A Study on Human Fall Detection Systems: Daily Activity Classification and Sensing Techniques

  • Yoosuf Nizam Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
  • Mohd Norzali Haji Mohd Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
  • M. Mahadi Abdul Jamil Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
Keywords: Fall Detection, Algorithm, Approach, Depth Sensor, Assistive technology *

Abstract

Fall detection for elderly is a major topic as far as assistive technologies are concerned. This is due to the high demand for the products and technologies related to fall detection with the ageing population around the globe. This paper gives a review of previous works on human fall detection devices and a preliminary results from a developing depth sensor based device. The three main approaches used in fall detection devices such as wearable based devices, ambient based devices and vision based devices are identified along with the sensors employed.  The frameworks and algorithms applied in each of the approaches and their uniqueness is also illustrated. After studying the performance and the shortcoming of the available systems a future solution using depth sensor is also proposed with preliminary results.

Author Biographies

Yoosuf Nizam, Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.

Biomedical Engineering Modeling and Simulation (BIOMEMS) Research Group, Faculty of Electrical and Electronic Engineering

Mohd Norzali Haji Mohd, Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
Biomedical Engineering Modeling and Simulation (BIOMEMS) Research Group, Embedded Computing Systems (EmbCos), Faculty of Electrical and Electronic Engineering,
M. Mahadi Abdul Jamil, Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
Biomedical Engineering Modeling and Simulation (BIOMEMS) Research Group, Faculty of Electrical and Electronic Engineering,
Published
2016-04-01
How to Cite
Nizam, Y., Haji Mohd, M. N., & Abdul Jamil, M. M. (2016). A Study on Human Fall Detection Systems: Daily Activity Classification and Sensing Techniques. International Journal of Integrated Engineering, 8(1). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/1332
Section
Issue on Electrical and Electronic Engineering