Abstract
The purpose of this study was to predict and visualize pressure ulcer risks by using a novel approach of extracting computational features from seating interface pressures in people with spinal cord injury (SCI). In conventional clinical practice, seating interface pressure assessments rely on descriptive statistics of pressure magnitude. In this study, rank-2 nonnegative matrix factorization (NMF) was applied to the seating interface pressure maps during loading and pressure-relieving conditions in 16 people with SCI. The NMF basis images were used for visual interpretation and computational prediction of pressure ulcer risks. The two NMF basis images encapsulated pressure concentration and pressure dispersion, respectively. The first basis converged on the ischial tuberosity under both seating conditions, whereas the second basis converged anterior to the ischial tuberosity during loading and converged on the coccyx during unloading. The classification yielded 81.25% overall accuracy. In general, higher ulceration risk was associated with higher and lower activations of the first and second bases, respectively. The NMF pipeline yielded promising performance. Basis visualization affirmed the importance of lower ischial pressure and higher distribution dispersion while also revealing that clinical practice may currently be underestimating the importance of coccygeal pressure in response to pressure-relieving activities. [Figure not available: see fulltext.].
Original language | English (US) |
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Pages (from-to) | 227-237 |
Number of pages | 11 |
Journal | Medical and Biological Engineering and Computing |
Volume | 58 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2020 |
Keywords
- Dimensionality reduction
- Feature extraction
- Nonnegative matrix factorization
- Pressure ulcers
- Prevention
- Spinal cord injury
- Visualization
ASJC Scopus subject areas
- Biomedical Engineering
- Computer Science Applications