心率变异性
可靠性(半导体)
最小意识状态
回归分析
血压
线性回归
回归
心电图
灵敏度(控制系统)
计算机科学
心率
听力学
统计
医学
心脏病学
数学
心理学
内科学
神经科学
意识
工程类
功率(物理)
物理
量子力学
电子工程
作者
Martin Wieser,Lilith Buetler,Alexander Koenig,Robert Riener
标识
DOI:10.1109/iembs.2010.5626763
摘要
Clinical scales represent the golden standard in characterizing awareness for patients in vegetative or in a minimally conscious state. Clinical scales suffer from problems of sensitivity, specificity, subjectivity, and inter-rater reliability. This leads to a misdiagnosis rate of up to 40% and consequences associated with inappropriate treatment decisions. In this study, objective measures including physiological and neurological signals are used to quantify the patient status. Using linear backward regression analysis, 13 variables (based on frequency analysis of the electrocardiogram, heart rate variability, amplitude and latency of the P300, skin conductance responses, changes in the blood pressure and respiration signal) were found to be sufficient to describe 74.7% of the variability of the scores. In this regression model, the P300, electrocardiogram and the blood pressure signal account for most of the variability. More patient data and additional measures will enable refinement of the methods. This new objective-measurement based model of the state of awareness will complement the clinical scales in order to increase the quality of diagnosis.
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