Analyzing the “YES!” motion (MIII)

The “YES!” motion was introduced in the last entry where I discussed how we discovered an interesting aspect from the mechanics of pitching.

The “YES!” motion consists of doing some sort of a swiping / swinging motion starting from your hand being at a distance from the core of one’s body and eventually pulling it in and contracting your elbows close to one’s body.

This motion is prevalent in pitching and especially for educating young and amateur pitchers. It’s important because when the arm collapses inward towards the body it’s aiding the swinging arm to not run into obstacles during the twist as well as making sure the balance remains at the center of the body to prevent a breakdown.

In addition to how important the motion is, we agreed that as an assistance movement, it’s often overlooked and when we watch a pitcher in a baseball game, you don’t really notice what’s going on with their non-dominant arm as the focus tends to be drawn towards the baseball itself. So it’s nice to find out how a seemingly non-significant motion has such a significant value.

Looking at our film documentation of ourselves pitching, we again did the same frame-to-frame breakdown and jotted down notes supporting the action.

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Again, this was helpful for us to focus on the target area of our selected movement, and it’s helpful have this kind of reference to go back to whenever we need some sort of visual aid.

Following these analyses we proceeded with jotting down actions we believe resemble or consists of the YES motion, including:

• Apple picking
• Swiping a BIG screen
• Bicep curls / pull-ups (many workout routines involving the arm)
• “Come here!”— motion of inviting someone over
• Lifting something from the ground
• Rowing

Machine Learning

It was finally time to test with the machine learning technology!

We organized ourselves by collecting four sets of data, all “YES!” motions but from different directions:

1. Swing from right side to center then “YES!”
2. Swing from left side to center then “YES!”
3. Swing from bottom to center then “YES!” (curling motion)
4. Swing from top to center then “YES!” (apple picking motion)

Visual reference:

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To test the technology, we recorded each gesture 30 times this time around, as discussed before, we thought about trying to train more data to hopefully enhance the accuracy. Then with improved code (after a series of panic and anxiety from errors) provided by the teachers, we put the data to test. We noticed again that the technology is able to distinguish the swings from the left and right sides— when the movement moves across the x-axis the technology can easily predict correctly, but again, when the x-axis remains unchanged but the coordinates are only changing on the y-axis, the prediction became iffy and inaccurate. When we tried it again making the curling and apple picking motions more dramatic and unique from each other the results were more or less completely accurate. We didn’t delve too much into this after the second iteration, however, it’s at least revealing to know that the technology works and the differentiation is somewhat successful.

Felt Quality

After the analysis and testing the technology for our “YES!” motion, we proceeded to discuss the psychological aspects of our movement. We’ve been paying a lot of attention the motor aspects of our movement and have somehow neglected the other yet almost more important aspect for this module, how it feels to perform this action.

The Felt Quality of a movement refers to the sensation or feeling in the body (Loke & Anderson 2010). Following the Felt Quality model again from Loke & Anderson’s paper for analyzing dancers and falling, we wrote down a list of what we felt when we performed the movement first-hand. It consists of:

• Expressing extreme content
• Becoming smaller
• Hiding / Shielding / Crouching
• Swinging
• Regaining balance
• Staying out of the way
• Dragging self towards object
• Keeping to oneself
• Grasping (but not actually grasping anything)
• Sense of completion
• Beginning of a run, but actually staying still
• Pulling in
• “I want this, but I can’t have it”
• Protecting, “my precious”
• Shutting down

This analysis was significant as it revealed a diverse range of understandings of the process and experience of the motion of saying “YES!”, it revealed that on the surface, the motion may appear to only be used to express contentedness. But when you simply look at the body language and ignore the social aspects and your preconception about the action itself, you may find yourself viewing the motion in a complete different way and a completely different attitude may be conveyed— such as hiding and shielding as opposed to cheering for being first in a race— they’re so different yet a similar body language can be seen!