Head of Research Group: Dr. László Bálint GRAND
Members of the Group: Yara GODA, Dominik HOMOKI, Gábor NAGY
Contact: grand.laszlo.balint@itk.ppke.hu
The Sport Bionics and Data Intelligence Lab focuses on objective, data-driven assessment of human movement and performance in sport and rehabilitation. Our research combines data from wearable sensors (IMU, EMG, ECG/HRV) and video-based measurements with markerless and marker-based motion analysis, machine learning, and deep learning. Current application areas include biomechanical analysis in kayak-canoe and swimming, sport analytics based on underwater and above-water camera systems, monitoring of fatigue and technical efficiency, and quantitative assessment of movement disorders and rehabilitation processes. The methods developed in the lab aim to turn large-scale multimodal datasets into interpretable feedback for athletes, coaches, clinical partners, and researchers. Our work is strongly application-oriented: we integrate sensor-based data acquisition, computer vision, biomechanical modeling, and cloud-based processing into systems that support performance improvement, injury prevention, and the evaluation of therapeutic effectiveness.
Multimodal movement analysis in sport and rehabilitation by combining wearable sensors, video-based tracking, and machine learning.
Future research directions, collaboration opportunities
The lab offers collaboration with sports clubs, clinical partners, research institutes, and industry teams in multimodal movement measurement, sport analytics, rehabilitation monitoring, and AI-based data processing. We are open to joint grant proposals, student projects, and validation studies.
Key publications
- Nagy, G., Katona, P., Gannorouwa, L., Grand, L. (2025). Machine Learning-Based Stroke Segmentation in Kayaking Using Integrated IMU and EMG Data. ICSPORTS 2025, pp. 256-264.
- Négyesi, J., Petró, B., Salman, D. N., Khandoker, A., Katona, P., Wang, Z., Almaazmi, A. I. S. Q., Hortobágyi, T., Váczi, M., Rácz, K., Pálya, Z., Grand, L., Kiss, R. M., Nagatomi, R. (2022). Biosig-nal processing methods to explore the effects of side-dominance on patterns of bi-and unilateral standing stability in healthy young adults. FRONTIERS IN PHYSIOLOGY, 13, 965702.
- Nagy, G., Komka, Z., Szathmáry, G., Katona, P., Gannoruwa, L., Erdős, G., Tarjányi, P., Tóth, M., Krepuska, M., Grand, L. (2020). Multimodal Approach for Kayaking Performance Analysis and Improvement. INTERNATIONAL JOURNAL OF COMPUTER SCIENCE IN SPORT, 19(2), pp. 51-76.
