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This paper aimed to evaluate the effect of various electrode configurations on applying a convolutional neural network (CNN) to recognize uterine contraction (UC) with Electrohysterogram (EHG) signals. Seven 8‐electrode configurations and thirteen 4‐electrode configurations were selected from the 4 × 4 electrode grid in the Icelandic 16‐electrode EHG database. EHG signals were divided into UC and...
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