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• W2945951802 abstract "mHealth technology, by using habitual devices, i.e., smartphones, improves prevention, diagnosis, treatment, monitoring, and management of health. Monitoring heart profile during intense sports activities allows to diagnose pathologies, not identifiable with the traditional Holter approach and, therefore, it can help preventing possible injuries. On the other hand, denoising and extracting features from electrocardiographic (ECG) signal acquired during physical activity is a challenging task due to motion artifacts and measurement noise. In this paper, we propose a solution enabling a complete analysis of ECG signal through the implementation of a robust denoising algorithm, which has been characterized on synthetic signals and then has been tested on real traces acquired with a low-cost smartphone-based device during motorbike and car races." @default.
• W2945951802 created "2019-05-29" @default.
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• W2945951802 date "2019-07-01" @default.
• W2945951802 modified "2023-09-30" @default.
• W2945951802 title "Denoising ECG Signal by CSTFM Algorithm: Monitoring During Motorbike and Car Races" @default.
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• W2945951802 doi "https://doi.org/10.1109/tim.2019.2906989" @default.
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