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.
The original version of this chapter was revised: Author affiliations were corrected. The erratum to this chapter is available at 10.1007/978-3-319-46669-9_247
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-46669-9_247
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The study is linked to the research supported by EPSRC (EP/K020463/1).
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Maqbool, H.F., Husman, M.A.B., Awad, M.I., Abouhossein, A., Iqbal, N., Dehghani-Sanij, A.A. (2017). Stance Sub-phases Gait Event Detection in Real-Time for Ramp Ascent and Descent. In: Ibáñez, J., González-Vargas, J., Azorín, J., Akay, M., Pons, J. (eds) Converging Clinical and Engineering Research on Neurorehabilitation II. Biosystems & Biorobotics, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-319-46669-9_34
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DOI: https://doi.org/10.1007/978-3-319-46669-9_34
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