Article

Interpolation is a common data processing step in the study of interface pressure
data collected at the wheelchair seating interface. However, there has been no
focused study on the effect of interpolation on features extracted from these
pressure maps, nor on whether these parameters are sensitive to the manner in
which the interpolation is implemented. Here, two different interpolation
paradigms, bilinear versus bicubic spline, are tested for their influence on
parameters extracted from pressure array data and compared against a conventional
low-pass filtering operation. Additionally, analysis of the effect of tandem
filtering and interpolation, as well as the interpolation degree (interpolating
to 2, 4, and 8 times sampling density), was undertaken. The following
recommendations are made regarding approaches that minimized distortion of
features extracted from the pressure maps: (1) filter prior to interpolate
(strong effect); (2) use of cubic interpolation versus linear (slight effect);
and (3) nominal difference between interpolation orders of 2, 4, and 8 times
(negligible effect). We invite other investigators to perform similar benchmark
analyses on their own data in the interest of establishing a community consensus
of best practices in pressure array data processing.

Langue : ANGLAIS