The invention discloses an
energy metabolism assessment method based on
wearable sensing information fusion and a
system thereof. The method comprises the following steps: acquiring electrocardiosignal information reflecting the physiological state of a
human body, acceleration
signal information reflecting the
exercise intensity level of the
human body and physical characteristic information of a
human body structure; inputting the electrocardiosignal information into a first
convolutional neural network to extract electrocardiosignal features, inputting the acceleration
signal information into a second
convolutional neural network to extract acceleration features, wherein the first
convolutional neural network and the second convolutional neural network are obtained through training, and the first convolutional neural network and the second convolutional neural network are both multi-
branch structures so as to extract multi-scale features; and fusing the electrocardio characteristics, the acceleration characteristics and the physical characteristic information of the
human body structure, and predicting corresponding
energy metabolism information based on the fused characteristics. By means of the method, accurate calculation of
energy consumption in the movement process can be achieved, and the generalization ability is high.