**3. Results**

#### *3.1. Demographic Characteristics of Participants*

We recruited 21 participants for this study, including a martial arts teacher, nine undergraduate students who have not learned Baduanjin (novice students), and 11 undergraduate students who had completed the Baduanjin course (senior students). All participants gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the University of Malaya Research Ethics Committee (UM.TNC2/UMREC–558). The demographic characteristics of the students are shown in Table 2. For each mean duration of the eight motions shown in Table 3, we measured all participants three times with IMU, resulting in 63 motion data.


**Table 2.** Demographic characteristics of the students.


#### **Table 3.** Mean duration of Baduanjin.

#### *3.2. Di*ff*erences in Motion Accuracy between Novice and Senior Students on Original Frames*

Algorithms explained in the data analysis section were coded with Matlab R2018b. Independent sample T-tests and Mann–Whitney U tests were used to assess the differences in motion accuracy of novice and senior students.

Before assessing macro differences, we assessed the normality of original frames data using the Shapiro–Wilk test (see Table 4).


**Table 4.** Normality of data of groups using the Shapiro-Wilk test.

From Table 4, we can see that the data of the groups on Motions 2, 3, and 4 were normally distributed (*p* > 0.05), whereas the others were not. Therefore, we assessed the differences in motion accuracy of Motions 2, 3, and 4 between novice and senior students using independent sample T-tests

(see Table 5). The differences in the motion accuracy of other motions between novice and senior students were assessed using Mann–Whitney U tests (see Table 6).

**Table 5.** Differences in motion accuracy between novice and senior students on original frames (using the independent sample T-test).


1Number of motions; 2 Mean of differences in motion between teacher and students; 3 2-tailed.

**Table 6.** Differences in motion accuracy between Novice students and senior students on original frames (using the Mann-Whitney U test).


1 Number of motions; 2 Mann-Whitney U; 3 2-tailed.

From Tables 5 and 6, we can see significant differences (*p* < 0.05 or *p* < 0.01) in motion accuracy of all eight motions between novice and senior students. The differences in motion accuracy between the teacher and senior students were lower than the differences in motion accuracy between the teacher and novice students.

We also evaluated the difference in motion accuracy on each skeleton point between novice and senior students (Figure 6).

From Figure 6, we found that out of the 17 points on eight motions of Baduanjin, there were significant differences in the motion accuracy between novice and senior students for some points. For example, in Motion 1, there were significant differences in motion accuracy between the two groups at the head and neck (points 8 and 9) and the right upper limb (points 10, 11, and 12).

**Figure6.**Differencesinmotionaccuracyofpoints betweennoviceandseniorstudentsonoriginalframes.

 *3.3. Di*ff*erences in Motion Accuracy between Novice and Senior Students on Key-Frames*

3.3.1. Compression Rate and Reconstruction Error of Two Different Key-Frames Extraction Methods

Motion accuracy is assessed based on key-frames. In this study, we chose two methods to extract key-frames. In the key-frames extraction method on inter-frame pitch, we selected different thresholds (0.1, 0.5, 1.0, 1.5, 2.0) to extract key-frames and evaluated the compression rate and the reconstruction error of corresponding key-frames on different thresholds. The results are shown in Table 7.


**Table 7.** Compression rate and reconstruction error of corresponding key-frames on inter-frame pitch.

1 Compression rate (%); 2 Reconstruction error.

Table 7 shows significant differences in the compression rates of the different motions extracted under the same threshold. We can see when the threshold value is set to 1 for obtaining key-frames using the inter-frame pitch, there was a difference in average compression rates ranging from 7.08% to 20.78% for the eight motions of Baduanjin. Moreover, when the threshold value increased, the number of key-frames decreased, which decreased the compression rate. However, the error of motion reconstruction also increased. Based on the data in Table 7, it can be seen that in the five preset values, the compression rate and reconstruction error of the extracted key-frames are relatively reasonable when the threshold is 1. In the other key-frames extraction method on clustering, we chose di fferent compression rates (5, 10, 15, 20, 25) to extract key-frames and evaluate the reconstruction error on di fferent key-frames. The results are shown in Table 8.



1 Compression rate (%) of key-frames.

From Table 8, we can see that as the compression rate increases, the error of motion reconstruction decreases. When the compression rate increased from 5% to 15%, the reconstruction error dropped sharply. But when the compression ratio increased from 15% to 25%, the reconstruction error decrease tended to be smooth. It can be seen that, in the five preset values, the compression rate and reconstruction error of the extracted key frames were relatively reasonable when the preset compression rate is 15%.

#### 3.3.2. Di fferences in Motion Accuracy on Key-Frames

The di fferences in motion accuracy on key-frames between novice and senior students are shown in Tables 9 and 10.


**Table 9.** Di fferences in motion accuracy on the key-frames on inter-frame pitch between novice and senior students.

**Table 10.** Di fferences in motion accuracy on the key-frames on clustering between novice and senior students.


1 Compression rate (%) of key-frames.

From the results of the key-frames on clustering, the motion accuracy of the eight motions of novice and senior students were significantly di fferent. This result is consistent with the result based

on the original frames. However, on the key-frames of inter-frame pitch on five different thresholds, there was no significant difference in motion accuracy between the two groups in Motion 7.

The differences in motion accuracy of points between the two groups on key-frames were also evaluated. Figure 7 shows the results on the key-frames of inter-frame pitch when the setting threshold = 1.

**Figure 7.** Differences in motion accuracy of points between novice and senior students on the key-frames of inter-frames pitch (Threshold = 1).

From Figures 6 and 7, we find that there was a difference between the results on the original frame and the key-frames on the inter-frame pitch. When there was a significant difference in motion accuracy between the two groups, we set the point to 1, otherwise, it was 0. Then, we evaluated the correlation between the results on the original frames and different key-frames on the Kendall correlation coefficient test (see Figures 8 and 9).

The results for key-frame extraction on inter-frame pitch show that when the threshold value was 0.1, the result of the differences in motion accuracy on the key-frames was highly correlated with the result based on the original frame (Kendall coefficient of points in each motion is higher than 0.7 except for Motion 7). However, when the threshold was 0.1, the compression rates of the key-frames were higher. As shown in Table 7, when the threshold was 0.1, the compression rate of each motion exceeded 50%. For key-frames extraction on clustering, there is a high correlation when the compression rate is 0.1. The Kendall coefficient of points in each motion is higher than 0.7 except for Motion 5, where the coefficient was 0.63.

We also tested the mean processing time for using DTW to calculate the distances between motions on original frames and key-frames (Table 11).

**Figure 8.** The Kendall coefficient of differences between skeleton points based on two difference methods (on the original frames and the key-frames on inter-frame pitch).

**Figure 9.** The Kendall coefficient of differences between skeleton points based on two difference methods (on the original frames and the key-frames on clustering).


**Table 11.** The mean processing time on the original frames and the key-frames.

1 Key-frames on inter-frames pitch (Threshold = 1); 2 Key-frames on clustering (compression rate = 15%).

From Table 11, the processing time on the key-frames is lower than original frames. Therefore, using key-frames can effectively decrease data processing time.
