Morphological detection method for superficial aneurysm and wearable equipment

The invention provides a form detection method for superficial aneurysm and wearable equipment. The method comprises the following steps: step 1, constructing and training a diameter-neck ratio prediction neural network model; 2, synchronous ECG signals and PPG signals of a testee are obtained, feature parameters are extracted according to the ECG signals and the PPG signals, and the feature parameters comprise the maximum blood flow velocity, the blood flow velocity variation, the blood flow and the blood pressure; and step 3, generating a feature vector of the testee according to the extracted feature parameters, and inputting the feature vector into the trained diameter-neck ratio prediction neural network model to obtain the diameter-neck ratio of the testee. 本发明提供一种面向浅表层动脉瘤的形态检测方法和可穿戴式设备。该方法包括：步骤1：构建并训练径颈比预测神经网络模型；步骤2：获取受测者同步的ECG信号与PPG信号，根据所述ECG信号与PPG信号提取特征参数，所述特征参数包括最大血流速度、血流速度变化量、血液流量和血压；步骤3：根据提取到的特征参数生成受测者的特征向量，将所述特征向量输入至训练好的径颈比预测神经网络模型，得到受测者的径颈比。