Principal component analysis of vertical ground reaction force: a powerful method to discriminate normal and abnormal gait and assess treatment.
This study aims at testing the application of principal component analysis (PCA) in the ground reaction force (GRF) in discriminating the gait pattern between normal and abnormal subjects, and assessing the rehabilitation treatment. The sample was composed by 31 subjects, organized into two groups: a control group (CG) of 25 normal and a group (FG) of six patients with lower limb fractures, which was considered before (FGB) and after (FGA) a treadmill physiotherapeutic treatment. The vertical component of GRF data was collected with an instrumentized treadmill. PCA method was applied and the first two coefficients (PCC) were obtained for the three groups. The region of CG values was separated in the PCC plane with the elliptical area of displacement and with a linear threshold between CG and FGB obtained by stepwise logistic regression. Results show that all values of FGA moved towards CG region from the corresponding FGB position, indicating the potential power of PCA in discriminating between normal and abnormal gait and objectively evaluating the effects of rehabilitation treatment.
Muniz
A M S
AM
Biomed. Eng. Program, Fed. Univ. of Rio de Janeiro. adriane@peb.ufrj.br
Manfio
E F
EF
Andrade
M C
MC
Nadal
J
J
D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D005528:Foot / Q000503:physiopathology*; D020233:Gait Disorders, Neurologic / Q000175:diagnosis* / Q000503:physiopathology*; D006801:Humans; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013314:Stress, Mechanical