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Effect of interpolation on parameters extracted from seating interface pressure arrays.
Michael Wininger1, Barbara Crane
1Cooperative Studies Program, Department of Veterans Affairs Connecticut Healthcare System, West Haven, CT;
Journal of Rehabilitation Research and Development
|March 25, 2015
Summary
Filtering wheelchair seating interface pressure data before interpolation is crucial. Cubic interpolation offers slight benefits over linear methods, with interpolation density having minimal impact on feature distortion.
Area of Science:
- Biomedical Engineering
- Rehabilitation Engineering
- Data Science
Background:
- Interface pressure mapping is vital for wheelchair seating research.
- Data processing, including interpolation, is common but its impact on pressure map features is understudied.
Purpose of the Study:
- To investigate the influence of different interpolation methods (bilinear vs. bicubic spline) on pressure map parameters.
- To compare interpolation effects against low-pass filtering.
- To analyze the impact of filtering order, interpolation, and interpolation density.
Main Methods:
- Compared bilinear and bicubic spline interpolation on pressure array data.
- Evaluated the effect of low-pass filtering.
- Assessed tandem filtering and interpolation effects.
- Tested interpolation to 2, 4, and 8 times original sampling density.
Main Results:
- Filtering pressure data prior to interpolation significantly minimizes feature distortion.
- Cubic interpolation shows a slight advantage over linear interpolation in preserving features.
- Increasing interpolation density (2x, 4x, 8x) has a negligible effect on extracted parameters.
Conclusions:
- Recommends filtering pressure data before interpolation for optimal feature preservation.
- Suggests cubic interpolation as a preferred method over linear.
- Highlights the need for community consensus on best practices for pressure array data processing.
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