A Contemplative Analysis of Thyroid Disorders based on ECG Signal and Thyroid Test Measure

Authors

  • M. Deepika Vels Institute of Science
  • K. Kalaiselvi Vels Institute of Science

DOI:

https://doi.org/10.4108/eai.1-7-2020.166006

Keywords:

Classification, Data Mining, ECG, Heart rate, Hypothyroid, Hyperthyroid, QRS duration and Thyroid test measures

Abstract

Hypothyroidism can influence the heart and circulatory framework in various manners. Inadequate thyroid hormone eases back the pulse. With the goal of forecasting hypothyroid, by utilizing thyroid measures turns out to be high intricacy in order of Hypothyroid and Hyperthyroid. Some of the common clinically most relevant findings explaining hyperthyroidism as well as hypothyroidism are the anatomic symptoms of the disease of Thyroid disease. Data Mining plays a vital role in the process of prediction and classification. The proposed work utilizes the information mining methods, such as the characterization and expectation by adopting parallel tree calculation. A Trust Region method for Nonlinear Minimization streamlining calculation is incorporated in the count of QRS point discovery in electrocardiogram (ECG) signal. This proposed model is re-enacted on the MATLAB R2014b. This analysis is used to assess the relationship among outright thyroxine (T4) and thyrotropin (TSH) levels with ECG parameters.

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Published

26-08-2020

How to Cite

1.
Deepika M, Kalaiselvi K. A Contemplative Analysis of Thyroid Disorders based on ECG Signal and Thyroid Test Measure. EAI Endorsed Trans Energy Web [Internet]. 2020 Aug. 26 [cited 2024 May 4];8(32):e10. Available from: https://publications.eai.eu/index.php/ew/article/view/823