Changhe Zhang
Orcid: 0000-0001-7046-9240
According to our database1,
Changhe Zhang
authored at least 13 papers
between 2021 and 2026.
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Bibliography
2026
Lower limb Locomotion Mode Recognition based on sEMG: A pilot study in healthy individuals and stroke patients.
Biomed. Signal Process. Control., 2026
2025
Temporal-constrained parallel graph neural networks for recognizing motion patterns and gait phases in class-imbalanced scenarios.
Eng. Appl. Artif. Intell., 2025
2024
Interpretable Dual-branch EMGNet: A transfer learning-based network for inter-subject lower limb motion intention recognition.
Eng. Appl. Artif. Intell., 2024
Dynamic graph topology generating mechanism: Framework for feature-level multimodal information fusion applied to lower-limb activity recognition.
Eng. Appl. Artif. Intell., 2024
Exploration of deep learning-driven multimodal information fusion frameworks and their application in lower limb motion recognition.
Biomed. Signal Process. Control., 2024
Decoding of lower limb continuous movement intention from multi-channel sEMG and design of adaptive exoskeleton controller.
Biomed. Signal Process. Control., 2024
Parallel Graph Neural Networks: Class-Imbalanced Gait Phase Recognition via Adaptive Fusion of Multimodal sEMG and Kinematic Data.
Proceedings of the 30th International Conference on Mechatronics and Machine Vision in Practice, 2024
End-to-End Hand Gesture Recognition Based on Dynamic Graph Topology Generating Mechanism and Weighted Graph Isomorphism Network.
Proceedings of the 30th International Conference on Mechatronics and Machine Vision in Practice, 2024
Exploration of Adaptive sEMG Denoising and Deep Learning Paradigms and Their Application in Lower Limb Motion Recognition.
Proceedings of the 30th International Conference on Mechatronics and Machine Vision in Practice, 2024
2023
An end-to-end lower limb activity recognition framework based on sEMG data augmentation and enhanced CapsNet.
Expert Syst. Appl., October, 2023
Entropy, September, 2023
SKND-TSACNN: A novel time-scale adaptive CNN framework for fault diagnosis of rotating machinery.
Knowl. Based Syst., 2023
2021
IEEE Trans. Instrum. Meas., 2021