Validity of Dual-Minima Algorithm for Heel-Strike and Toe-Off Prediction for the Amputee Population

Assessment of gait deficits relies on accurate segmentation based the key events heel strike (HS) and toe-off (TO). Kinematics-based estimation has shown promise in this regard, especially using leg velocity signal gyroscopic sensors. However, its validation for amputee population is not established literature. The goal study to assess accuracy lower-leg angular determining TO HS instants population. An open data set containing marker 10 subjects with unilateral transfemoral amputation during treadmill walking was used. A rule-based dual-minima algorithm developed detect landmarks shank indicating events. predictions were compared against force platform 2595 cycles from 239 trials. results showed considerable a median error ?1 ms. prediction larger ranging 35–84 consistently predicted earlier than actual event. Significant differences found between sound prosthetic legs. also affected by subjects’ mobility level (K-level) but largely unaffected speed. In conclusion, profile can predict heel-strike varying degrees depending upon side amputee’s functional ability level.