development of a fall detecting system for the elderly residents speaker: 林佑威 author: chia-chi...

Development of a Fall Detecting System for the Elderly Residents

speaker: 林佑威

Author:Chia-Chi Wang, Chih-Yen Chiang, Po-Yen Lin, Yi-Chieh Chou, I-Ting Kuo, Chih-Ning Huang, Chia-Tai Chan

  Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on 1

OutlineI. IntroductionII. MethodIII. Experimental ResultsIV. Conclusion

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Introduction 25~35% of elderly residents experienced fall-related injury more

than one time per year.

30~40% of all needed to be hospitalized.

3% of the fallers helplessly lie without any external support for more than 20 minutes

The cost forecasting of medical care for elderly residents’ fall-related injury goes to $43.8 billion by 2020

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Research

(2003) Thomas Degen et al. inlaid two accelerometers into a wrist watch

(2006) C.C. Yanget al. used a triple-axial accelerometer placed at the waist level

(2005) U. Lindemann et al. proposed a pilot study with two accelerometers into the hearing aid housing

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Method

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Sensor Position

Accelerometer has been used in various studies to monitor a range of human movement

The paper Inlaid the accelerometers into the hearing aid housing

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Four Criteria on Fall Detection

A accelerometer was placed above the ear side

The sample rate of the accelerometer was 200Hz.

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X軸

Y軸

Z軸

Four Criteria on Fall Detection

(1).Sum-vector of all axes (Sa): it is used to describe the spatial variation of acceleration during the falling interval.

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Four Criteria on Fall Detection

(2).Sum-vector of horizontal plane (Sh): An acceleration change of the horizontal plane (x-z plane)

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Four Criteria on Fall Detection

Timestamp of falling body to be at rest (Trs) Timestamp of the body’s initial contact to the

ground (Tic)

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Four Criteria on Fall Detection

Backward integration of reference velocity (Vmax)

According to the dynamics of free-falling objects, 0.2 meters height of potential energy completely transformed into kinetic energy may give rise to a velocity of 2 m/s.

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Four Criteria on Fall Detection

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Flow of fall detection

Experimental Results

1.Five volunteers 2.Eight kinds of falling posture 3.Seven daily activities

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Seven daily activities

The seven activities include standing, sitting down, lying down, walking, jumping, going up (down) stairs, and jogging

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Eight kinds of falling posture

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Falling:Right-Side to the Ground

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Lie Down Twice:Slow then Quick

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Experimnets

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Conclusion

These experimental results have demonstrated the proposed falls detection is effective

The algorithm had been accomplished

The data need to be transmitted to the central computer to do further data analysis

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Conclusion

The future work :

1.Bluetooth module

2.Alarm system with VoIP or SMS communications.

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