Personal Identification via Heartbeat Signal
| Autor: | Bin Li, Shi-Jinn Horng, Xuan-Zi Hu, Naixue Xiong |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Heartbeat
Biometrics business.industry Computer science Feature extraction 020206 networking & telecommunications Pattern recognition 02 engineering and technology Signal Random forest Identification (information) Naive Bayes classifier ComputingMethodologies_PATTERNRECOGNITION Computer Science::Computer Vision and Pattern Recognition Multilayer perceptron 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | PAAP |
| DOI: | 10.1109/paap.2018.00034 |
| Popis: | This study is trying to improve the biometric system using the heartbeat signal. The proposed algorithm calculates the contribution of all extracted features to biometric recognition. The efficiency of the proposed algorithms is demonstrated by the experiment results obtained from the Multilayer Perceptron, Naive Bayes and Random Forest classifier applications based on the extracted features. The results were evaluated via the Multilayer Perceptron, Naive Bayes and Random Forest classifier models; the true positive rates are then 94.6078%, 92.1569% and 90.3922%, respectively. Compared to existing methods, the proposed method has the better results. |
| Databáze: | OpenAIRE |
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