Development of Human Fall Detection System using Joint Height, Joint Velocity, and Joint Position from Depth Maps

Authors

  • Yoosuf Nizam Modeling and Simulation (BIOMEMS) Research Group, Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia.
  • Mohd Norzali Haji Mohd Embedded Computing Systems (EmbCos), Department of Computer Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia.
  • Razali Tomari Advanced Mechatronic Research Group (ADMIRE), Department of Mechatronic and Robotic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia.
  • M. Mahadi Abdul Jamil Modeling and Simulation (BIOMEMS) Research Group, Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia.

Keywords:

Kinect, Velocity, Joint Height, Depth Maps,

Abstract

Human falls are a major health concern in many communities in today’s aging population. There are different approaches used in developing fall detection system such as some sort of wearable, ambient sensor and vision based systems. This paper proposes a vision based human fall detection system using Kinect for Windows. The generated depth stream from the sensor is used in the proposed algorithm to differentiate human fall from other activities based on human Joint height, joint velocity and joint positions. From the experimental results our system was able to achieve an average accuracy of 96.55% with a sensitivity of 100% and specificity of 95%

Downloads

Download data is not yet available.

Downloads

Published

2016-09-01

How to Cite

Nizam, Y., Haji Mohd, M. N., Tomari, R., & Abdul Jamil, M. M. (2016). Development of Human Fall Detection System using Joint Height, Joint Velocity, and Joint Position from Depth Maps. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(6), 125–131. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1260