Stance Sub-Phases Gait Event Detection in Real-time for Ramp Ascent and Descent

Maqbool, HF orcid.org/0000-0003-3193-4984, Husman, MAB, Awad, MI orcid.org/0000-0002-0367-0187 et al. (3 more authors) (2017) Stance Sub-Phases Gait Event Detection in Real-time for Ramp Ascent and Descent. In: Ibáñez, J, González-Vargas, J, Azorín, JM, Akay, M and Pons, JL, (eds.) Converging Clinical and Engineering Research on Neurorehabilitation II. 3rd International Conference on NeuroRehabilitation (ICNR2016), 18-21 Oct 2016, Segovia, Spain. Springer International Publishing , pp. 191-196. ISBN 978-3-319-46668-2

Abstract

This article presents a real-time gait event/phase detection system for control subjects and lower limb amputees during ramp ascent (RA) and ramp descent (RD) using a single wearable sensor. Development of the algorithm is based on the shank angular velocity in the sagittal plane and linear acceleration signal in the shank longitudinal direction. System performance was evaluated with nine control subjects (CS) and one transfemoral amputee (TFA) and the results were validated with foot-switches. Results were promising for Initial-Contact (IC) and Toe-Off (TO) across all the subjects. Higher mean differences were found out for Foot-Flat start and Heel-Off, particularly in the case of TFA due to the difference in kinematics behavior compared to CS. Success detection rate of 99.7 % was achieved for RA and RD in both groups.