The invention discloses an
atrial fibrillation recognition method based on a group
convolution residual error network and a long / short-
term memory network and relates to the field of
machine recognition of
atrial fibrillation. According to the method, characteristics of electrocardiosignals of three different frequency bands are respectively extracted through three channels on a network structurebased on a group
convolution residual error network and a long / short-
term memory network, characteristic analysis on a
time domain is further implemented through LSTM (
long short term memory), and finally electrocardiosignal segments are classified into a normal segment, an
atrial fibrillation segment, a segment with large
noise and a segment of other rhythms. By adopting the
network model, atrialfibrillation recognition accuracy can be improved in a situation of
noise interference, the analysis time can be shortened, and the instantaneity of an
algorithm can be improved; and on the basis ofthe group
convolution residual error network, a classification accurate rate can be increased on premise that parameter complexity is not improved, benefits of a topology structure of group convolution blocks in a residual error module are taken into play, and meanwhile, data amounts of hyper-parameters can be also increased.