Document Detail

Towards an intelligent system for clinical guidance on wheelchair tilt and recline usage.
MedLine Citation:
PMID:  23366964     Owner:  NLM     Status:  MEDLINE    
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.
Jicheng Fu; Paul Wiechmann; Yih-Kuen Jan; Maria Jones
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2012     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2012  
Date Detail:
Created Date:  2013-01-31     Completed Date:  2013-07-22     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  4648-51     Citation Subset:  IM    
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MeSH Terms
Artificial Intelligence*
Patient Positioning / methods*
Pressure Ulcer / etiology,  physiopathology*,  prevention & control*
Spinal Cord Injuries / complications,  physiopathology*,  rehabilitation*
Therapy, Computer-Assisted / methods*
Treatment Outcome
Grant Support

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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