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Comparison between using spectral analysis of electrogoniometer data and observational analysis to quantify repetitive motion and ergonomic changes in cyclical industrial work

机译:比较用电测角计数据的频谱分析和观察分析来量化周期性工业工作中的重复运动和人体工程学变化

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Spectral analysis of continuously measured joint angles using an electrogoniometer was considered as a potentially efficient method for quantifying exposure to physical stress in repetitive manual work. The method was previously demonstrated in the laboratory but has not yet been tested extensively in the field. Spectral analysis was compared against observational analysis, consisting of time- and-motion study and posture classification. Six industrial jobs were selected: (1) press operation, (2) large parts hanging, (3) product packaging, (4) small parts hanging, (5) parts counting and sorting and (6) construction vehicle operation. The posture angle data were synchronized with activities on the video using an interactive multimedia video data acquisition system. Motion for every joint was analyzed using both spectral analysis and observational analysis. Joint angles for the wrist, elbow and shoulder were directly measured using electrogoniometers. Visual posture classification involved determining joint angles from a frozen videotape image sampled three times per s. Repetitiveness was quantified for observational analysis using time study to measure the frequency that specific motions repeat, while spectral analysis measured repetitiveness as the frequency where spectral peaks occurred. Spectral analysis agreed closely with observational analysis. Correlation between the repetition frequencies obtained using time study and spectral analysis was 0.97, with no statistically significant difference observed. Average sustained posture was quantified as the mean, and posture deviation as the RMS angle of joint motion. No statistically significant differences between data obtained using posture classification or spectral analysis were observed for either posture deviation or sustained posture. Since posture classification was very limited in resolution and often contained measurement errors caused by poor joint visibility, the correlation between the postural classification and spectral analysis was 0.77 for sustained posture and 0.53 for posture deviation. When considering only large motions that exceeded the posture classification angle precision, the correlation between postural classification and spectral analysis was 0.8l for sustained posture and 0.81 for posture deviation. Spectral analysis of electrogoniometer data were, therefore, an efficient method for analyzing repetitive manual work that obtained equivalent results, and was more precise than observational analysis.
机译:使用电子测角计对连续测量的关节角度进行频谱分析被认为是定量重复劳动中暴露于物理应力的潜在有效方法。该方法先前已在实验室中得到证明,但尚未在该领域进行广泛测试。光谱分析与观察分析进行了比较,观察分析包括时间和运动研究以及姿势分类。选择了六个工业工作:(1)冲压操作,(2)大件悬挂,(3)产品包装,(4)小件悬挂,(5)零件计数和分类以及(6)工程车辆操作。使用交互式多媒体视频数据采集系统将姿势角度数据与视频上的活动同步。使用频谱分析和观察分析来分析每个关节的运动。腕部,肘部和肩膀的关节角度直接用电子测角仪测量。视觉姿势分类涉及从每秒钟采样3次的冻结录像带图像确定关节角度。使用时间研究来量化重复性,以进行观察性分析,以测量特定运动重复的频率,而频谱分析则将重复性测量为出现频谱峰值的频率。光谱分析与观察分析非常吻合。使用时间研究和频谱分析获得的重复频率之间的相关性为0.97,没有观察到统计学上的显着差异。将平均持续姿势量化为平均值,将姿势偏差量化为关节运动的RMS角度。使用姿势分类或频谱分析获得的数据之间在姿势偏差或持续姿势方面均未观察到统计学上的显着差异。由于姿势分类的分辨率非常有限,并且通常包含由于关节可见度差而导致的测量误差,因此姿势分类与频谱分析之间的相关性对于持续姿势为0.77,对于姿势偏差为0.53。当仅考虑超过姿势分类角度精度的大运动时,姿势分类与频谱分析之间的相关性对于持续姿势为0.8l,对于姿势偏差为0.81。因此,电测角仪数据的频谱分析是一种有效的方法,可以分析重复的手工作业,并获得了同等的结果,并且比观察分析更为精确。

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