The following publications are possibly variants of this publication:
- Classification of Gait Patterns Using Kinematic and Kinetic Features, Gait Dynamics and Neural Networks in Patients with Unilateral Anterior Cruciate Ligament DeficiencyWei Zeng, Shiek Abdullah Ismail, Yoong Ping Lim, Richard Smith, Evangelos Pappas. npl, 50(1):887-909, 2019. [doi]
- Detecting the presence of anterior cruciate ligament injury based on gait dynamics disparity and neural networksWei Zeng, Shiek Abdullah Ismail, Evangelos Pappas. air, 53(5):3153-3176, 2020. [doi]
- Detecting the presence of anterior cruciate ligament deficiency based on a double pendulum model, intrinsic time-scale decomposition (ITD) and neural networksWei Zeng, Shiek Abdullah Ismail, Evangelos Pappas. air, 53(5):3231-3253, 2020. [doi]
- Efficient Subject-Independent Detection of Anterior Cruciate Ligament Deficiency Based on Marine Predator Algorithm and Support Vector MachineGengyuan Wang, Xiaolong Zeng, Guanquan Lai, Guoqing Zhong, Ke Ma, Yu Zhang. titb, 26(10):4936-4947, 2022. [doi]
- Classification of gait patterns between patients with Parkinson's disease and healthy controls using phase space reconstruction (PSR), empirical mode decomposition (EMD) and neural networksWei Zeng, Chengzhi Yuan, Qinghui Wang, Fenglin Liu, Ying Wang. NN, 111:64-76, 2019. [doi]