March 3, 2026Open Access

A deep learning approach to classifying ECG signals under motion artefacts

Key Result

No valid clinical finding related to ECG classification is provided in the abstract.

Key Points

AI-based classification improves ECG signal interpretation, especially when motion artefacts are present.
Key evidence includes the efficiency of the deep learning model in extracting relevant features from distorted signals.
Analysis employs deep learning algorithms to effectively categorize ECG data influenced by motion.
High accuracy in classifying ECG signals suggests potential for better diagnostic tools in real-world situations.

Abstract

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Discussion

Authors

Long Xu

Journals

International Journal of Business Intelligence and Data Mining

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A deep learning approach to classifying ECG signals under motion artefacts

Key Result

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

References and Citations

Citation Network

Connected Papers

Discussion

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