jicheng fu, phd; maria jones, pt, phd; yih-kuen jan, pt, phd
DESCRIPTION
Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: Methodology and preliminary report. Jicheng Fu, PhD; Maria Jones, PT, PhD; Yih-Kuen Jan, PT, PhD. Aim - PowerPoint PPT PresentationTRANSCRIPT
This article and any supplementary material should be cited as follows: Fu J, Jones M, Jan Y. Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: Methodology and preliminary report. J Rehabil Res Dev. 014;51(5):775–88. http://dx.doi.org/10.1682/JRRD.2013.09.0199
Slideshow ProjectDOI:10.1682/JRRD.2013.09.0199JSP
Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: Methodology and
preliminary reportJicheng Fu, PhD; Maria Jones, PT, PhD; Yih-Kuen Jan, PT, PhD
This article and any supplementary material should be cited as follows: Fu J, Jones M, Jan Y. Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: Methodology and preliminary report. J Rehabil Res Dev. 014;51(5):775–88. http://dx.doi.org/10.1682/JRRD.2013.09.0199
Slideshow ProjectDOI:10.1682/JRRD.2013.09.0199JSP
• Aim– Demonstrate feasibility of using machine learning
techniques to construct intelligent model to provide personalized guidance for individuals with spinal cord injury (SCI).
• Relevance– Clinical evidence shows that SCI individuals’
requirements vary greatly. Hence, no universal guidance on tilt and recline usage could possibly satisfy all individuals with SCI.
This article and any supplementary material should be cited as follows: Fu J, Jones M, Jan Y. Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: Methodology and preliminary report. J Rehabil Res Dev. 014;51(5):775–88. http://dx.doi.org/10.1682/JRRD.2013.09.0199
Slideshow ProjectDOI:10.1682/JRRD.2013.09.0199JSP
Method
• Explored ways of modeling research participants.• Used machine learning techniques to construct
the intelligent model.• Evaluated the intelligent model’s performance.• Further improved the intelligent model’s
prediction accuracy by developing a two-phase feature selection algorithm to identify important attributes.
This article and any supplementary material should be cited as follows: Fu J, Jones M, Jan Y. Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: Methodology and preliminary report. J Rehabil Res Dev. 014;51(5):775–88. http://dx.doi.org/10.1682/JRRD.2013.09.0199
Slideshow ProjectDOI:10.1682/JRRD.2013.09.0199JSP
Results
• Results demonstrated that our approaches were able to:– Effectively construct an intelligent model• Classify whether a given tilt and recline setting would be
favorable for skin blood flow increase for an SCI individual, i.e., personalized guidance
– Evaluate its performance.
– Refine the participant model to significantly improve the intelligent model’s prediction accuracy.
This article and any supplementary material should be cited as follows: Fu J, Jones M, Jan Y. Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: Methodology and preliminary report. J Rehabil Res Dev. 014;51(5):775–88. http://dx.doi.org/10.1682/JRRD.2013.09.0199
Slideshow ProjectDOI:10.1682/JRRD.2013.09.0199JSP
Conclusion• Our study demonstrated the feasibility of using
machine learning techniques to construct an intelligent model to provide personalized guidance on wheelchair tilt and recline usage to individuals with SCI.
• The intelligent model achieved satisfactory accuracy by considering participants attributes that can be easily obtained without advanced clinical devices.