Multi-day monitoring of foot progression angles during unsupervised, real-world walking in people with and without knee osteoarthritis

Clinical biomechanics (Bristol, Avon)(2023)

引用 1|浏览8
暂无评分
摘要
Background: Foot progression angle is a biomechanical target in gait modification interventions for knee oste-oarthritis. To date, it has only been evaluated within laboratory settings.Methods: Adults with symptomatic knee osteoarthritis (n = 30) and healthy adults (n = 15) completed two conditions: 1) treadmill walking in the laboratory (5-min), and 2) real-world walking outside of the laboratory (1-week). Foot progression angle was estimated via shoe-embedded inertial sensing. We calculated the foot progression angle magnitude (median) and variability (interquartile range, coefficient of variation), and used mixed models to compare outcomes between the conditions, participant groups, and disease severities. Reli-ability was quantified by the intraclass correlation coefficient, standardized error of the measurement, and the minimum detectable change.Findings: Foot progression angle magnitude did not differ between groups or conditions but variability signifi-cantly higher in real-world walking (P < 0.001). Structural and symptomatic severity were unrelated to FPA in either walking condition, except for real-world coefficient of variation which was higher for moderate-severe structural osteoarthritis compared to the treadmill for those with mild structural severity (P < 0.034). All real-world outcomes showed excellent reliability including intraclass correlation coefficients above 0.95. The participants recorded a mean (standard deviation) of 298 (33) and 10,447 (5232) steps in the laboratory and real-world walking conditions, respectively.Interpretation: This study provides the first characterization of foot progression angles during real-world walking in people with and without symptomatic knee osteoarthritis. These results indicate that foot progression angles can be feasibly and reliably measured in unsupervised real-world walking conditions.
更多
查看译文
关键词
Wearable sensors,Gait,Knee osteoarthritis,Real-world
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要