Abstract
This study investigated gait adaptations in elderly individuals by comparing normal walking with walker-assisted gait through a Principal Component Analysis (PCA) of spatiotemporal parameters and sagittal plane kinematics, which are less influenced by intersubject variability. Fourteen unimpaired older adults performed two walking tasks: unassisted gait, and walker-assisted gait with a smart walker designed to enhance stability and support during locomotion. Gait data were acquired using a wearable 3D motion capture system based on inertial measurement units. The results showed that combining joint kinematics and spatiotemporal metrics provides a more comprehensive perspective of gait domains in older adults. In normal walking, distinct components were identified, including pace/variability, asymmetry, rhythm, base of support, and step length, while the incorporation of kinematic data further delineated specific motion patterns of the knee, ankle, and hip joints. Walker-assisted gait exhibited slower pace, increased temporal variability, modifications in the base of support and increased hip flexion throughout the gait cycle. Additionally, this modality exhibited two new gait domains related to swing phase mechanics and step dynamics. These findings form a biomechanical foundation that isolates device-induced adaptations and can be used to tailor rehabilitation protocols and smart walker designs aimed at promoting safe and effective locomotion in older adults.