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面部运动和形态的定量评估。

Quantitative evaluation of facial movement and morphology.

作者信息

Vimercati Sara Laura, Rigoldi Chiara, Albertini Giorgio, Crivellini Marcello, Galli Manuela

机构信息

Department of Bioengineering, Politecnico di Milano, Milan, Italy.

出版信息

Ann Otol Rhinol Laryngol. 2012 Apr;121(4):246-52. doi: 10.1177/000348941212100410.

Abstract

OBJECTIVES

The aim of our study was to quantitatively analyze facial motion kinematics by means of an optoelectronic system. In particular, we defined a set of easily recognizable reference points for markerization, and tested the applicability of our markerization method for an exhaustive characterization of the subjects' facial motion through the definition of some kinematic parameters.

METHODS

Thirty healthy subjects (mean age, 24.6 +/- 1.0 years; 15 female and 15 male) participated in the study. A set of markers (diameter, 3 mm) was positioned on several reference points of the face, and some parameters were computed for the characterization of facial morphology and movement, such as ranges of motion, angles, times, and distances.

RESULTS

The protocol was tested for inter-rater and intra-rater reliability by use of intraclass correlation, of which the results were good (between 0.4 and 0.75) to excellent (greater than 0.75). The parameters were useful for characterizing the resting position, mimicry, and speaking movements, and highlighted some distinctions between men and women in facial morphology.

CONCLUSIONS

The protocol can be applied to a variety of facial movements, including speaking. Future works could address the use of the protocol in subjects with disorders and the integrated analysis of kinematic parameters and voice spectrography.

摘要

目的

我们研究的目的是通过光电系统对面部运动学进行定量分析。具体而言,我们定义了一组易于识别的参考点用于标记,并通过定义一些运动学参数来测试我们的标记方法对详尽表征受试者面部运动的适用性。

方法

30名健康受试者(平均年龄24.6±1.0岁;15名女性和15名男性)参与了该研究。一组标记物(直径3毫米)被放置在面部的几个参考点上,并计算了一些用于表征面部形态和运动的参数,如运动范围、角度、时间和距离。

结果

通过组内相关系数对该方案进行了评分者间和评分者内信度测试,结果良好(0.4至0.75之间)至优秀(大于0.75)。这些参数有助于表征静息位置、表情和说话动作,并突出了男性和女性在面部形态上的一些差异。

结论

该方案可应用于包括说话在内的各种面部运动。未来的工作可以探讨该方案在患有疾病的受试者中的应用以及运动学参数与语音频谱分析的综合分析。

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