Research area
Explainable AI for human movement
Model output should be examinable and clinically usable, not a black box. SHAP and related methods applied to gait, physical activity and technical-tactical performance.
Explaining deep learning models for age-related gait classification based on time series acceleration
X Zheng, M Reneman, E Ottem, C Lamoth · Computers in Biology and Medicine, 184, 2025: 109338
SHAP reveals which parts of an acceleration time series a deep network relies on when classifying age-related gait.
Age-related gait patterns classification using deep learning based on time-series data from one accelerometer
X Zheng, E Wilhelm, M Reneman, E Ottem, C Lamoth · Biomedical Signal Processing and Control, 104, 2025: 107406
Deep learning on raw acceleration from a single accelerometer classifies age-related gait patterns without hand-crafted features.
Establishing central sensitization inventory cut-off values in patients with chronic low back pain by unsupervised machine learning
X Zheng, C Lamoth, H Timmerman, E Ottem, M Reneman · Computers in Biology and Medicine, 178, 2024: 108739
Unsupervised clustering establishes Central Sensitization Inventory cut-off values from data rather than expert consensus.
Association between central sensitization and gait in chronic low back pain: Insights from a machine learning approach
X Zheng, M Reneman, J Echeita, R Schiphorst Preuper, H Kruitbosch, E Ottem, C Lamoth · Computers in Biology and Medicine, 144, 2022: 105329
Gait features derived from one accelerometer separate chronic low back pain patients by level of central sensitization; SHAP shows which.
Are Better Game Statistics Equivalent to Key Technical-Tactical Indicators? A SHAP-Based Explanation of Collegiate and Youth 3x3 Basketball Game Outcomes
X Zheng, C Ho, D Beesley, S Yu, L Cheung, R Sum, Y YangIn preparation
Effects of a Customized Multicomponent Physical Activity Program on Gait Pattern Transitions in Long-Term Care Older Adults: A Cluster Randomized Controlled Trial Using Wearable Sensors and Explainable Machine Learning
X Zheng, Z Zeng, C Ho, Z Zhou, Y Yang · JMIR mHealth and uHealth, 2026Under review
