References

Works cited

These resources guided our work and helped us figure out the motion model:

Aksoy, Selim, and Ahmet Dirican. “Step Counting Using Smartphone Accelerometer and Fast Fourier Transform.” Sigma Journal of Engineering and Natural Sciences, vol. 8, 1 Feb. 2017.

Gave us an idea of how the FFT maps to an accelerometer and how to use it to count steps, which is similar to what we wanted. It also gave us a jumping off point to find future research that was more applicable to our topic.

Ecruhue. “Ecruhue/Pedometer-Step-Counting-Algorithm: Collected Real Time Walking Data(Patterns) with Gyroscope, Use Fast Fourier Transformation to Extract the Clustering Features, and Build the Step Counting Algorithm for Pedometer.” GitHub, https://github.com/ecruhue/Pedometer-Step-Counting-Algorithm.

Gave us a jumping off point for implementing this project in code.

Kang, Xiaomin, et al. “A Novel Walking Detection and Step Counting Algorithm Using Unconstrained Smartphones.” Sensors, vol. 18, no. 1, 2018, p. 297., https://doi.org/10.3390/s18010297.

We based our motion model off of the data from this study. They did a bunch of research on how mems accelerometers work and how they're able to count steps when used inside of a smartphone. While it wasn't exactly what we were doing, it was so close that we were able to use a number of parts from the motion model, that made the rest of our work much easier.

Scarlett, Jim. “Enhancing the Performance of Pedometers Using a Single Accelerometer.” Analog Devices, 2007, https://www.sgbotic.com/products/appnotes/sensors/47076299220991AN_900.pdf.

Gave us an idea of what our plots and output would look like. Analog Devices, a company local to this area, created this to analyze their accelerometers for use in pedometers, so we could see what our data might look like in an optimal, ideal sense.