Project title
Human Activity Recognition using 2D pose analysis
Submitted to:
- Tapas Badal
Submitted By:
- Manikya Verma
- Aarushi Phade
- Dayaala Joshitha
- Praveena K P
- 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
