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利用治疗效果期间的皮肤电反应分析意识水平。

Analysis of Consciousness Level Using Galvanic Skin Response during Therapeutic Effect.

机构信息

Department of Biomedical Engineering, Erciyes University, Kayseri, Turkey.

Department of Anesthesiology and Reanimation, Erciyes University, Kayseri, Turkey.

出版信息

J Med Syst. 2020 Nov 24;45(1):1. doi: 10.1007/s10916-020-01677-5.

Abstract

The neurological status of patients in the Intensive Care Units (ICU) is determined by the Glasgow Coma Scale (GCS). Patients in coma are thought to be unaware of what is happening around them. However, many studies show that the family plays an important role in the recovery of the patient and is a great emotional resource. In this study, Galvanic Skin Response (GSR) signals were analyzed from 31 patients with low consciousness levels between GCS 3 and 8 to determine relationship between consciousness level and GSR signals as a new approach. The effect of family and nurse on unconscious patients was investigated by GSR signals recorded with a new proposed protocol. The signals were recorded during conversation and touching of the patient by the nurse and their families. According to numerical results, the level of consciousness can be separated using GSR signals. Also, it was found that family and nurse had statistically significant effects on the patient. Patients with GCS 3,4, and 5 were considered to have low level of consciousness, while patients with GCS 6,7, and 8 were considered to have high level of consciousness. According to our results, it is obtained lower GSR amplitude in low GCS (3, 4, 5) compared to high GCS (7, 8). It was concluded that these patients were aware of therapeutic affect although they were unconscious. During the classification stage of this study, the class imbalance problem, which is common in medical diagnosis, was solved using Synthetic Minority Over-Sampling Technique (SMOTE), Adaptive Synthetic Sampling (ADASYN) and random oversampling methods. In addition, level of consciousness was classified with 92.7% success using various decision tree algorithms. Random Forest was the method which provides higher accuracy compared to all other methods. The obtained results showed that GSR signal analysis recorded in different stages gives very successful GCS score classification performance according to literature studies.

摘要

重症监护病房(ICU)患者的神经状态由格拉斯哥昏迷量表(GCS)确定。处于昏迷状态的患者被认为无法感知周围发生的事情。然而,许多研究表明,家庭在患者的康复过程中起着重要作用,是重要的情感资源。在这项研究中,分析了 31 名意识水平较低(GCS 3 至 8 分)的患者的皮肤电反应(GSR)信号,以确定意识水平与 GSR 信号之间的关系,这是一种新方法。通过新提出的方案记录的 GSR 信号研究了家庭和护士对无意识患者的影响。信号记录了护士和他们的家人与患者交谈和触摸时的情况。根据数值结果,使用 GSR 信号可以分离意识水平。还发现家庭和护士对患者有统计学上的显著影响。GCS 3、4 和 5 的患者被认为处于低意识水平,而 GCS 6、7 和 8 的患者被认为处于高意识水平。根据我们的结果,在低 GCS(3、4、5)与高 GCS(7、8)相比,获得的 GSR 幅度较低。这表明这些患者尽管无意识,但能感知治疗效果。在本研究的分类阶段,使用合成少数过采样技术(SMOTE)、自适应合成采样(ADASYN)和随机过采样方法解决了医学诊断中常见的类不平衡问题。此外,使用各种决策树算法将意识水平分类为 92.7%的成功率。与所有其他方法相比,随机森林是提供更高精度的方法。获得的结果表明,根据文献研究,在不同阶段记录的 GSR 信号分析可提供非常成功的 GCS 评分分类性能。

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