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- W3119440015 abstract "The goal of automatic ECG analysis is to assess the clinical status of the heart system as accurately as possible, and the identification of P and T waves plays a significant role in this matter. This works presents original algorithms for the detection of P and T waves. These algorithms are based on the morphological and temporal characteristics of the electrocardiogram. To test and compare the algorithms' performance, we considered the QTDB and MIT-BIH Arrhythmia annotated databases. The developed algorithms obtained a good performance for the detection of both peaks. In particular, in both the QTDB and MIT-BITH database the P wave detection algorithm obtained considerably higher performance than those presented in the literature (QTDB: 95.87% vs 89.05%; MIT-BITH: 84.65% vs 83.36% for Lead 1). The T wave detection algorithm, achieved best performance than those in literature in the QTDB (89.05% vs 87.49%) while in the MIT-BITH database results were almost comparable to those reported in the literature. These findings suggest the high potential of the proposed simple algorithms for P and T wave detection in ECG." @default.
- W3119440015 created "2021-01-18" @default.
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- W3119440015 date "2020-12-30" @default.
- W3119440015 modified "2023-09-23" @default.
- W3119440015 title "Automatic Detection of Characteristic Waves in Electrocardiogram" @default.
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- W3119440015 doi "https://doi.org/10.22489/cinc.2020.174" @default.
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