Physiological Signal-Based Method for Measurement of Pain Intensity

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 机器人学研究室

	Physiological Signal-Based Method for Measurement of Pain Intensity
	Su, Yang ; Han JD(韩建达); Zhao XG(赵新刚); Chu YQ(褚亚奇)
刊名	FRONTIERS IN NEUROSCIENCE
	2017
卷号	11 页码:1-13
关键词	feature extraction feature selection and reduction pain intensity quantification physiological signals pattern classification
ISSN号	1662-453X
通讯作者	Zhao XG(赵新刚)
产权排序	1
中文摘要	The standard method for prediction of the absence and presence of pain has long been self-report. However, for patients with major cognitive or communicative impairments, it would be better if clinicians could quantify pain without having to rely on the patient's self-description. Here, we present a newly pain intensity measurement method based on multiple physiological signals, including blood volume pulse (BVP), electrocardiogram (ECG), and skin conductance level (SCL), all of which are induced by external electrical stimulation. The proposed pain prediction system consists of signal acquisition and preprocessing, feature extraction, feature selection and feature reduction, and three types of pattern classifiers. Feature extraction phase is devised to extract pain-related characteristics from short-segment signals. A hybrid procedure of genetic algorithm-based feature selection and principal component analysis-based feature reduction was established to obtain high-quality features combination with significant discriminatory information. Three types of classification algorithms linear discriminant analysis, k-nearest neighbor algorithm, and support vector machine are adopted during various scenarios, including multi-signal scenario, multi-subject and between-subject scenario, and multi-day scenario. The classifiers gave correct classification ratios much higher than chance probability, with the overall average accuracy of 75% above for four pain intensity. Our experimental results demonstrate that the proposed method can provide an objective and quantitative evaluation of pain intensity. The method might be used to develop a wearable device that is suitable for daily use in clinical settings.
WOS标题词	Science & Technology ; Life Sciences & Biomedicine
类目[WOS]	Neurosciences
研究领域[WOS]	Neurosciences & Neurology
关键词[WOS]	HEART-RATE-VARIABILITY ; COMPONENT ANALYSIS ; SKIN-CONDUCTANCE ; CARE ; GUIDELINES ; ADULTS ; TOOLS
收录类别	SCI
语种	英语
WOS记录号	WOS:000406527800001
内容类型	期刊论文
源URL	[http://ir.sia.cn/handle/173321/20811]
专题	沈阳自动化研究所_机器人学研究室
作者单位	1.Shengjing Hospital of China Medical University, Shenyang, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
推荐引用方式 GB/T 7714	Su, Yang,Han JD,Zhao XG,et al. Physiological Signal-Based Method for Measurement of Pain Intensity[J]. FRONTIERS IN NEUROSCIENCE,2017,11:1-13.
APA	Su, Yang,Han JD,Zhao XG,&Chu YQ.(2017).Physiological Signal-Based Method for Measurement of Pain Intensity.FRONTIERS IN NEUROSCIENCE,11,1-13.
MLA	Su, Yang,et al."Physiological Signal-Based Method for Measurement of Pain Intensity".FRONTIERS IN NEUROSCIENCE 11(2017):1-13.