The invention discloses a sleep apnea syndrome assessment method based on electrocardiogram signals. The method comprises the following steps: acquiring the night electrocardiogram signals; pre-processing the electrocardiogram signals so as to obtain clean electrocardiogram signals; finding out the position of a peak value of R wave by virtue of R wave detecting algorithm, and conducting calculation so as to obtain RR sequences; interpolating the RR sequences, so that the RR sequences are identical in length; and dividing the interpolated RR sequences into three groups in accordance with a sample: a pre-training group, a fine-adjusting group and a test group, wherein by virtue of the pre-training group and the fine-adjusting group, an OSAS (obstructive sleep apnea syndrome) recognition model is constructed and optimized, and by virtue of the test group, an assessment result of the model on the OSAS is obtained. The method provided by the invention, by collecting the human electrocardiogram signals in a noninvasive mode, can be used for assessing the sleep apnea syndrome, and for the RR sequences extracted from original electrocardiogram signals, characteristic learning and OSAS recognition model construction can be conducted by virtue of a sparse self-coding network; meanwhile, network parameters are optimized through micro-adjusting, so that the model is more excellent in recognition capacity and good assessment is conducted; and the method provided by the invention is available by collecting the electrocardiogram signals within 8h at night.