The second project we completed in STEM this year was Gait Analysis. We dove into the details of how a person walks and what characteristics can be used to determine who is walking. Our guiding question for this project was "What is the relationship between the height and gait frequency for walking humans?" To answer this, we measured leg lengths, height, weight, which foot was the test subject's dominant, and if they had any health issues that might affect their walking. We then experimented with how far they had to walk and how fast, looking into the differences between walking and jogging. Finally, we compiled all our data and created a predictive model to determine an unknown person's characteristics based on their gait. Our predictive model, equations, and more information about the project can be found in our written report below.
To conduct our experiments, we downloaded the "Physics Toolbox Accelerometer" app and duct taped one of our group member's phones to the subjects' leg. We chose to attach the phone to the leg rather than the subjects' center of gravity because it is creates the most motion when someone walks. This way, our results had bigger numbers and created more visible trends. Our first step in the actual experiment was gathering constant data like shoe size, height, weight, etc. These were constant throughout the experiment and we matched the characteristics with our data to create baseline graphs. Once we had that data, we recorded how long it took each subject to walk 10 steps. For our next phase of the experiment we decided to roughly measure out 5 meters. However, there was a discrepancy within the data for the running times because of the fact that we cannot really control how fast a person runs. One person might be “jogging” while the other considers it“running.” Because of this, we decided to focus more on the walking aspect. With all our data collected and graphed we concluded this project with a predictive model and written report.
To conduct our experiments, we downloaded the "Physics Toolbox Accelerometer" app and duct taped one of our group member's phones to the subjects' leg. We chose to attach the phone to the leg rather than the subjects' center of gravity because it is creates the most motion when someone walks. This way, our results had bigger numbers and created more visible trends. Our first step in the actual experiment was gathering constant data like shoe size, height, weight, etc. These were constant throughout the experiment and we matched the characteristics with our data to create baseline graphs. Once we had that data, we recorded how long it took each subject to walk 10 steps. For our next phase of the experiment we decided to roughly measure out 5 meters. However, there was a discrepancy within the data for the running times because of the fact that we cannot really control how fast a person runs. One person might be “jogging” while the other considers it“running.” Because of this, we decided to focus more on the walking aspect. With all our data collected and graphed we concluded this project with a predictive model and written report.
Concepts
Engineering analysis- The application of scientific and analytic principles to reveal the state and properties of a system.
Accelerometer- A device that measures the physical acceleration experienced by an object. For our project we used the "Physics Toolbox Accelerometer" app to measure our gait.
Dynamicity- In terms of gait analysis, the quantification of variations in kinematic or kinetic parameters within a step.
Gait- The stride of a human as s/he moves his/her limbs.
Metric- A quantitative indicator of a characteristic or attribute.
(Predictive) Model- In technology, a description of observed or predicted behavior of some system, simplified by ignoring certain details. Models allow complex systems to be understood and their behavior predicted.
Symmetry- In terms of gait analysis, the quantification of differences between left-foot and right-foot steps.
Variability- In terms of gait analysis, the quantification of fluctuations from one stride to the next.
Frequency- The number of crests of a wave that move past a given point in a given unit of time. The most common unit of frequency is the hertz (Hz).
Engineering analysis- The application of scientific and analytic principles to reveal the state and properties of a system.
Accelerometer- A device that measures the physical acceleration experienced by an object. For our project we used the "Physics Toolbox Accelerometer" app to measure our gait.
Dynamicity- In terms of gait analysis, the quantification of variations in kinematic or kinetic parameters within a step.
Gait- The stride of a human as s/he moves his/her limbs.
Metric- A quantitative indicator of a characteristic or attribute.
(Predictive) Model- In technology, a description of observed or predicted behavior of some system, simplified by ignoring certain details. Models allow complex systems to be understood and their behavior predicted.
Symmetry- In terms of gait analysis, the quantification of differences between left-foot and right-foot steps.
Variability- In terms of gait analysis, the quantification of fluctuations from one stride to the next.
Frequency- The number of crests of a wave that move past a given point in a given unit of time. The most common unit of frequency is the hertz (Hz).
Reflection
Overall, the Gait Analysis project was a little tricky. It required a lot more planning than some of our previous projects and a lot more data analysis. Through this project I learned how to use graphs to create models and come up with useful equations from it. This is a skill that I will definitely use again in STEM and in other classes. Another positive from this project is that I learned a lot about how humans walk and how this subject can be applied. I am really interested in shows such as Criminal Minds and the forensic and behavioral science they use. Gait analysis is frequently used by law enforcement when they analyze any foot prints they find to determine characteristics about the suspect such as height, weight, and whether or not they have a limp. Something I can improve on is my patience with certain parts of a project. At times, I would get frustrated when our data didn't quite add up and coming up with an equation was very difficult. Another thing I can work on is time management. This project had a lot of overlap with another mini project we were working on and I didn't leave enough time to work on my part of the report. I finished it in the end and our report turned out really solid but I could space my work out more for the next project using our Ghantt chart. In the end, our project and report was extremely successful and I was really proud of myself and our group's effort.
Overall, the Gait Analysis project was a little tricky. It required a lot more planning than some of our previous projects and a lot more data analysis. Through this project I learned how to use graphs to create models and come up with useful equations from it. This is a skill that I will definitely use again in STEM and in other classes. Another positive from this project is that I learned a lot about how humans walk and how this subject can be applied. I am really interested in shows such as Criminal Minds and the forensic and behavioral science they use. Gait analysis is frequently used by law enforcement when they analyze any foot prints they find to determine characteristics about the suspect such as height, weight, and whether or not they have a limp. Something I can improve on is my patience with certain parts of a project. At times, I would get frustrated when our data didn't quite add up and coming up with an equation was very difficult. Another thing I can work on is time management. This project had a lot of overlap with another mini project we were working on and I didn't leave enough time to work on my part of the report. I finished it in the end and our report turned out really solid but I could space my work out more for the next project using our Ghantt chart. In the end, our project and report was extremely successful and I was really proud of myself and our group's effort.
Here is our official written report:
Below is our micro-presentation that summarizes the main points of the written report: