1. 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 Project DOI: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 report Jicheng Fu, PhD; Maria Jones, PT, PhD; Yih-Kuen Jan, PT, PhD

2. 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 Project DOI: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.

3. 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 Project DOI: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.

4. 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 Project DOI: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.

5. 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 Project DOI: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.