Expertise
Medicine & Life Sciences
# Gait
# Horses
# Machine Learning
Physics & Astronomy
# Gait
# Horses
Engineering & Materials Science
# Body Sensor Networks
# Network Protocols
# Units Of Measurement
Organisations
Publications
Recent
Parmentier, J. I. M.
, Bosch, S.
, Zwaag, B. J. V. D., Weishaupt, M. A., Gmel, A. I.
, Havinga, P. J. M., Weeren, P. R. V., & Serra Bragança, F. M. (2023).
Prediction of continuous and discrete kinetic parameters in horses from inertial measurement units data using recurrent artificial neural networks.
Scientific reports,
13(1), 740. [740].
https://doi.org/10.1038/s41598-023-27899-4
Darbandi, H., Braganca, F. S.
, van der Zwaag, B. J.
, & Havinga, P. (2022).
Accurate Horse Gait Event Estimation Using an Inertial Sensor Mounted on Different Body Locations. In
Proceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022 (pp. 329-335). (Proceedings IEEE International Conference on Smart Computing, SMARTCOMP; Vol. 2022). IEEE.
https://doi.org/10.1109/SMARTCOMP55677.2022.00076
Darbandi, H., Serra Bragança, F. M.
, van der Zwaag, B. J., Rhodin, M., Hernlund, E., Hobbs, S. J., Clayton, H. M.
, & Havinga, P. J. M. (2022).
Estimation of hoof-on/off moments using inertial sensors and deep learning.
Comparative Exercise Physiology,
18(Suppl. 1), S54-S54.
https://doi.org/10.3920/cep2022.s1
Parmentier, J. I. M., Serra Bragança, F. M.
, & van der Zwaag, B. J. (2022).
Benchmarking feature selection algorithms for optimal classification and dataset comprehension: a biomechanical application.
Computer methods in biomechanics and biomedical engineering,
25(Suppl. 1), S245-S247.
https://doi.org/10.1080/10255842.2022.2116885
Parmentier, J. I. M.
, Zwaag, B. J. V. D., Weishaupt, M. A., Gmel, A. I.
, Havinga, P. J. M., van Weeren, P. R., & Serra Bragança, F. M. (2022).
Prediction of kinetic parameters from body mounted IMU data using recurrent neural networks.
Comparative Exercise Physiology,
18(Suppl. 1), S45-S45.
https://doi.org/10.3920/cep2022.s1
Darbandi, H., Bragança, F. S.
, van der Zwaag, B. J., Voskamp, J., Gmel, A. I., Haraldsdóttir, E. H.
, & Havinga, P. (2021).
Using different combinations of body-mounted IMU sensors to estimate speed of horses: A machine learning approach.
Sensors (Switzerland),
21(3), [798].
https://doi.org/10.3390/s21030798
Serra Bragança, F. M., Broomé, S., Rhodin, M., Björnsdóttir, S., Gunnarsson, V., Voskamp, J. P., Persson-Sjodin, E., Back, W., Lindgren, G., Novoa-Bravo, M., Roepstorff, C.
, van der Zwaag, B. J., Van Weeren, P. R., & Hernlund, E. (2020).
Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning.
Scientific reports,
10(1), [17785].
https://doi.org/10.1038/s41598-020-73215-9
Adin, I., Scheers, B., Sanchez, J. M., Ferreira, J.
, Van der Zwag, B. J., De Wulf, D., & Attema, Y. (2019).
AIOSAT - Autonomous Indoor & Outdoor Safety Tracking System. In Z. Franco, J. J. Gonzalez, & J. H. Canos (Eds.),
ISCRAM 2019 - Proceedings: 16th International Conference on Information Systems for Crisis Response and Management (pp. 1409-1410). (Proceedings of the International ISCRAM Conference; Vol. 2019-May). Information Systems for Crisis Response and Management, ISCRAM.
Maleki, E., Belkadi, F., Boli, N.
, Van Der Zwaag, B. J., Alexopoulos, K., Koukas, S.
, Marin-Perianu, M., Bernard, A., & Mourtzis, D. (2018).
Ontology-Based Framework Enabling Smart Product-Service Systems: Application of Sensing Systems for Machine Health Monitoring.
IEEE Internet of Things Journal,
5(6), 4496-4505. [8352684].
https://doi.org/10.1109/JIOT.2018.2831279
Bosch, S., Serra Bragança, F.
, Marin-Perianu, M.
, Marin-Perianu, R.
, van der Zwaag, B. J., Voskamp, J., Back, W., Van Weeren, R.
, & Havinga, P. (2018).
Equimoves: A wireless networked inertial measurement system for objective examination of horse gait.
Sensors (Switzerland),
18(3), [850].
https://doi.org/10.3390/s18030850
UT Research Information System
Courses Academic Year 2022/2023
Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
Courses Academic Year 2021/2022
Contact Details
Visiting Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(building no. 11), room 5015
Hallenweg 19
7522NH Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
5015
P.O. Box 217
7500 AE Enschede
The Netherlands