Students Activity Recognition by Heart Rate Monitoring in Classroom using K-Means Classification

Abstract

Background: Heartbeat playing the main roles in our life. With the heartbeat, the anxiety level can be known. Most of the heartbeat is used in the exercise. Heart rate measurement is unique and uncontrollable by any human being.Objective: This research aims to learn student's actions by monitoring the heart rate. In this paper, we are measuring the student reaction and action in classroom can give impact on teacher's way of delivery when in the teaching session. In monitoring, student's behavior may give feedback whether the teaching session have positive or negative outcome.Methods: The method we use is K-Means algorithm. Firstly, we need to know the student's normal heartbeat as benchmark. We used Hexiware for collecting data from students' hear beat. We perform the classification where K is benchmark students' heartbeat. K-Means algorithm performs classification of the heart rate measurement of students.Results: We did the testing for five students in different subjects. It shows that all students have anxiety during the testing and presentation. Its consistency because we tested 5 students with mixes activities in the classroom, where the student has quiz, presentation and only teaching.Conclusion: Heart rate during studying in the classroom can change the education world in improving the efficiency of knowledge transfer between student and teacher. This research may act as basic way in monitoring student behavior in the classroom. We have tested for 5 students. Three students have their anxiety in classroom during the exam, presentation, and question. Two students have normal rate during the seminar and lecturer. The drawback, Hexiware is capturing average of ten minutes and tested in different classes and students. In future, we need just measure one student for all the subjects and Hexiware need to configure in one minute.