JMIR Publications

ABSTRACT

Background:

Gait function is essential for mobility and independence in older adults. Although age-related gait decline on level-ground surfaces has been studied extensively, there is less information on how aging affects gait during ramp walking, despite its relevance in daily living. Different biomechanical strategies are used during ramp ascent and descent; however, detailed joint kinematics remain unclear, particularly under real-world conditions.

Objective:

To investigate age-related differences in lower-limb joint angles and spatiotemporal parameters during level and ramp walking.

Methods:

Gait was assessed in 20 young (31.3 ± 8.9 years) and 20 older (64.2 ± 0.8 years) healthy adults using a markerless motion capture system (Theia3D) in a living lab setting. The participants completed gait trials on level ground and on a 7° ramp (ascent and descent). Between-group comparisons were conducted using independent two-sample t-tests for spatiotemporal parameters (gait speed, step length, and gait cadence) and the Wilcoxon rank-sum tests for sagittal joint angles (hip, knee, and ankle), with Cohen’s d and Cliff’s delta effect sizes, respectively.

Results:

Older adults exhibited significantly lower velocity and step length across all conditions, with the largest effect size observed during ramp ascent (d = 1.614 for velocity). During ramp ascent, significant reductions were observed in maximum ankle plantarflexion angle. During ramp descent, multi-joint kinematic alterations were evident, including increased hip flexion and reduced hip extension, knee extension, and ankle plantarflexion angles. In contrast, differences during level walking were not statistically significant for most joint angles, except for knee extension, which exhibited significant intergroup differences in both level walking and ramp descent.

Conclusions:

Age-related gait differences became pronounced under inclined conditions, particularly during ramp descent, where coordinated multi-joint adaptations were required. These findings highlight the importance of assessing gait under various environmental conditions to better understand mobility limitations in older adults. The combination of an AI-based markerless motion capture system and an ecologically designed living lab environment addresses this need by enabling non-invasive, realistic gait analysis beyond traditional laboratory constraints. Clinical Trial: UMIN Clinical Trials Registry UMIN000049283; UMIN000049284 https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000056122 https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000056126