Emmanuel A Onsay, Jomar F Rabajante
Measuring the unmeasurable multidimensional poverty for economic development: Datasets, algorithms, and models from the poorest region of Luzon, Philippines
Data in brief
biomechanical assessments running typically take place inside motion capture laboratories however unclear whether data inlab gait assessments representative gait realworld running study sought test well realworld gait patterns represented inlab gait data two cohorts runners equipped consumergrade wearable sensors measuring speed step length vertical oscillation stance time leg stiffness cohort 1 n 49 completed inlab treadmill run plus five realworld runs selfselected distances selfselected courses cohort 2 n 19 completed 24 km outdoor run known course plus five realworld runs selfselected distances selfselected courses degree inlab gait reflected realworld gait quantified using univariate overlap multivariate depth overlap statistics realworld running realworld running flat straight segments comparing inlab realworld data subject univariate overlap ranged 657 leg stiffness 952 speed considering gait metrics together 325 realworld data wellrepresented inlab data subject pooling inlab gait data across multiple subjects led greater distributional overlap inlab realworld data depth overlap 893903 due broader variability gait seen across opposed within subjects stratifying realworld running include flat straight segments meaningfully increase overlap inlab realworld running changes 1 individual gait patterns realworld running characterized consumergrade wearable sensors wellrepresented runners inlab data researchers clinicians consider borrowing information pool many runners predict individual gait behavior using biomechanical data make clinical sports performance decisions