XIAOPING ZHENG

(郑潇平)

Contact

My name is Xiaoping Zheng, a Ph.D. student at the department of Human movement sciences at University of Groningen. My supervisors are Prof. Dr. Claudine Lamoth, Prof. Dr. Michiel Reneman and Prof. Dr. Bert Otten.
  My research focuses on the intersection of Human movement sciences, AI, and wearable sensors. I am particularly interested in employing machine learning methods to analyze the movement characteristics of patients with Low Back Pain during daily life environments based on wearable sensor data.
  I obtained the B.E degree and the M.E degree from China University of Geosciences (Wuhan).

PUBLICATIONS

• Journals
• Conferences

Explainable Artificial Intelligence in movement sciences: focusing on gait analysis in healthy older adults and patients with back pain

X Zheng

PhD Thesis

Explaining Deep Learning Models for Age-related Gait Classification based on time series acceleration

X Zheng, CJC Lamoth, Hans Timmerman,E Otten, MF Reneman

preprint

Establishing Central Sensitization Inventory Cut-off Values in patients with Chronic Low Back Pain by Unsupervised Machine Learning

X Zheng, CJC Lamoth, Hans Timmerman,E Otten, MF Reneman

preprint

Age-related Gait Patterns Classification Using Deep Learning Based on Time-series Data from One Accelerometer

X Zheng, E Wilhelm, MF Reneman, E Otten, CJC Lamoth

preprint

Relationship Between Physical Activity Intensity Patterns and Central Sensitization in Patients with Chronic Low Back Pain: Insights from A Machine Learning Approach

X Zheng, MF Reneman, RHRS Preuper, E Otten, CJC Lamoth

Computer Methods and Programs in Biomedicine, 2023

Association between central sensitization and gait in chronic low back pain: Insights from a machine learning approach

X Zheng, MF Reneman, JA Echeita, RHRS Preuper, H Kruitbosch, E Otten, CJC Lamoth

Computers in biology and medicine, 2022

Path distance-based map matching for Wi-Fi fingerprinting positioning

P Chen, X Zheng, F Gu, J Shang

Future Generation Computer Systems, 2020

HTrack : An Efficient Heading-Aided Map Matching for Indoor Localization and Tracking

Y Wu, P Chen, F Gu, X Zheng, J Shang

IEEE Sensors Journal, 2019