The use of assistive technologies, such as a non-invasive interface for neuroelectrical signal and functional electrical stimulation (NES
-FES
), can mitigate the effects of spinal cord injury (SCI), including impairment of motor, sensory, and autonomic functions. However, it requires an
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The use of assistive technologies, such as a non-invasive interface for neuroelectrical signal and functional electrical stimulation (NES
-FES
), can mitigate the effects of spinal cord injury (SCI), including impairment of motor, sensory, and autonomic functions. However, it requires an adaptation process to enhance the user’s performance by tuning the learning curve to a point of extreme relevance. Therefore, in this pilot study, the learning curves of two people with complete SCI (
: paraplegic-T
, and
: quadriplegic-C
) were analyzed, with results obtained on the accuracy of the classifier (Ac
), repetitions of intra-day training, and number of hits and misses in the activation of FES
for sixteen interventions using the NES
-FES
interface. We assumed that the data were non-parametric and performed the Spearman’s
test (and
p-value) for correlations between the data. There was variation between the learning curves resulting from the training of the NES
-FES
interface for the two participants, and the variation was influenced by factors both related and unrelated to the individual users. Regardless of these factors,
improved significantly in its learning curve, as it presented lower values in all variables in the first interventions compared to the
, although only
showed statistical correlation (on Ac
values in RLL). It was concluded that despite the variations according to factors intrinsic to the user and the functioning of the equipment used, sixteen interventions were sufficient to achieve a good learning effect to control the NES
-FES
interface.
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