Project title

Human Activity Recognition using 2D pose analysis

Submitted to:

  • Tapas Badal

Submitted By:

  1. Manikya Verma
  2. Aarushi Phade
  3. Dayaala Joshitha
  4. Praveena K P
  5. Hemanth Janapala

Project Description

The aim of the project is to detect whether the person has heart disease or not by using his ECG wave. This paper proposes a technique for ECG Arrhythmia classification by using 6 recognised machine learning models like SVM,KNN,RF,DT, DA and NB in order to obtain the optimal classifier and its parameters. The proposed techniques uses 7 statistical features namely Mean, Variance,Standard Deviation,Skewness,Kurtosis,energy,entropy rom the QRS complex.

Project Poster

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