformatics and Biomedicine}, keywords = {myown bigmedilytics fb-boettinger}, title = {MORPHER – A Platform to Support Modeling of Outcome and Risk Prediction in Health Research}, year = 2019 }
Konak, O., Freitas Da Cruz, H., Thiele, M., Golla, D., Schapranow, M.-P.: An Information and Communication Platform Supporting Analytics for Elderly Care.5th International Conference on Information for Ageing Well, Communication Technologies e Health (2019).
[ BibTeX ]

@inproceedings{konak2019information, author = {Konak, Orhan and Freitas Da Cruz, Harry and Thiele, Marvin and Golla, David and Schapranow, Matthieu-P.}, booktitle = {5th International Conference on Information for Ageing Well, Communication Technologies e Health}, keywords = {myown sys:relevantfor:dhc SAHRA fb-boettinger}, title = {An Information and Communication Platform Supporting Analytics for Elderly Care}, year = 2019 }

Orhan Konak, M.Sc.

Research Assistant, PhD Candidate

Research Topics

Projects

Teaching

Publications

Hasso Plattner Institute for Digital Health at Mount Sinai (HPI·MS)

Contact

Chair Representatives

Office:

Office:

Visiting address:

Press and media contact:

News

19.01.2021 | INTERVENE: Verbesserte Krankheitsprävention durch Einsatz von KI und Genomik

11.11.2020 | Neuer HPI Podcast: Wie KI bei der Erkennung psychischer Störungen helfen kann

08.10.2020 | Neuer Co-Direktor des Hasso Plattner Institute for Digital Health at Mount Sinai

04.09.2020 | COVID-19: Wissenschaftler warnen vor akutem Nierenversagen

29.06.2020 | Kostenloser SARS-CoV-2 Test für HPI Mitarbeitende und Studierende