Shanghai Lepu Cloudmed Co., Ltd

Kaifeng Zang

Jun Cao

Chang Liu

Yan Jiang

Pengfei Zhao

Tao Liu

Chuanyan Hu

Haitao Lu

Baoquan Wang

Erbin Wang

Youchao Lu

Youchao Lv

An artificial intelligence self-learning-based automatic electrocardiography analysis method and apparatus, the method comprising data preprocessing, heartbeat feature detection, interference signal detection and heartbeat classification based on deep learning, signal quality evaluation and lead combination, heartbeat verification, analysis and calculation of electrocardiography events and parameters, and finally automatic output of reporting data, realizing an automated analysis method having a complete and rapid flow. The automatic electrocardiography analysis method may also record modification information of an automatic analysis result, collect modified data, and feed same back to the depth learning model to continue training, thereby continuously making improvements and improving the accuracy of the automatic analysis method.

Artificial intelligence self-learning-based automatic electrocardiography analysis method and apparatus

A detection report data generation method including acquiring event type information of an electrocardiogram event corresponding to electrocardiogram event data, wherein the event data has one or more pieces of event type information; screening the event data according to signal quality evaluation indexes so as to obtain report conclusion data and report entry data; carrying out quality assessment on an event segment included in the event data according to the signal quality evaluation indexes, and determining a pre-selected sample segment according to a quality assessment result; determining position information of an event heart beat in the pre-selected sample segment, and determining segment interception parameters; carrying out interception processing on the pre-selected sample segment according to the segment interception parameters so as to obtain a typical data segment; generating report graphic data according to the typical data segment; and outputting the entry data, the graphic data and the conclusion data.

Detection report data generation method

An artificial intelligence self-learning-based static electrocardiography analysis method and apparatus, the method comprising data preprocessing, heartbeat detection, heartbeat classification based on a depth learning method, heartbeat verification, heartbeat waveform feature detection, measurement and analysis of electrocardiography events, and finally automatic output of reporting data, realizing an automated static electrocardiograph analysis method having a complete and rapid flow. The static electrocardiography analysis method can also record modification information of an automatic analysis result, collect modified data, and feed same back to the depth learning model to continue training, thereby continuously making improvements and improving the accuracy of the automatic analysis method.

Artificial intelligence self-learning-based static electrocardiography analysis method and apparatus

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Beijing, China

Kaifeng Zang