The invention relates to a breath pattern classification and evaluation method for chest and
abdomen tumor patients before radiotherapy. The method comprises the steps that respiratory movement signals of the chest and the
abdomen of a patient are collected, and original
signal data reflecting changes of chest and
abdomen respiratory movement along with time are obtained; preprocessing and
feature extraction are conducted on the original
signal data, a plurality of
breathing feature parameters are obtained, and the feature parameters comprise a chest
breathing movement amplitude parameter, an abdomen
breathing movement amplitude parameter, breathing frequency, a chest and abdomen breathing
synchronism index and a chest and abdomen breathing movement
phase difference; inputting the characteristic parameters into a breathing mode classification model based on
machine learning, and identifying and classifying the breathing mode of the patient to determine that the breathing mode of the patient belongs to an abdominal breathing mode, a thoracic breathing mode, a mixed breathing mode or other
abnormal breathing modes; and evaluating the breathing mode of the patient based on the
classification result and the characteristic parameters. According to the invention, the safety and effectiveness of the radiotherapy process are improved.