# An intelligent learning approach for improving ECG signal classification and arrhythmia analysis

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/an-intelligent-learning-approach-for-improving-ecg-signal-classification-and/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Arun Kumar Sangaiah,Maheswari Arumugam,Gui‐Bin Bian |
| Citations | 141 |
| DOI | 10.1016/j.artmed.2019.101788 |
| Fields | Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2996862638 |
| PMID | 32143795 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Gui‐Bin Bian](https://scholariq.org/researchers/gui-bin-bian/)

## Paper journal

- [Artificial Intelligence in Medicine](https://scholariq.org/journals/artificial-intelligence-in-medicine/)

## Paper primary topic

- [ECG Monitoring and Analysis](https://scholariq.org/topics/ecg-monitoring-and-analysis/)

## Paper topics

- [ECG Monitoring and Analysis](https://scholariq.org/topics/ecg-monitoring-and-analysis/)
- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)
- [Heart Rate Variability and Autonomic Control](https://scholariq.org/topics/heart-rate-variability-and-autonomic-control/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.