Resumen
Gait stability indices are crucial for identifying individuals at risk of falling while walking. The margin of stability is one such index, known for its good construct validity. Generally, the measurement of this stability index requires a motion capture system, rendering it inaccessible for everyday use. This study proposes an alternative approach by estimating the index through time-series data of triaxial kinematic motion from a single body feature. We analyzed an open gait database comprising data from 60 participants aged over 60 to identify the most accurate body feature for estimating the margin of stability. The margin of stability values were estimated by using principal motion analysis, with the time series of the triaxial translational velocities of a body feature as predictors. Among the 10 body feature points, the sacral crest provided the highest accuracy, with the correlation coefficients between observation and estimation being 0.56 and 0.54 for the mediolateral and anterior directions, respectively. Although these values need to be further improved, these findings pave the way for developing an accessible system to estimate fall risks.