Conclusions 
If the impulse response is checked regularly in rehabilitation 
process, it will allow us to make a new evaluation of walking 
stability. The impulse response analysis on walking stability 
suggested new potential for the understanding of medical 
recovery. 
The stability of COG suggested the stability of human 
movement balance and also the power spectral analysis utilizing 
AR modelling provides clear results for the medical evaluation 
for human movement. It is well known that the //f appears in 
stable and normal biological conditions. It is recognized that 
the power spectral analysis expresses characteristics of 
sequential system decomposing into periodic components. The 
present systems using accelerometers and gyro sensor for 
analysing human movement stability provide more diverse, and 
a new method medical evaluation. for improvement in 
rehabilitation and physical fitness. 
References 
Davenpor W.B, Jr., W.L. Root, 1987. An Introduction to the 
Theory of Random Signals and Noise, IEEE Press., New York, 
NY. 
G. Kitagawa, Gersch, W., 1996. Smoothness Priors Analysis of 
Time Series, Lecture Notes in Statistics 116, Springer-Verlag 
Inc., New York, NY, 
Tsuruoka, M., R. Shibasaki, S. Murai, T. Wada, 1997. Spectral 
Analysis of Standing Balance using Medical Stereo Images, In: 
Archives of 19th Annual International Conference of the IEEE 
Engineering in Medicine and Biology Society, Chicago, USA, , 
pp. 1671-1674. 
Tsuruoka, M., R. Shibasaki, S. Murai, T. Wada, 1998. Bio- 
Feedback Control Analysis of Postural Stability using CCD 
Video Cameras and a Force-Plate Sensor Synchronized System, 
In: Archives of IEEE International Conference on Systems, 
Man, and Cybernetics, San Diego, USA, pp. 3200-3205. 
Tsuruoka, M., Y.Yasuoka, R. Shibasaki, S. Murai, and Y. 
Tsuruoka, 2000. Analysis of 1/f Fluctuation in Walking using 
Gyro Sensor System, Proceedings of 13th IEEE Symposium on 
Computer-Based Medical Systems, pp.77 - 82,Houston, Texas, 
USA, June 22-24. 
Tsuruoka, Y., Y. Tamura, S. Minakuchi, and M. Tsuruoka, 
2001. Time Series Analysis of Bio-Medical Signals, Proceedings 
of 14th IEEE Symposium on Computer-Based Medical Systems, 
pp. 97-102, N.I.H. Bethesda, Maryland, USA, July 25-28. 
Acknowledgments 
The authors would like to thank Dr. Chen Tianen for technical 
programming. We also would like to thank Dr. Chiaki Kudoh, 
P.T. Shuji Awata and Makoto Iritani for medical discussion. 
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