GAIT AND HEIGHT ANALYSIS |
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Class Gait Analysis
(Class Data) https://docs.google.com/spreadsheets/u/1/d/150b1-yV3A_sxjVM_x5nBJOxQmjUJ6iwnHH4JuQfsgto/edit?usp=drive_web Height Prediction Model
https://docs.google.com/document/d/1hS-6TwoKtgGlT-tzbRhwCY_DsdDF2296-XU__1eqLoI/edit Through comparing the class gait data, I realized how a taller a person is, the less amount of steps they took. I also learned how to read the graph; every bump in the graph, that represents each steps.
It was hard to compare between each gait data because everyone had different variables to begin with. For example, every had different distance walked, amount of steps took, and places where they put the phone. However, in order to compare the datas, I minimize all the datas to 25 seconds. I only took everyone’s “X” values because it’s horizontal to the ground that it shows acceleration changes. I observed that taller they were, they had bigger changes of acceleration between each steps and took less steps. On the other hand, shorter peole had more stable acceleration and took more steps. I predict that this was because shorter people had shorter legs that caused them to take more step even when they walk in same amount of time. However, taller people needed greater acceleration than shorter people because it take more effort and force to move their heavy and long legs forward. |
Group Gait Analysis
https://docs.google.com/spreadsheets/d/1HNLsjzTxQ2x_k4v8fCN1Eekx2SePebgFGiRs7SlvEPI/edit#gid=0 1) downloaded an accelerometer app and put our phone to our stomach 2) Recorded the data/what happened between 7 steps 3) measured height, leg length, and distance walked. 4) repeated three trials to have an accurate data New/Unknown Data
We were given three unknown data to analyze and figure out whether they were data of Kids or adults. I analyzed the gait data by looking at graphs. I compared the column graphs of children and adults. I found out that the children had higher average gap(ex:AVG-A_GapV) and longer average step time(ex:AVG-Step_Time). My partner and I made a conclusion that this was due to children having shorter legs. Since they have shorter legs, it requires them to take more and slower steps than adults. Then I looked at the unknown datas and found out that unknown 1 and 3 had higher average gap and longer average step time than unknown 2. Also, unknown 1 and 3 had similar AVG-A_GapV and AVG-Step_Time to Child 1, 2, 3, and 4. Only unknown 2 had similar AVG-A_GapV and AVG-Step_Time to data of Adult 1, 2, 3, and 4. |