Keywords

1 Introduction

When saying Japanese greetings ceremony, first of all we have a bow. Greeting ceremonies around the world vary by country, region, time and occasion [1]. In Japan many people bow at the scene of greeting, gratitude or apology. We see bowing in various scenes such as business scene and restaurant, apology press conference, and also public place in train. The characteristics of the Japanese bowing are that scenes and usage are diverse.

Although it is not as daily as in Japan, there are actions of bowing in the world as well. In Christianity bow to represent respect and obedience. In Islam and Judaism it is positioned as being done only to God. Looking at the Western area, the bow of Europe is a movement of “Bow and scrape” which the nobility and the butler see in a movie, etc., draw a right foot, attach a right hand to the body, and move the left hand horizontally horizontally in a motion (On the other hand, a woman pulls one leg diagonally in the back of the back, lightly bends the knee of the other foot, and greets the spine with the spine stretched, the action called “courtesy”) [2]. However, it goes without saying that bowing in everyday life is not common in Europe and the Middle Eastern countries because it has a religious background or restricted to aristocracy as described above.

There is a bow in East Asia as well. In China, there was a bow from ancient times, but in modern times it is considerably simplified in everyday life. Korea’s “Sitting Bow” (Joru) is a series of actions, such as bending the knees from the standing posture and lightly attaching the forehead to the back of the hand and then standing up again, and it exists as an important manner often used [3]. Also, in Thailand there is a daily greeting action called Wai.

In Japan, bowing is done on a daily basis, but scenes actually receiving guidance are few. In this research, we investigated and analyzed what kind of characteristics the non-experts bowed, what kind of motion the expert would evaluate.

2 Experiment Method

2.1 Recording of Bowing Videos of Unskilled People

For experts to evaluate the bow of non-experts, first of all, non-experts bowed videos were recorded. A marker was added to measure each motion index of a bow of an unskilled person. The marker was attached to the head, shoulders, waist and knees of non-experts. Each bowing motion was recorded with a video camera (Fig. 1).

Fig. 1.
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Measurement graphics

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2.2 Motion Analysis and Extraction of Motion Indicators

From the positions of markers of recorded videos, motion analysis was performed by Photoron’s two-dimensional motion analysis software TEMA and various motion indices were measured and calculated from the position information of each marker during bowing motion. The various motion indicators are as shown in Table 3.

2.3 Creating an Answer Form

We used a questionnaire form by Google form in order to improve the smooth response environment of experts. We created a form that can be evaluated with 7 full marks by watching 41 bowing videos of non-experts I made 1 for the worst evaluation and 7 for the best evaluation.

2.4 Answers by Experts

Three persons were selected for responding by experts. Both of them are manners lecturers for enterprises, nine years, fourteen years, fourteen years respectively. Experts had a questionnaire form prepared in advance and asked 41 people to evaluate the video by watching one movie and evaluating the impression in seven levels.

3 Result

3.1 Reliability of Evaluation

Intra-Class Correlation (ICC) was calculated using the evaluation value for 41 videos by 3 evaluators (Table 1).

Table 1. ICC
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Regarding reproducibility between examiners, ICC (2, 1) was .305. The average value of three evaluators was calculated and the correlation coefficient with the evaluation value of each evaluator was calculated (Table 2).

Table 2. Correlation among evaluators
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Relationship between impression evaluation of bow and action indicator Table 3 shows the average value of each index of bowing movement.

Table 3. Motion indicator
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Table 4 shows correlation coefficients between the values ​​of impression evaluation of the bow and action index.

Table 4. Correlation between skill evaluations and behavior indicators
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In evaluator A, significant positive correlation was found between angle at the end of flexion of neck, angle at the end of stationary of neck, angle at the end of flexion of waist, angle at the end of stationary of waist, flexion speed of neck, and extension speed of neck. And significant negative correlation was found between synchronization ratio at the time of completion of flexion, at the start of stationary and synchronization ratio at the time of completion of stationary, at the start of extension.

In evaluator B, significant positive correlation was found between stationary time, total time, center time of bowing movement and center time of stationary. And significant negative correlation was found between angle at the end of flexion of waist, angle at the end of stationary of waist, extension speed of waist, percentage of flexion time and percentage of extension time.

Evaluator C did not show any significant correlation with any of the variables.

3.2 Principal Component Analysis to Multiple Regression Analysis, Cluster Analysis

Principal Component Analysis

Principal component analysis was performed using all variables (Table 5). As a result, it was possible to extract from the first principal component to the sixth principal component.

Table 5. Principal component analysis
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The first principal component is a component related to the flexion angle and flexion extension speed of the site A and was named “neck component”. The second principal component is composed of a variable indicating the length of time of operation and is named “motion time component”. The third principal component is a component related to the bending angle and flexion extension speed of waist, and is named “waist component”. Since the fourth principal component is a component showing the difference between flexion time and extension time, it is named “motion time balance component”. Since the fifth principal component is composed of variables concerning flexion time and rest time, it was named “stationary time component”. The sixth principal component is composed of variables of the final angle difference and the final angle, so it is named “final posture component”.

