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Updated: Aug 20, 2026
Motor Dual-Tasks for Gait Analysis and Evaluation in Post-Stroke Patients
Published on: March 11, 2021
Preliminary Reference Values for Dual-Task Gait Performance and Data-Driven Gait Profiles Across the Lifespan in
Bora Jin1, Seungho Lee2, Sang-Myung Cheon3
1Department of Neurology, College of Medicine, Dong-A University, Busan, Republic of Korea.
Objectives:
Understanding normal gait characteristics is fundamental for characterizing disease-specific gait alterations. This study aimed to evaluate age-related differences in gait across various task conditions and identify data-driven gait profiles based on dual-task vulnerability in healthy Korean adults.
Methods:
A cross-sectional gait assessment was conducted using GAITRite® under four conditions: preferred speed, serial sevens subtraction, cell phone use, and backward walking. Gait parameters were categorized into five domains: pace, variability, rhythm, asymmetry, and postural control. Participants were stratified into younger (<60 years) and older adults (≥60 years). Latent profile analysis (LPA) was performed using the dual-task cost variables to identify data-driven gait profiles.
Results:
Ninety-eight healthy adults (aged 23-87 years) were analyzed. Age-related differences were most pronounced during cell phone use, which was supported by significant age × task interaction effects across the pace, variability, rhythm, and postural control domains (pfdr < 0.05). LPA identified three profiles: Pace-Preserved (Pa-P), Asymmetry-Dominant (Asym-D), and Postural control-Dominant (Pc-D). Younger adults were evenly distributed across the profiles, whereas older adults were predominantly classified into the Asym-D and Pc-D profiles. The Asym-D profile, characterized by the highest mean age, exhibited numerically lower cognitive scores, particularly in the visuospatial domain.
Conclusions:
Regardless of chronological age groups and data-driven profiles, dual-task gait interference was most pronounced in the cognitive-motor dual-task condition. Data-driven profiling also identified a subgroup characterized by gait asymmetry, older age, and lower cognitive scores, suggesting a potentially distinct cognitive-motor pattern that warrants longitudinal investigation. These preliminary reference values provide a valuable foundation for the identification of pathological gait patterns in clinical populations.
