1. Presenter: Wei-Chen Lin Adviser: Dr. Cheng-Jui Hung
Implementation of a Real-Time Human Movement Classifier Using a Triaxial Accelerometer for Ambulatory Monitoring
Presenter: Wei-Chen Lin Adviser: Dr. Cheng-Jui Hung
2009/2/25

2. Outline Introduction Paper review Motivation and Purpose
Materials and Methods
Results
Future works
References

3. Introduction Triaxial accelerometer applications Numerical Analysis
Experiment
Behavior
Monitoring systems

4. Paper review(1) Purpose
From: Classification of basic daily movements using a triaxial accelerometer Author(s): Mathie MJ, Celler BG, Lovell NH, et al. Source: Medical & Biological Engineering & Computing   Volume: 42   Issue: 5   Pages:   Published: SEP 2004
Purpose
Advances in miniature sensor and wireless technologies have resulted in interest in the development of systems for monitoring subjects over long periods of time using wearable monitoring units.

5. Paper review(1) materials and methods
Waist-mounted triaxial accelerometer
The unit was composed of two orthogonally mounted biaxial accelerometers*(range± 10 g; frequency response: Hz)
Presented a more systematic approach to classification, based on a formal, hierarchical, decision tree.
The algorithms were developed and tested using data collected from 26 normal, healthy subjects (seven female, 19 male; mean age 30.5 years years standard deviation)

6. Paper review(1) flow chart
TA signal
Level 1
Activity? No
Level 2
Activity
Rest
Yes
Upright? No
Fall? No
Lying? No
Walking? No
Yes
Transition? No
Inverted:
Raise alarm
Yes
Yes
Yes
Fall:raise
alarm
walking
Other
movement
Level 3
Yes
Lying face
Down? No
Sitting? No
Upright-
Upright? No
lying on back? No No
Lying on left
side? No
Upright-
Lying? No
Yes
Yes
Yes
Yes
Lying-lying? No
Yes
Yes
Yes
Lying-
Upright?
Yes
Level 4
Yes
Upright-to-
Lying transition
Lying-to-lying
transition
Lying-to-upright
transition
sitting
standing
Lying face
down
Lying on
back
Lying on left
side
Lying on right
side
TA: Triaxial Accelerometer 三軸加速度器

7. Paper review(1) results
Fig.1 Experimental Statistics tables

8. Paper review(1) conclusion
Using this framework, a classifier for the identification of basic movements, based on a monitoring system consisting of a 686 single, waist-mounted triaxial accelerometer, was developed, in laboratory studies in which 26 subjects performed a specific routine of movements, the system obtained an overall sensitivity of 97.7% and specificity of 98.7% over a data set of 1309 movements.

9. Paper review(2) Purpose
From: Alvarez, J.C.; Gonzalez, R.C.; Alvarez, D.; Lopez, A.M.; Rodriguez-Uria, J.; Engineering in Medicine and Biology Society, EMBS th Annual International Conference of the IEEE Aug Page(s):
Purpose
Step lengthcan be computed by means of a biaxial accelerometer and a gyroscope on the sagital plane.

10. Paper review(2) materials and methods
Biaxial accelerometer and a gyroscope
Motion is computed, at every stride, by estimating the distance traveled by the foot that swings forward on the air.
Fig.2 Experimental device

11. Paper review(2) experiments results
ω:角加速度 θ:角度
Fig. 3-4 One foot displacement, signals from the gyroscope (up), its
integration (middle) and the corrected accelerations (down). Computations
are made with equations (2) and (3).

12. Paper review(2) experiments results
Fig. 5 Integrating the gyroscope signal of
the sagital plane

13. Paper review(2) conclusion
We have presented a method to estimate the step length
based on inertial feet attached sensors. Contrary to similar
works, a multisensor approach is applied in order to reduce
uncertainty and to produce better estimations. An adapted
kalman filter based sensor fusion system is proposed. Initial
results are encouraging. Ongoing extended field experiments
have been designed to validate and generalize the results for
a heterogeneous populations and walking conditions.

14. Motivation and Purpose
Monitoring of human movement
Measured distance
Design platform for measuring the distance
To detect the occurrence of falls

15. Materials and Methods ST LIS302DL Measurement platform
3-Axis
range : ± 8g
frequency response:100Hz or 400Hz
Measurement platform
28cm × 21cm × 3.7cm
Microchip APP009
Microchip Dsp30F4011

16. Measurement platform
可移動方向
APP009 實驗版
尺規刻度
三軸加速度器

17. Results
Fig.6 加速度曲線圖
Fig.7 速度曲線圖

18. Results
Fig. 8距離曲線圖

19. Results
The experimental results show that estimated value is measured 9 cm, the actual measurement of 7.8 centimeters. Error value of 11%
Ideal distance
number of measure
experimental
average
accuracy
9 cm 54
7.8 cm
89%

20. Future works Paper review Increase the distance measurement accuracy
Data collection and statistics
Reduce the board
Functional integration

21. References
[1] C.V. Bouten,K. T.Koekkoek, M.Verduin, R.Kodde, and J. D. Janssen, "A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity," IEEE Trans. Biomed. Eng., vol. 44, no. 3, pp. 136–147, 1997.
[2] M. J. Mathie, A. C. F. Coster, N. H. Lovell, and B. G. Celler, "A pilot study of long term monitoring of human movements in the home using accelerometry," IEEE Trans. Biomed. Eng., vol. 10, pp. 144–151, 2004.
[3] M. Makikawa, D. Murakami, " Development of an ambulatory physical activity and behavior map monitoring system," in 18th Annual Conf. IEEE Engineering in Medicine Biology Soc. Amsterdam, Holland, 1996.
[4] M. J.Mathie, N. H. Lovell, A. C. F. Coster, and B. G. Celler, "Determining activity using a triaxial accelerometer," in Proc. 2nd Joint EMBS-BMES Conf., Houston, TX, 2002.
[5] M. J.Mathie, B. G. Celler, N.H. Lovell, et al. "Classification of basic daily movements using a triaxial accelerometer," Medicine & Biological Engineering & Computing., vol. 42  pp , 2004.
[6] W. Zijlstra and A. Hof, "Assessment of spatio-temporal gait parameters from trunk accelerations during human walking," Gait & Posture., vol. 18, pp. 1-10, 2003.

22. Thank you for your
attention