Data analysis 2.1

This week, I finished the first letter specific feature's analysis -- symmetry for letter m.

I took these steps to extract the feature

Step 1: scan the file, and if the gesture is m, find the bounding box and compute the middle line function y = b

Step 2: pass the b value (from step 1) and the corresponding list of points to find all crossing points, and store them in another list - cross point list. If two adjacent points Point 1 and Point 2 are on different sides of the line y = b, I consider the second point as a crossing point.

Step 3: filter some of the gestures according to the number of crossing points.

            Only 1 crossing point: maybe a gesture that was not logged properly

Too many crossing points (e.g. 12 crossing points in Gesture 31 from Subject 10): the subject wrote two m…

Step 4: compute length of segments, and check which is on the left and which is on the right.

Step 5: get the ratio between two segments. Here, I use right_segment_length / left_segment_length, and compute average value for each level

The result shows that there are only significant differences in limited conditions. I think this is a potential feature, but still need adjustment to investigate in more details.

Data Analysis 1.3

I finished statistical tests for basic features like dimensions of bounding box, pen pressure and length of the gesture. I mainly use statistical methods including t-test and ANOVA. The results are not as good as expected, but I still found something. For example, the gesture length in the session 1. However, how to combine my result with external dataset and gave a generalised explanation is not easy to do.

In the next phase, I will focus on the letter-specific geometrical features for letter a, g and m.

Data Analysis 1.2

Today, I added the what subjects wrote during the experiment to the logging files. As it was almost impossible to collect what they wrote on-fly without recognition package, I took letters down by observing them writing. However, the problem is that I have to add the letter tag manually in the logging to facilitate further analysis.

It took me longer time than I expected, and I also encountered several formatting problems. Finally, all the gesture has the corresponding letter tag at the end of the gesture. It helps me to understand the importance of constructing logging files. If the format is not right, it may bring a lot of problems in the future stages.

Data Analysis 1

I have finished the user experiment on Tuesday, and started the first phase of data analysis.

First of all, I computed the accuracy of all questions to get an overview of the task performance. Then, I did the Friedman ANOVA on the subjective feedback to validate my experiment design (i.e. difficulty for each level). 

In the next step, I'll continue to analyse the features I've tested on the external dataset, and focus on the letter specific features.

Conduct the Experiment

This week, I conduct my user experiment in the lab. Up to now, I have finished 7 out of 12, and all experiments are expected to be finished before next Tuesday. Since I've got some experience from the summer project, this time everything goes smoothly.

Next week, I will start the analysis of my dataset, and compare some of the result from the external dataset. I think it would be good to get some inspiration from my dataset and in turn do further analysis to the external dataset.

Experiment Implementation 5

This week I improved my implementation according to the result in the pilot study and finalised the experiment on Wednesday. I also finished booking subjects, and the experiment will start on next Monday. It will take about 1 hour and 10 minutes per subject, including 10 minutes instruction explanation and training time.

As the logging format is similar to the external dataset, so I think after the experiment, I could modify previous data analysis scripts to get some basic feature results. However, I still need explore more "letter specific" features before the end of the analysis.

Experiment Implementation 4

Today, I do a formal pilot study to tune the parameter of the experiment, such as time arrangement, task difficulty and settings of the tablet.

First of all, I increased the task difficulty a bit, which I think could make the task harder to complete than before. Then, I also adjust some time arrangement, like resting time between two sections and between two figures as well. Finally, the angle of the tablet is tested by three separate pilot runs. Taking two factors into consideration -- the average pen pressure and the proportion of points which reached the pressure limit, I adjust the angle to be 30 degrees from the vertical plane.

Additionally, I also finish the consent form and the subjective ratings.