Principal component analysis in ground reaction forces and center of pressure gait waveforms of people with transfemoral amputation. (December 2016)

• Record Type: Journal Article
• Authors: Soares, Denise Paschoal; de Castro, Marcelo Peduzzi; Mendes, Emilia Assunção; Machado, Leandro
• Is Part Of: Prosthetics and orthotics international. Volume 40:Number 6(2016:Dec.)
• Page Start: 729
• Page End: 738
• Publication Date: 2016-12
• Subjects: Principal component analysis -- walking -- amputees -- lower limb amputation -- gait analysis; Orthopedic apparatus -- Periodicals; Prosthesis -- Periodicals; Implants, Artificial -- Periodicals; 617.905
• DOI: 10.1177/0309364615612634
• Languages: English
• ISSNs: 0309-3646

Abstract

Background: The alterations in gait pattern of people with transfemoral amputation leave them more susceptible to musculoskeletal injury. Principal component analysis is a method that reduces the amount of gait data and allows analyzing the entire waveform. Objectives: To use the principal component analysis to compare the ground reaction force and center of pressure displacement waveforms obtained during gait between able-bodied subjects and both limbs of individuals with transfemoral amputation. Study design: This is a transversal study with a convenience sample. Methods: We used a force plate and pressure plate to record the anterior–posterior, medial–lateral and vertical ground reaction force, and anterior–posterior and medial–lateral center of pressure positions of 12 participants with transfemoral amputation and 20 able-bodied subjects during gait. The principal component analysis was performed to compare the gait waveforms between the participants with transfemoral amputation and the able-bodied individuals. Results: The principal component analysis model explained between 74% and 93% of the data variance. In all ground reaction force and center of pressure waveforms relevant portions were identified; and always at least one principal component presented scores statistically different ( p < 0.05) between the groups of participants in these relevant portions. Conclusion: Principal component analysis was able to discriminate many portions of the stance phase between both lower limbs of people with transfemoral amputation compared to the able-bodied participants. Clinical relevance: Principal component analysis reduced the amount of data, allowed analyzing the whole waveform, and identified specific sub-phases of gait that were different between the groups. Therefore, this approach seems to be a powerful tool to be used in gait evaluation and following the rehabilitation status of people with transfemoral amputation.