The Way We Stand: A Sequential Case Study on Foot Angle Dataset
Description
Background: This study quantifies the significance of foot angle as it relates to common biometric data to assess its use in the clinical realm. Research Question: What is the average foot angle of 73 orthopedic patients in a case study, and what is the relationship between foot angle and 10 surveyed biometric data points (age, weight, height, biological makeup, shoe size, orthotic use, physical activity level, competitive sports history, lower extremity injury history, and reason for visiting doctor)? Methods: The study’s duration was December 9, 2021, to April 7, 2022 at the Arizona Institute of Motion. Participants were informed of measurement steps and the purpose of the study and had the option to decline participation. Participants were asked to walk down a hallway as a distraction to collect the most accurate data to the participants’ stance. Participants filled out a 10-question survey of biometric data. Correlational calculations and linear regressions were performed to support or reject the existence of a relationship between foot angle and biometric data. Results: The average left foot angle was 26.35 degrees, and the average right foot angle was 26.54 degrees. A strong positive correlation was found between left and right foot angles. The optimized linear regression model had an adjusted r² value of 0.549 for left foot angle against right foot angle, shoe size, and height, and an adjusted r² value of 0.522 for right foot angle against left foot angle, shoe size, and height. Foot angle had no other relationships with the other biometric data and had limited numerical significance. Significance: Additional study is required to confirm its numerical importance, but foot angle may continue to be used in clinical settings in conjunction with gait analysis and qualitative assessments for musculoskeletal function. Foot angle is most useful to supplement qualitative data. Notes on dataset: The data used in this study was processed using Python 3 systems. Data includes linear regression models, correlational heat maps, and other graphs. An Excel Spreadsheet is also provided to view raw subject data, both biometric and qualitative, collected from the 10-question survey.