Classification of oscillometric envelope shape using frequent sequence mining

Hung Wen Diao, Weichih Hu, Gong Yau Lan, Liang Yu Shyu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The shape of the oscillometric envelope is known to affect the accuracy of automatic noninvasive blood pressure (NIBP) measurement devices that use the oscillometric principle to determine systolic and diastolic blood pressures. This study proposes a novel shape classification method that uses data mining techniques to determine the characteristic sequences for different envelope shapes. The results indicate that the proposed method effectively determines the characteristic sequences for different subject groups. Subjects in the high- score group and in the low- score group tend to have an envelope with a broader plateau and are bell-shaped, respectively. This information about shape can be used for future determination of the correct algorithm for systolic and diastolic blood pressures determination in NIBP devices.

Original languageEnglish
Title of host publication2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Pages5805-5808
Number of pages4
DOIs
Publication statusPublished - Oct 31 2013
Externally publishedYes
Event2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan
Duration: Jul 3 2013Jul 7 2013

Conference

Conference2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
CountryJapan
CityOsaka
Period7/3/137/7/13

Fingerprint

Blood pressure
Blood Pressure
Blood Pressure Determination
Pressure measurement
Equipment and Supplies
Data Mining
Data mining

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Diao, H. W., Hu, W., Lan, G. Y., & Shyu, L. Y. (2013). Classification of oscillometric envelope shape using frequent sequence mining. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 (pp. 5805-5808). [6610871] https://doi.org/10.1109/EMBC.2013.6610871

Classification of oscillometric envelope shape using frequent sequence mining. / Diao, Hung Wen; Hu, Weichih; Lan, Gong Yau; Shyu, Liang Yu.

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. p. 5805-5808 6610871.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Diao, HW, Hu, W, Lan, GY & Shyu, LY 2013, Classification of oscillometric envelope shape using frequent sequence mining. in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013., 6610871, pp. 5805-5808, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013, Osaka, Japan, 7/3/13. https://doi.org/10.1109/EMBC.2013.6610871
Diao HW, Hu W, Lan GY, Shyu LY. Classification of oscillometric envelope shape using frequent sequence mining. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. p. 5805-5808. 6610871 https://doi.org/10.1109/EMBC.2013.6610871
Diao, Hung Wen ; Hu, Weichih ; Lan, Gong Yau ; Shyu, Liang Yu. / Classification of oscillometric envelope shape using frequent sequence mining. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. pp. 5805-5808
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