1.
Journal of Biomedical Engineering
;
(6): 284-287, 2004.
Artigo
em Chinês
| WPRIM
| ID: wpr-291129
RESUMO
Neural networks can fit any nonlinear function. After drawing out several characteristic parameters from the three-dimension spectrum for high frequency QRS waves, we input them into the network and trained the network. In this way, we can get a m-dimension curved surface in the m-dimension space which is constructed by those parameters, and this curved surface divides the space into two parts: the unhealthiness and the health. Now, the network can automatically distinguish between the healthiness and the unhealthiness according to their three-dimension spectrum for high frequency QRS waves.