Towards an intelligent system for clinical guidance on wheelchair tilt and recline usage

Jicheng Fu, Paul Wiechmann, Yih Kuen Jan, Maria Jones

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

Abstract

We propose to construct an intelligent system for clinical guidance on how to effectively use power wheelchair tilt and recline functions. The motivations fall into the following two aspects. (1) People with spinal cord injury (SCI) are vulnerable to pressure ulcers. SCI can lead to structural and functional changes below the injury level that may predispose individuals to tissue breakdown. As a result, pressure ulcers can significantly affect the quality of life, including pain, infection, altered body image, and even mortality. (2) Clinically, wheelchair power seat function, i.e., tilt and recline, is recommended for relieving sitting-induced pressures. The goal is to increase skin blood flow for the ischemic soft tissues to avoid irreversible damage. Due to variations in the level and completeness of SCI, the effectiveness of using wheelchair tilt and recline to reduce pressure ulcer risks has considerable room for improvement. Our previous study indicated that the blood flow of people with SCI may respond very differently to wheelchair tilt and recline settings. In this study, we propose to use the artificial neural network (ANN) to predict how wheelchair power seat functions affect blood flow response to seating pressure. This is regression learning because the predicted outputs are numerical values. Besides the challenging nature of regression learning, ANN may suffer from the overfitting problem which, when occurring, leads to poor predictive quality (i.e., cannot generalize). We propose using the particle swarm optimization (PSO) algorithm to train ANN to mitigate the impact of overfitting so that ANN can make correct predictions on both existing and new data. Experimental results show that the proposed approach is promising to improve ANN's predictive quality for new data.

Original languageEnglish (US)
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages4648-4651
Number of pages4
DOIs
StatePublished - 2012
Externally publishedYes
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

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

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  • Cite this

    Fu, J., Wiechmann, P., Jan, Y. K., & Jones, M. (2012). Towards an intelligent system for clinical guidance on wheelchair tilt and recline usage. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012 (pp. 4648-4651). [6347003] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2012.6347003