Multiple Regression Analysis

Multiple regression analysis was performed for each evaluator by the forced input method with six principal component scores as explanatory variables and evaluation points as objective variables (Table 6). Significant regression was obtained for evaluators A, B and average points. Considering the standard regression coefficient, in Evaluator A, the first principal component (neck component) and the third principal component (waist component) were significant positive coefficients. In the evaluator B, the second principal component (motion time component) was a significant positive coefficient, and the fifth principal component (stationary time component) was a significant negative coefficient. On average, the fifth principal component (stationary time component) was a significant negative coefficient.

Table 6. Multiple regression analysis
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Cluster Analysis

Cluster analysis (square Euclidean distance) by Ward method was performed using principal component scores. As a result, it was judged from the shape of the dendrogram that it is appropriate to classify into 5 clusters. The values of each variable are shown for each cluster (Table 7). As a result of one-factor analysis of variance, the fifth cluster has the shortest operation time, and the tuning rate at which the cervical flexion angle is the largest is also large, so it is named “fast and big synchronized action type”. Next, since the fourth cluster has the longest operation time and the large waist flexion angle, it was named “slowly large motion type”. Because Cluster 3 has a short operation time and a small waist flexion angle, it is named “Fast and waist flextion angle small size type”.

Table 7. Cluster comparison
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Since Cluster 2 has a small flexion angle of the neck and deep flexion angle of the lumbar region, it is named “Synchronized no action type”. Cluster 1 was named as “asymmetric time type” because the value of the operation time balance component is the largest. For the motion index, significant main effects were observed for all variables except for the final angle B, the final angle difference, and the final synchronization rate.

As a result of one factor analysis analysis with five cluster types as explanatory variables and evaluator’s evaluation points as objective variables, a significant main effect was seen in evaluator 2, but other than evaluator 2, significant No main effect was seen.

4 Discussion

Evaluation by three experts resulted in a slight variation. There are features in action indicators that evaluate highly for each evaluator, but when you examine them individually, they are evaluated according to circumstances in which evaluators are placed within the scope of general guidance points.

First, the evaluator A will be described. The evaluator A is evaluated focusing on whether the neck is straight or whether the waist angle is a moderate angle (30 degrees as a salute). The evaluator A is an evaluator who is good at teaching to the person who receives a customer at the dental reception. Since the beauty of the motion of the upper body greatly affects the impression of the customer at the reception, the evaluator A emphasizes the bow that bent from the waist, which made the neck straight, which is consistent with this result. The “bowed bent from the waist with the neck straightened” is a general guidance point in bowing.

Next, the evaluator B will be described. Evaluator B focuses on the length of the bowing rest time and the depth of the bending angle. Evaluator B is an evaluator who is good at teaching in business manners for enterprises. In business etiquette, since respect for partner and confidence influence impression on opponent, emphasis is placed on a clear bow of motion, it seems that bow and long bending angle deep bowing evaluated.

Finally, we will talk about the evaluator C. In the evaluator C, we could not find a significant motion index this time. Evaluator C is an evaluator who provides customer service instruction for employees in the bridal industry. When conducting customer service guidance in the bridal industry, customer service guidance assuming various scenes such as greetings, respect, appreciation, apologies are necessary. The current operation index was a linear analysis by time, angle and speed. We think that it is necessary to find appropriate indicators other than these motion indices or to require further analysis which is not linear analysis in the motion indicator.

In cluster analysis, by classifying into five clusters, it was possible to categorize patterns that are likely to be inexperienced by non-experts. “Asymmetric time type (10 people)” “Synchronized no action type (10 people)” “Fast, waist flexion angle small size (8 people)” “slowly large motion type (7 people)” “Fast and big synchronized action type (3 people)”.

In line with these and the significant action indicators, as in Cluster 1, non-expert who has the characteristic of “long flexion time” and unskilled person having characteristics of “long time and large waist angle” as in Cluster 2 Together, it turns out that it accounts for a majority. From these, it is understood that non-experts tend to express “slowly politely and deeply” when fearing to carefully bow the bow, and in presence or absence of synchronization there is noticed that “it is better not to bend the neck”. It turns out that there is a difference in bowing behavior depending on whether or not

Cluster 3 has a waist flexion angle of about 30 degrees. Because it is said that 30 degrees is appropriate for expert salute, this cluster can be said to be “done” in terms of the waist flexion angle. However, as for stationary time, further comparison and examination with experts is necessary.

In Cluster 4, the total time is long and in Cluster 5 the total time is short. The waist flexion angle is deep in both Cluster 4 and 5. Both clusters seem to have commonality at first glance, but it is quite different as an expression of actual bow. Cluster 4 has deep flexion with long operation time, so it has a relaxed atmosphere and it is bowing. On the other hand, since the cluster 5 performs a deep bending with a short operation time, it is a very stiff bow. It turned out that there was a very wide variation in the theoretical operating time considered by unskilled persons.

5 Conclusion

In this study, it was found that the viewpoint of the experts was not uniform in one word. Since no significant motion indicator was found for evaluator C, we believe that it is necessary to expand the scope not only for linear analysis but also for quadratic curve analysis and to clarify new behavior indicators in the future. In addition to this, we performed multiple regression analysis and cluster analysis from the principal component analysis, but we would like to expand the range of factor analysis, multiple regression analysis and cluster analysis.