UNBOXING THE „BLACK-BOX“: EXPLAINING MACHINE LEARNING MODELS IN HUMAN MOVEMENT ANALYSIS

D. Slijepčević

St. Pölten University of Applied Sciences, Austria

SUPPORT VECTOR MACHINE APPLIED TO FRAGILE X EMG DATA: A MACHINE LEARNING APPROACH USING DYNAMIC TIME WARPING

F. Beghetti¹, F. Spolaor^1,2, V. Liani³, R. Polli^2,3, D. Varagnolo^1,4, Z. Sawacha¹

¹Department of Information Engineering, University of Padova, Italy; ²Pediatric Research Institute Città della Speranza, Padova, Italy; ³Department of Women’s and Children’s Health, University of Padova, Padova, Italy; ⁴Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway

DEEP NEURAL NETWORK TO PREDICT GROUND REACTION FORCES FROM PRESSURE MAPS DURING GAIT

P. Rudolf von Rohr^1,2, J. Romkes^1,2, E. Viehweger^1,2, M. Sangeux^1,2

¹University Children's Hospital Basel, Switzerland; ²Department of biomedical engineering, University of Basel, Switzerland

UNVEILING THE OPTIMAL SENSOR CONFIGURATION IN RUNNING: AN EXPLAINABLE AI TOOL FOR LOWER BODY JOINT ANGLE ESTIMATION

X. Song¹, F. J. Wouda^1,2, J. Reenalda¹

¹Biomedical Signals and Systems Group, University of Twente, The Netherlands; ²Movella Technologies B.V., The Netherlands

PREDICTION OF KNEE MOMENTS POST-TOTAL KNEE ARTHROPLASTY USING WEARABLE SENSORS AND MACHINE LEARNING

S. Fahmawy, A. Sabaty, S. Batcir, A. Fishman, A. G Fischer

Technion Israel Institute Of Technology, Israel

PATIENT-SPECIFIC DIGITAL HUMAN TWINS BASED ON THERMODYNAMICS-INFORMED GRAPH-NEURAL NETWORKS

L. Tesan¹, D. González¹, E. Cueto¹, P. Martins^1,2

¹ESI Group-UZ Chair of the National Strategy of AI. Instituto de Investigación en Ingeniería de Aragón (I3A). Universidad de Zaragoza, Spain; ²Aragonese Foundation for Research and Development (ARAID), Aragón, Spain

KNEE JOINT KINETICS PREDICTION USING SINGLE KINEMATIC INPUT DURING GAIT THROUGH DEEP LEARNING MODELS

A. A. V. Hulleck, A. Alshehhi, R. Katmah, M. Abdullah, M. El Rich, K. Khalaf

Khalifa University, United Arab Emirates