Repository logo
Communities & Collections
Research Outputs
Fundings & Projects
People
Statistics
User Manual
Have you forgotten your password?
  1. Home
  2. Faculty of Computer Science and Engineering
  3. Faculty of Computer Science and Engineering: Conference papers
  4. Optimal Filter Length to Identify Uninterpretable Electrocardiograms
Details

Optimal Filter Length to Identify Uninterpretable Electrocardiograms

Journal
2020 28th Telecommunications Forum (TELFOR)
Date Issued
2020-11-24
Author(s)
Krluku, Era Ajdaraga
DOI
10.1109/telfor51502.2020.9306632
Abstract
The ubiquity of wearable health monitors has drastically improved the quality of life for end-users whose wellbeing relies on continuous monitoring. The main challenge with telemedicine services lies in the quality of the data that the system receives from the user. Therefore, it is paramount that the telehealth processing system has a way to check and identify corrupted data so that it can be corrected or excluded from further processing. The Simple Differential Filter (SDF) aims to solve the challenge of artifact detection in ECG signals. In this paper, we research the optimal value for filter length. This parameter is significant not only because of its implications on performance and accuracy, but memory management in big data systems as well.
Subjects

ECG

artifact detection

signal processing

⠀

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify