Detection of abnormal operations during surgery via SEMG / EEG and its applications to prevention of malpractice

在本研究中，对内窥镜手术中的手术进行了自动识别，并对识别出的手术的异常进行了区分。将结扎手术分为7个手术，并根据钳子手术次数的阈值标准，将手术确定为其中之一。接下来，当手术被识别为线结时，使用基于操作者表面肌电的自组织神经网络：sEMG将线结的操作分类为正常或异常。最后，构建了通过向外科医生呈现异常操作的检测来预防医疗事故的预警系统。脑电检测(1)惊喜感和(2)精神疲劳：以脑电为基础实验，检测病人病情突变时医生的感觉变化，以及长时间手术过程中医生感觉的异常。

In this research, an automatic identification of a surgical operation in endoscopic surgery and distinction of the abnormality of the identified surgical operation were executed. Surgical operation of ligation was divided into seven operations, and on the basis of the threshold criteria for the amount of operations of forceps, a surgical operation was identified as one of them. Next, when the surgical operation was identified as a thread knotting, the operation of thread knotting was classified as either normal or abnormal using a self-organizing map based on operator's surface electromyogram:SEMG. Finally, a warning system to prevent malpractice by presenting detection of the abnormal operation to surgeon was constructed. In addition, detection of (1)surprise feeling and (2)mental fatigue via electroencephalogram:EEG was tried as a basic experiment for the purpose of detecting change of feeling of a doctor at the time of sudden condition change of a patie nt and detecting abnorlity of a doctor's feelings during the long time surgical operation.