Gait event detection for use in FES rehabilitation by radial and tangential foot accelerations

Gait rehabilitation by Functional Electrical Stimulations (FESs) requires a reliable trigger signal to start the stimulations. This could be obtained by a simple switch under the heel or by means of an inertial sensor system. This study provides an algorithm to detect gait events in differential acceleration signals of the foot. The key feature of differential measurements is that they compensate the impact of gravity. The real time detection capability of a rule based algorithm in healthy and hemiparetic individuals was investigated. Detection accuracy and precision compared to signals from foot switches were evaluated. The algorithm detected curve features of the vectorial sum of radial and tangential accelerations and mapped those to discrete gait states. The results showed detection rates for healthy and hemiparetic gait ranging form 84.2% to 108.5%. The sensitivity was between 0.81 and 1, and the specificity between 0.85 and 1, depending on gait phase and group of subjects. The algorithm detected gait phase changes earlier than the reference. Differential acceleration signals combined with the proposed algorithm have the potential to be implemented in a future FES system.