Lausberg Hedda, Sloetjes Han
Department of Neurology, Psychosomatic Medicine, and Psychiatry, German Sport University Cologne, Am Sportpark Müngersdorf 6, D-50939, Köln, Germany.
The Language Archive, Max Planck Institute for Psycholinguistics, Wundtlaan 1, Nijmegen, 6525 XD, The Netherlands.
Behav Res Methods. 2016 Sep;48(3):973-93. doi: 10.3758/s13428-015-0622-z.
As visual media spread to all domains of public and scientific life, nonverbal behavior is taking its place as an important form of communication alongside the written and spoken word. An objective and reliable method of analysis for hand movement behavior and gesture is therefore currently required in various scientific disciplines, including psychology, medicine, linguistics, anthropology, sociology, and computer science. However, no adequate common methodological standards have been developed thus far. Many behavioral gesture-coding systems lack objectivity and reliability, and automated methods that register specific movement parameters often fail to show validity with regard to psychological and social functions. To address these deficits, we have combined two methods, an elaborated behavioral coding system and an annotation tool for video and audio data. The NEUROGES-ELAN system is an effective and user-friendly research tool for the analysis of hand movement behavior, including gesture, self-touch, shifts, and actions. Since its first publication in 2009 in Behavior Research Methods, the tool has been used in interdisciplinary research projects to analyze a total of 467 individuals from different cultures, including subjects with mental disease and brain damage. Partly on the basis of new insights from these studies, the system has been revised methodologically and conceptually. The article presents the revised version of the system, including a detailed study of reliability. The improved reproducibility of the revised version makes NEUROGES-ELAN a suitable system for basic empirical research into the relation between hand movement behavior and gesture and cognitive, emotional, and interactive processes and for the development of automated movement behavior recognition methods.
随着视觉媒体渗透到公共生活和科学生活的各个领域,非言语行为正成为一种重要的交流形式,与书面和口头语言并驾齐驱。因此,目前包括心理学、医学、语言学、人类学、社会学和计算机科学在内的各个学科都需要一种客观可靠的手部动作行为和手势分析方法。然而,到目前为止尚未制定出适当的通用方法标准。许多行为手势编码系统缺乏客观性和可靠性,而记录特定运动参数的自动化方法在心理和社会功能方面往往缺乏有效性。为了弥补这些不足,我们将两种方法结合起来,一种是精细的行为编码系统,另一种是用于视频和音频数据的注释工具。NEUROGES-ELAN系统是一种有效且用户友好的研究工具,用于分析手部动作行为,包括手势、自我触摸、移动和动作。自2009年首次发表于《行为研究方法》以来,该工具已用于跨学科研究项目,共分析了来自不同文化背景的467个人,包括患有精神疾病和脑损伤的受试者。部分基于这些研究的新见解,该系统在方法和概念上进行了修订。本文介绍了该系统的修订版,包括对可靠性的详细研究。修订版提高的可重复性使NEUROGES-ELAN成为一个适合对手部动作行为与手势以及认知、情感和互动过程之间的关系进行基础实证研究以及开发自动化运动行为识别方法的系统。