Heuristic Based Gait Event Detection for Human Lower Limb Movement

Gait event detection is important for intent predication in lower limb prostheses and exoskeletons during different activities. Human gait cycle is divided into two main phases i.e. swing phase and stance phase. Initial contact (IC) with the ground indicate the start of stance phase while Toe Off (TO) is the start of swing phase. This article presents algorithm based on set of heuristic rules for gait event detection using a single gyroscope attached on shank of subjects performing activities of daily living such as normal walking, fast walking, ramp ascending and ramp descending. The algorithm sequentially detected gait events like IC, TO, Midswing (MSw) and Midstance (MSt). Results were compared with the reference pressure measurement system using Flexiforce footswitches (FSW). The mean difference error between the reference and proposed system was for IC is about +4ms and for TO is about −6.5ms. The results showed that proposed algorithm achieved high detection performance compared to the existing algorithms and will lead to powerful tool to develop an intent recognition system for lower limb amputees.