Denoising ECG Signal by CSTFM Algorithm: Monitoring During Motorbike and Car Races

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.

• Publication year

  2019

• Venue

  IEEE Transactions on Instrumentation and Measurement

• Publication date

  2019-04-15

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1109/TIM.2019.2906989
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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