Gait event detection accuracy: Effects of amputee gait pattern, terrain and algorithm

Abstract

Several kinematic-based algorithms have shown accuracy for gait event detection in unimpaired and pathological gait. However, their validation in subjects with lower limb amputation while walking on different terrains is still limited. The aim of this study was to evaluate the accuracy of three kinematic-based algorithms: Coordinate-Based Algorithm (CBA), Velocity-Based Algorithm (VBA) and High-Pass Filtered Algorithms (HPA) for detection of gait events in subjects with unilateral transtibial amputation walking on different terrains. Twelve subjects with unilateral transtibial amputation, using a hydraulic ankle prosthesis, walked at self-selected walking speed, on level ground and up and down a slope. Detection of Initial Contact (IC) and Foot Off (FO) by the three algorithms for intact and prosthetic limbs was compared with detection by force platforms using the True Error (TE) (time difference in detection). Mean TE found for over 100 events analysed per condition were smaller than 40 ms for both events in all conditions (approximately 6 % of stance phase). Significant interactions (p < 0.01) were found between terrain and algorithm, limb and algorithm, and also a main effect for the algorithm. Post-hoc analyses indicate that the algorithm, the limb and the terrain had an effect on the accuracy in detection. If an accuracy of 40 ms is acceptable for the particular application, then all three algorithms can be used for event detection in amputee gait. However, if accuracy in detection of events is crucial for the intended application, an evaluation of the algorithms in pathological gait walking on the terrain of interest is recommended.