Novel delta zero crossing regression features for gait pattern classification

Ronny K. Ibrahim; Vidhyasaharan Sethu; Eliathamby Ambikairajah

doi:10.1109/IEMBS.2010.5626275

Novel delta zero crossing regression features for gait pattern classification

Ronny K. Ibrahim, Vidhyasaharan Sethu, Eliathamby Ambikairajah

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

1 Citation (Scopus)

Abstract

Many recent research works on gait pattern classification indicates that static features are used. This paper describes of extracting novel dynamic features as complimentary features for the gait pattern classification. The dynamic features are obtained by using regression on the delta zero crossing counts (ΔZCC) of the acceleration signal. The classification results using the filterbank features with the novel dynamic features showed an overall accuracy of 97% was achieved. This is an improvement of 3% from using the filterbank features alone.

Original language	English
Title of host publication	2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	2427-2430
Number of pages	4
ISBN (Electronic)	9781424441242
ISBN (Print)	9781424441235
DOIs	https://doi.org/10.1109/IEMBS.2010.5626275
Publication status	Published - 2010
Event	2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina Duration: 31 Aug 2010 → 4 Sept 2010

Other

Other	2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Country/Territory	Argentina
City	Buenos Aires
Period	31/08/10 → 4/09/10

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10.1109/IEMBS.2010.5626275

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Ibrahim, R. K., Sethu, V., & Ambikairajah, E. (2010). Novel delta zero crossing regression features for gait pattern classification. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 (pp. 2427-2430). Article 5626275 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IEMBS.2010.5626275

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title = "Novel delta zero crossing regression features for gait pattern classification",

abstract = "Many recent research works on gait pattern classification indicates that static features are used. This paper describes of extracting novel dynamic features as complimentary features for the gait pattern classification. The dynamic features are obtained by using regression on the delta zero crossing counts (ΔZCC) of the acceleration signal. The classification results using the filterbank features with the novel dynamic features showed an overall accuracy of 97\% was achieved. This is an improvement of 3\% from using the filterbank features alone.",

author = "Ibrahim, \{Ronny K.\} and Vidhyasaharan Sethu and Eliathamby Ambikairajah",

year = "2010",

doi = "10.1109/IEMBS.2010.5626275",

language = "English",

isbn = "9781424441235",

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booktitle = "2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

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note = "2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 ; Conference date: 31-08-2010 Through 04-09-2010",

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Ibrahim, RK, Sethu, V & Ambikairajah, E 2010, Novel delta zero crossing regression features for gait pattern classification. in 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10., 5626275, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 2427-2430, 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10, Buenos Aires, Argentina, 31/08/10. https://doi.org/10.1109/IEMBS.2010.5626275

Novel delta zero crossing regression features for gait pattern classification. / Ibrahim, Ronny K.; Sethu, Vidhyasaharan; Ambikairajah, Eliathamby.
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2010. p. 2427-2430 5626275.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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Y2 - 31 August 2010 through 4 September 2010

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Novel delta zero crossing regression features for gait pattern classification

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