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A genetic algorithm-based feature selection method for human identification based on ground reaction force
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ACM/SIGEVO Summit on Genetic and Evolutionary Computation archive
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation table of contents
Shanghai, China
SESSION: Full papers table of contents
Pages 665-670  
Year of Publication: 2009
ISBN:978-1-60558-326-6
Authors
Su Xu  The Key lab of Biomimetic Sensing and Advanced Robot Tech, Inst. of Intel Machines, Chinese Academy of Science, Hefei, Anhui, China
Xu Zhou  The Key lab of Biomimetic Sensing and Advanced Robot Tech, Inst. of Intel Machines, Chinese Academy of Science, Hefei, Anhui, China
Yi-ning Sun  The Key lab of Biomimetic Sensing and Advanced Robot Tech, Inst. of Intel Machines, Chinese Academy of Science, Hefei, Anhui, China
Sponsors
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Biometrics-based identification is a promising technology. Ground reaction force (GRF), with its characteristics of non-invasion, easily measurement and low environment-affection, shows a potential in this field. Feature selection is an important step in biometrics-based identification. In this paper, a genetic algorithm-based feature selection method was discussed. The proposed algorithm has the advantage of finding small subsets of features that perform well in identification. Two contrast experiments were conducted to show the effectiveness of the algorithm, which shows that with GA, higher identification accuracy and smaller feature size were reached


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Tian Jie, Yang Xing. Theories and Applications of Biometrics Identification Technologies. Beijing: publishing house of electronics industry, 2005.9: 2
 
2
Michael S. Orendurff, Greta C. Bernatz, Jason A. Schoen, Glenn K. Klute. Kinetic mechanisms to alter walking speed. Gait & Posture 27 (2008) 603--610
 
3
Kirtley C, Whittle MW, Jefferson RJ. Influence of walking speed on gait parameters. J Biomed Eng. 1985; 7: 282--288
 
4
T S Keller, A M Weisberger, J L Ray, S S Hasan, R G Shiavi,D M Spengler. Relationship between vertical ground reaction force and speed during walking, slow jogging, and running. Clinical Eiomerhanics Vol. 11. No. 5, pp. ?S3--259, 1996
 
5
White R,Agouris I.The Variability of Force Platform Data in Normal and Cerebral Palsy Gait{J}.Clinical Biomechanics,1999,14:185--192
 
6
Evie Vereecke, Kristiaan D'Août, Dirk De Clercq, Linda Van Elsacker, Peter Aerts. The Relationship between Speed, Contact Time and Peak Plantar Pressure in Terrestrial Walking of Bonobos. Clinical BiomeChanics Vol. 11. No. 5, pp. 253--259, 1996
 
7
Julie EP James OH Brian LD, Simultaneous measurement of plantar pressure and shear forces in diabetic individuals. Gait&posture 2002: 15:101--107
 
8
Metin Yavuz,, Azita Tajaddini, Georgeanne Botek, Brian L. Davis. "Temporal characteristics of plantar shear distribution: Relevance to diabetic patients," Journal of Biomechanics, vol. 41, no. 3, 2008, p 556--559
 
9
Muniz, A. M. S.; Manfio, E. F.; Andrade, M. C.; Nadal, J.; Principal Component Analysis of Vertical Ground Reaction Force: A Powerful Method to Discriminate Normal and Abnormal Gait and Assess Treatment. 28th Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, Aug. 30 2006--Sept. 3 2006 Page(s):2683 -- 2686
 
10
P . Akashi , I . Sacco , R . Watari , E . Hennig. The effect of diabetic neuropathy and previous foot ulceration in EMG and ground reaction forces during gait. Clinical Biomechanics , 23(5) :584 -- 592
 
11
 
12
 
13
 
14
 
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