TY -非盟的崔Byung-Moon盟——严,霁Yeon AU - Shin Hangsik盟——能剧,Gyujeong PY - 2021 DA - 2021/2/3 TI -小说镇痛对术后疼痛评估指数基于Photoplethysmographic光谱图和卷积神经网络:观察研究乔- J地中海互联网Res SP - e23920六世- 23 - 2 KW -镇痛指数KW -机器学习KW -疼痛评估KW - photoplethysmogram KW -术后疼痛KW -谱图AB -背景:虽然基于生物信号处理的市售镇痛指标已被用于量化全麻期间的痛觉，但其在意识清醒的患者中的表现较低。因此，有必要开发一种新的性能更好的镇痛指标来量化意识清醒患者的术后疼痛。目的:本研究旨在利用光容量描记图(PPG)和卷积神经网络(CNN)开发一种新的镇痛指标，客观评估意识清醒患者的疼痛。方法:从一组手术患者中获得PPGs，在无疼痛(术前)和存在疼痛(术后)的情况下均持续6分钟。然后使用后5分钟的PPG数据进行分析。基于ppg和CNN，我们开发了用于疼痛评估的谱图- CNN指数。通过测量受试者工作特征曲线的曲线下面积(AUC)来评价两项指标的性能。结果:100例患者的ppg被用来建立谱图- cnn指数。当有疼痛时，平均(95% CI)频谱- cnn指标值显著增加——基线:28.5(24.2-30.7)，恢复区:65.7 (60.5-68.3); P<.01. The AUC and balanced accuracy were 0.76 and 71.4%, respectively. The spectrogram–CNN index cutoff value for detecting pain was 48, with a sensitivity of 68.3% and specificity of 73.8%. Conclusions: Although there were limitations to the study design, we confirmed that the spectrogram–CNN index can efficiently detect postoperative pain in conscious patients. Further studies are required to assess the spectrogram–CNN index’s feasibility and prevent overfitting to various populations, including patients under general anesthesia. Trial Registration: Clinical Research Information Service KCT0002080; https://cris.nih.go.kr/cris/search/search_result_st01.jsp?seq=6638 SN - 1438-8871 UR - //www.mybigtv.com/2021/2/e23920/ UR - https://doi.org/10.2196/23920 UR - http://www.ncbi.nlm.nih.gov/pubmed/33533723 DO - 10.2196/23920 ID - info:doi/10.2196/23920 ER -