%0 Journal Article
	%A L. Parisi
	%D 2014
	%J International Journal of Biomedical and Biological Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 94, 2014
	%T Exploiting Kinetic and Kinematic Data to Plot Cyclograms for Managing the Rehabilitation Process of BKAs by Applying Neural Networks
	%U https://publications.waset.org/pdf/9999626
	%V 94
	%X Kinematic data wisely correlate vector quantities in
space to scalar parameters in time to assess the degree of symmetry
between the intact limb and the amputated limb with respect to a
normal model derived from the gait of control group participants.
Furthermore, these particular data allow a doctor to preliminarily
evaluate the usefulness of a certain rehabilitation therapy.
Kinetic curves allow the analysis of ground reaction forces (GRFs)
to assess the appropriateness of human motion.
Electromyography (EMG) allows the analysis of the fundamental
lower limb force contributions to quantify the level of gait
asymmetry. However, the use of this technological tool is expensive
and requires patient’s hospitalization. This research work suggests
overcoming the above limitations by applying artificial neural
networks.

	%P 736 - 740