Gait Analysis
One human gait cycle.Copyright 1992 Perry J. Gait analysis: Normaland pathological function. Thorofare (NJ): SLACK via U.S. Department of Veterans Affairs http://www.rehab.research.va.gov/jour/11/484/page459.html
In this open-ended, hands-on activity that provides practice in engineering data analysis, students are given gait signature metric (GSM) data for known people types (adults and children). Working in teams, they analyze the data and develop models that they believe represent the data. They test their models against similar, but unknown (to the students) data to see how accurate their models are in predicting adult vs. child human subjects given known GSM data. They manipulate and graph data in Excel® to conduct their analyses.
Engineers often create predictive models from collected data to attempt to dynamically represent systems and how they function. Much of the engineering design process is related to problem analysis, data collection, modeling, model testing and model refinement. In this activity, students perform these tasks, which are similar to what real engineers do. For instance, software engineers determine the parameters that a software application must meet to be successful. They design and test the developed software and refine it. Civil engineers gather data about where roads, bridges and buildings will be built and then develop models to explore scenarios about how input such as moisture, wind, temperature and soil types are anticipated affect the structures. Models are developed and tested. These types of projects require data analysis and modeling skills that students learn in this activity.
After this activity, students should be able to:
- Analyze data.
- Define a model relating to the data.
- Make predictions using the developed model.
