Article

Wheelchair tilt and recline functions are two of the most desirable features for
relieving seating pressure to decrease the risk of pressure ulcers. The effective
guidance on wheelchair tilt and recline usage is therefore critical to pressure
ulcer prevention.
The aim of this study was to demonstrate the feasibility of
using machine learning techniques to construct an intelligent model to provide
personalized guidance to individuals with spinal cord injury (SCI). The
motivation stems from the clinical evidence that the requirements of individuals
vary greatly and that no universal guidance on tilt and recline usage could
possibly satisfy all individuals with SCI. We explored all aspects involved in
constructing the intelligent model and proposed approaches tailored to suit the
characteristics of this preliminary study, such as the way of modeling research
participants, using machine learning techniques to construct the intelligent
model, and evaluating the performance of the intelligent model. We further
improved the intelligent model's prediction accuracy by developing a two-phase
feature selection algorithm to identify important attributes. Experimental
results demonstrated that our approaches held the promise: they could effectively
construct the intelligent model, evaluate its performance, and refine the
participant model so that the intelligent model's prediction accuracy was significantly improved.

Langue : ANGLAIS