Abstract: A medical analysis device with cellular impedance signal processing comprises a memory (4) arranged to receive pulse data sets, each pulse data set comprising impedance value data that are associated each time with a time marker, these data together representing a curve of cellular impedance values that are measured as a cell passes through a polarised opening. This device further comprises a classifier (6) comprising a convolutional neural network receiving the pulse data sets as input and is provided with at least one convolutional layer, which convolutional layer has a depth greater than or equal to 3, and at least two fully connected layers, in addition to an output layer rendering a cell classification from which a pulse data set is derived.

Abstract: A device for medical analyses with cellular impedance signal processing comprises a memory (4) arranged to receive pulse data sets, each pulse data set comprising impedance value data that are associated each time with a time marker, these data together representing a curve of cellular impedance values that are measured as a cell passes through a polarized opening, a computer (6) arranged to process a pulse data set by determining a rotation value indicating whether the cell from which this pulse data set has been taken has undergone a rotation during its passage through the polarized opening, and a classifier (8) arranged to retrieve from the computer (6) a given pulse data set, and to use the resulting rotation value to classify the given pulse data set in a rotation pulse data set group (10) or a rotationless pulse data set group (12).