Falling Person Detection Using Multi-sensor Signal Processing

B.Ugur Toreyin,E Birey Soyer,A Enis Cetin,Ibrahim Onaran

doi:10.1109/siu.2007.4298709

Abstract

Falls are one of the most important problems for frail and elderly people living independently. Early detection of falls is vital to provide a safe and active lifestyle for elderly. In this paper, signals produced by sound and passive infrared (PIR) sensors are simultaneously analyzed to detect suddenly falling elderly people. A typical room in a supportive home can be equipped with sound and PIR sensors. Hidden Markov models are trained for regular and unusual activities of an elderly person and a pet for each sensor signal. Decisions of HMMs can be fused together to reach a final decision.

Highlights

Detection of a falling person in an unsupervised area is a practical problem with applications in safety and security areas including supportive home environments
A combination of passive infrared (PIR), sound, and vibration sensors provide an efficient solution for fall detection
Models for sound and PIR sensor types are trained with four two-minute-long recordings of walking, falling, and speech signals of a single person and random activities of a pet

Summary

INTRODUCTION

Detection of a falling person in an unsupervised area is a practical problem with applications in safety and security areas including supportive home environments. Used worn sensors include passive infrared sensors, accelerometers, and pressure pads [1–5]. They may produce false alarms and elderly people forget wearing them very often. A combination of passive infrared (PIR), sound, and vibration sensors provide an efficient solution for fall detection. Signals produced by these sensors are simultaneously analyzed to detect falling elderly people. Sound sensors can capture a fall on hard floors. PIR sensors detect the motion in a room but they cannot as reliably distinguish the motion of a pet from the owner as a sound sensor or a vibration sensor.

ANALYSIS OF THE SOUND SENSOR SIGNAL

PIR SENSOR DATA PROCESSING

VIBRATION SENSOR DATA PROCESSING

EXPERIMENTAL RESULTS

CONCLUSION