New technique for real-time interface pressure analysis: Getting more out of large image data sets

Kath Bogie, Xiaofeng Wang, Baowei Fei, Jiayang Sun

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Recent technological improvements have led to increasing clinical use of interface pressure mapping for seating pressure evaluation, which often requires repeated assessments. However, clinical conditions cannot be controlled as closely as research settings, thereby creating challenges to statistical analysis of data. A multistage longitudinal analysis and self-registration (LASR) technique is introduced that emphasizes real-time interface pressure image analysis in three dimensions. Suitable for use in clinical settings, LASR is composed of several modern statistical components, including a segmentation method. The robustness of our segmentation method is also shown. Application of LASR to analysis of data from neuromuscular electrical stimulation (NMES) experiments confirms that NMES improves static seating pressure distributions in the sacral-ischial region over time. Dynamic NMES also improves weight-shifting over time. These changes may reduce the risk of pressure ulcer development.

Original languageEnglish (US)
Pages (from-to)523-536
Number of pages14
JournalJournal of Rehabilitation Research and Development
Volume45
Issue number4
DOIs
StatePublished - 2008
Externally publishedYes

Keywords

  • Biomedical imaging
  • Gluteal stimulation
  • Interface pressure mapping
  • LASR
  • Longitudinal analysis and self-registration
  • Neuromuscular electrical stimulation
  • Pressure ulcers
  • Real-time statistical analysis
  • Rehabilitation
  • Seating pressure
  • Self-registration
  • Translational research

ASJC Scopus subject areas

  • Rehabilitation

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