Before revision:  Consequently, this paper proposes tackling the especially challenging task of adapting to sEMG signals when multiple days have elapsed between each recording , by presenting SCADANN, a new, deep learning-based, self-calibrating algorithm . SCADANN is ranked against three state of the art domain adversarial algorithms and a multiple-vote self-calibrating algorithm on both offline and online datasets.
After revision:  Consequently, this paper proposes tackling the especially challenging task of unsupervised adaptation of sEMG signals when multiple days have elapsed between each recording , by presenting SCADANN, a new, deep learning-based, self-calibrating algorithm . SCADANN is ranked against three state of the art domain adversarial algorithms and a multiple-vote self-calibrating algorithm on both offline and online datasets.