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TitleAssessment of walker-assisted gait based on principal component analysis and wireless inertial sensors
Author(s)Martins, Maria
Elias, Arlindo
Cifuentes, Carlos
Alfonso, Manuel
Frizera, Anselmo
Santos, Cristina
Ceres, RamóN
Intervention effectiveness
Principal Component Analysis
Walker-assisted gait
Issue date2014
PublisherSociedade Brasileira de Engenharia Biomédica (SBEB)
JournalRevista Brasileira de Engenharia Biomédica
Abstract(s)Introduction: This study investigates a gait research protocol to assess the impact of a walker model with forearm supports on the kinematic parameters of the lower limb during locomotion. Methods: Thirteen healthy participants without any history of gait dysfunction were enrolled in the experimental procedure. Spatiotemporal and kinematic gait parameters were calculated by using wireless inertial sensors and analyzed with Principal Component Analysis (PCA). The PCA method was selected to achieve dimension reduction and evaluate the main effects in gait performance during walker-assisted gait. Additionally, the interaction among the variables included in each Principal Component (PCs) derived from PCA is exposed to expand the understanding of the main differences between walker-assisted and unassisted gait conditions. Results: The results of the statistical analysis identified four PCs that retained 65% of the data variability. These components were associated with spatiotemporal information, knee joint, hip joint and ankle joint motion, respectively. Conclusion: Assisted gait by a walker model with forearm supports was characterized by slower gait, shorter steps, larger double support phase and lower body vertical acceleration when compared with normal, unassisted walking.
AccessRestricted access (UMinho)
Appears in Collections:DEI - Artigos em revistas internacionais

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