Assessment of Human Activity Recognition based on Impact of Feature Extraction Prediction Accuracy
P. William, Govinda Rajulu Lanke, Dibyhash Bordoloi, Anurag Shrivastava, Arun Pratap Srivastavaa, Sheetal Vishal Deshmukh · 2023
Recognition of human activities by analyzing smartphone data which is being collected via accelerometer and gyroscopic sensors has been a critical area of research and it has been providing solutions to various real-world problems in various domains like healthcare and others. For accurate prediction of human activities, the data is collected using accelerometer and gyroscopic sensor from a smartphone and a feature vector of size 561 is created. A set of features is calculated over this data. In this paper, a systematic analysis of these features is being done and an extensive result on how the choice of features affects the recognition accuracy for various human activities is being provided.